****                   MendelIHT Version 1.4.6                  ****
****     Benjamin Chu, Kevin Keys, Chris German, Hua Zhou       ****
****   Jin Zhou, Eric Sobel, Janet Sinsheimer, Kenneth Lange    ****
****                                                            ****
****                 Please cite our paper!                     ****
****         https://doi.org/10.1093/gigascience/giaa044        ****

Running sparse Multivariate Gaussian regression
Number of threads = 32
Link functin = GLM.IdentityLink()
Sparsity parameter (k) = 4678
Prior weight scaling = off
Doubly sparse projection = off
Debias = off
Max IHT iterations = 20000
Converging when tol < 0.0001 and iteration ≥ 5:

Iteration 1: loglikelihood = 1.9900806693628624e6, backtracks = 0, tol = 0.05038374598183472
Iteration 2: loglikelihood = 2.0109317364920506e6, backtracks = 3, tol = 0.0008774580995211358
Iteration 3: loglikelihood = 2.0223371598561592e6, backtracks = 3, tol = 0.0009518148583178098
Iteration 4: loglikelihood = 2.03079113895094e6, backtracks = 3, tol = 0.0009061352247563808
Iteration 5: loglikelihood = 2.005878397786369e6, backtracks = 3, tol = 0.0009953013187424269
Iteration 6: loglikelihood = 2.0603467294320364e6, backtracks = 3, tol = 0.0010096515593293449
Iteration 7: loglikelihood = 1.9533083706142209e6, backtracks = 3, tol = 0.0017813920227501409
Iteration 8: loglikelihood = 2.0659200390816713e6, backtracks = 2, tol = 0.0017802469304129336
Iteration 9: loglikelihood = 1.9674891749258635e6, backtracks = 3, tol = 0.0018060949593481524
Iteration 10: loglikelihood = 2.0984850300611453e6, backtracks = 2, tol = 0.0016815414957471759
Iteration 11: loglikelihood = 1.9628524110016613e6, backtracks = 3, tol = 0.0019122194242959074
Iteration 12: loglikelihood = 1.9953950755137852e6, backtracks = 1, tol = 0.0032100929475124117
Iteration 13: loglikelihood = 2.134420299294826e6, backtracks = 2, tol = 0.0014002572277623838
Iteration 14: loglikelihood = 1.9820533364195963e6, backtracks = 3, tol = 0.002343532315266765
Iteration 15: loglikelihood = 2.0244690125655136e6, backtracks = 1, tol = 0.002400953632550284
Iteration 16: loglikelihood = 2.0747637273851056e6, backtracks = 2, tol = 0.0017778945841499735
Iteration 17: loglikelihood = 2.0820936319051548e6, backtracks = 3, tol = 0.0011666483997611744
Iteration 18: loglikelihood = 2.0784581574943273e6, backtracks = 3, tol = 0.001169105137762058
Iteration 19: loglikelihood = 2.0870332717288947e6, backtracks = 3, tol = 0.001146502230359068
Iteration 20: loglikelihood = 2.0735056672301306e6, backtracks = 3, tol = 0.0014127084031846514
Iteration 21: loglikelihood = 2.1092655173647446e6, backtracks = 3, tol = 0.0010826853789894582
Iteration 22: loglikelihood = 2.0387033808109327e6, backtracks = 3, tol = 0.0015550912224117806
Iteration 23: loglikelihood = 2.0815266100712088e6, backtracks = 2, tol = 0.0015895231476213884
Iteration 24: loglikelihood = 2.095231388956582e6, backtracks = 3, tol = 0.0012809251684493632
Iteration 25: loglikelihood = 2.0761130039050975e6, backtracks = 3, tol = 0.0012217139518787723
Iteration 26: loglikelihood = 2.1239037792211315e6, backtracks = 3, tol = 0.0010545723930451643
Iteration 27: loglikelihood = 2.0321072628110414e6, backtracks = 3, tol = 0.0014876522850894073
Iteration 28: loglikelihood = 2.1295632602353063e6, backtracks = 2, tol = 0.001410780438207139
Iteration 29: loglikelihood = 2.027978179979342e6, backtracks = 3, tol = 0.0015087564178323995
Iteration 30: loglikelihood = 2.1599685018256987e6, backtracks = 2, tol = 0.001320345673293699
Iteration 31: loglikelihood = 2.001867933652855e6, backtracks = 3, tol = 0.001780705595515023
Iteration 32: loglikelihood = 2.082622832407198e6, backtracks = 1, tol = 0.0021217620372830375
Iteration 33: loglikelihood = 2.1495527512423275e6, backtracks = 3, tol = 0.000965058152033605
Iteration 34: loglikelihood = 2.0259116886105011e6, backtracks = 3, tol = 0.0016587507725767691
Iteration 35: loglikelihood = 2.0312970620722948e6, backtracks = 1, tol = 0.002362528975112182
Iteration 36: loglikelihood = 2.2148238253478445e6, backtracks = 2, tol = 0.0011882594080824564
Iteration 37: loglikelihood = 2.0181435024022656e6, backtracks = 3, tol = 0.001753432991373205
Iteration 38: loglikelihood = 2.0641219008934414e6, backtracks = 1, tol = 0.0020858838853845714
Iteration 39: loglikelihood = 2.0838199297806188e6, backtracks = 2, tol = 0.0015408113478073524
Iteration 40: loglikelihood = 2.189620807827518e6, backtracks = 3, tol = 0.0008847724496806284
Iteration 41: loglikelihood = 1.992478036472042e6, backtracks = 3, tol = 0.002031661148853347
Iteration 42: loglikelihood = 2.0089453806722441e6, backtracks = 0, tol = 0.003908920409155713
Iteration 43: loglikelihood = 2.1552014861200764e6, backtracks = 1, tol = 0.001772192031995265
Iteration 44: loglikelihood = 2.0493719228377747e6, backtracks = 3, tol = 0.0013528342429486979
Iteration 45: loglikelihood = 2.2243734627317344e6, backtracks = 2, tol = 0.0011586824300012983
Iteration 46: loglikelihood = 2.0089218215035712e6, backtracks = 3, tol = 0.0017948910249127442
Iteration 47: loglikelihood = 2.220630920103323e6, backtracks = 1, tol = 0.0016944490573090616
Iteration 48: loglikelihood = 2.0069499701707442e6, backtracks = 3, tol = 0.0021297266659799016
Iteration 49: loglikelihood = 2.013386386689867e6, backtracks = 0, tol = 0.003119714645649605
Iteration 50: loglikelihood = 2.213292050679892e6, backtracks = 1, tol = 0.0016496159679171498
Iteration 51: loglikelihood = 2.0160692717641839e6, backtracks = 3, tol = 0.0017480741339970611
Iteration 52: loglikelihood = 2.1997969699243177e6, backtracks = 1, tol = 0.0016840978443799217
Iteration 53: loglikelihood = 2.0181911071184543e6, backtracks = 3, tol = 0.0016501551682077344
Iteration 54: loglikelihood = 2.2004568006173023e6, backtracks = 1, tol = 0.0016499817762860396
Iteration 55: loglikelihood = 2.0235330577899446e6, backtracks = 3, tol = 0.0015634898194833052
Iteration 56: loglikelihood = 2.170812670613558e6, backtracks = 1, tol = 0.0017202863124603164
Iteration 57: loglikelihood = 2.0470444754757779e6, backtracks = 3, tol = 0.0013792225249812404
Iteration 58: loglikelihood = 2.0776082394863572e6, backtracks = 1, tol = 0.0019799195735751224
Iteration 59: loglikelihood = 2.12241893960124e6, backtracks = 2, tol = 0.0013427431164154127
Iteration 60: loglikelihood = 2.1421340218982114e6, backtracks = 3, tol = 0.0009456740957209783
Iteration 61: loglikelihood = 2.09061447478625e6, backtracks = 3, tol = 0.0011905909320125735
Iteration 62: loglikelihood = 2.1006031407901812e6, backtracks = 2, tol = 0.001441236423538556
Iteration 63: loglikelihood = 2.219611214164869e6, backtracks = 3, tol = 0.0008154969924141831
Iteration 64: loglikelihood = 2.0189418952340614e6, backtracks = 3, tol = 0.0017770627589015378
Iteration 65: loglikelihood = 2.2454176237800927e6, backtracks = 1, tol = 0.0015940240021240935
Iteration 66: loglikelihood = 2.04548429021641e6, backtracks = 3, tol = 0.0024886702242575423
Iteration 67: loglikelihood = 2.0693911922531084e6, backtracks = 1, tol = 0.0019325471686598426
Iteration 68: loglikelihood = 2.193308765187779e6, backtracks = 2, tol = 0.0011412859554409942
Iteration 69: loglikelihood = 2.032574178840933e6, backtracks = 3, tol = 0.0016395953956698363
Iteration 70: loglikelihood = 2.149434916376025e6, backtracks = 1, tol = 0.0017320145921458654
Iteration 71: loglikelihood = 2.0833802139931053e6, backtracks = 3, tol = 0.0012076013548597254
Iteration 72: loglikelihood = 2.14366049390195e6, backtracks = 2, tol = 0.00127818165978589
Iteration 73: loglikelihood = 2.0972324735145476e6, backtracks = 3, tol = 0.001152703441782094
Iteration 74: loglikelihood = 2.100924463468199e6, backtracks = 2, tol = 0.0014446502267616574
Iteration 75: loglikelihood = 2.240521456217655e6, backtracks = 3, tol = 0.0007915302740268169
Iteration 76: loglikelihood = 2.0219407600268205e6, backtracks = 3, tol = 0.0017859706263973786
Iteration 77: loglikelihood = 2.252960443614641e6, backtracks = 1, tol = 0.0015740931339963404
Iteration 78: loglikelihood = 2.0723374134699078e6, backtracks = 3, tol = 0.0015372448444983184
Iteration 79: loglikelihood = 2.1628936054292754e6, backtracks = 2, tol = 0.0013414315617515805
Iteration 80: loglikelihood = 2.0792355804215334e6, backtracks = 3, tol = 0.001359369670374256
Iteration 81: loglikelihood = 2.158516705932944e6, backtracks = 2, tol = 0.0012208194054970384
Iteration 82: loglikelihood = 2.0820174188306518e6, backtracks = 3, tol = 0.0012579022454415076
Iteration 83: loglikelihood = 2.147566902092409e6, backtracks = 2, tol = 0.0012798450969462743
Iteration 84: loglikelihood = 2.098976908501251e6, backtracks = 3, tol = 0.0011386442140024296
Iteration 85: loglikelihood = 2.260423602805943e6, backtracks = 3, tol = 0.000743339018165003
Iteration 86: loglikelihood = 2.0548616258156728e6, backtracks = 3, tol = 0.0012772502064846303
Iteration 87: loglikelihood = 2.0906182864377438e6, backtracks = 1, tol = 0.0019460949039068651
Iteration 88: loglikelihood = 2.1179743133990816e6, backtracks = 2, tol = 0.0013590401224310327
Iteration 89: loglikelihood = 2.1841777931823893e6, backtracks = 3, tol = 0.0008571794285733704
Iteration 90: loglikelihood = 2.0510021936558438e6, backtracks = 3, tol = 0.001516441930185564
Iteration 91: loglikelihood = 2.1081595541578345e6, backtracks = 1, tol = 0.0018528412069092528
Iteration 92: loglikelihood = 2.240645651817327e6, backtracks = 3, tol = 0.0007771684393001073
Iteration 93: loglikelihood = 2.0144502916577552e6, backtracks = 3, tol = 0.0019498867220850776
Iteration 94: loglikelihood = 2.0599493212469392e6, backtracks = 0, tol = 0.0028964540937730324
Iteration 95: loglikelihood = 2.0811008627313552e6, backtracks = 1, tol = 0.001918687793152971
Iteration 96: loglikelihood = 2.1812415009878147e6, backtracks = 2, tol = 0.0011612140079527023
Iteration 97: loglikelihood = 2.064419422520322e6, backtracks = 3, tol = 0.0013787499313985389
Iteration 98: loglikelihood = 2.0754646075993306e6, backtracks = 1, tol = 0.0020834981435896055
Iteration 99: loglikelihood = 2.217495548537287e6, backtracks = 2, tol = 0.001079074359467388
Iteration 100: loglikelihood = 2.0372044209000533e6, backtracks = 3, tol = 0.0018111697974049438
Iteration 101: loglikelihood = 2.211330719290115e6, backtracks = 1, tol = 0.0015953525593296453
Iteration 102: loglikelihood = 2.038980160487034e6, backtracks = 3, tol = 0.0015575935841046196
Iteration 103: loglikelihood = 2.19954353400168e6, backtracks = 1, tol = 0.001621137226969656
Iteration 104: loglikelihood = 2.0461935574680362e6, backtracks = 3, tol = 0.0015547864681930588
Iteration 105: loglikelihood = 2.154703102429959e6, backtracks = 1, tol = 0.0017183481605445217
Iteration 106: loglikelihood = 2.104797325303328e6, backtracks = 3, tol = 0.001273467214015098
Iteration 107: loglikelihood = 2.1193890596978767e6, backtracks = 2, tol = 0.0013921944738075867
Iteration 108: loglikelihood = 2.21807797075762e6, backtracks = 3, tol = 0.000823725876766388
Iteration 109: loglikelihood = 2.0342769583671363e6, backtracks = 3, tol = 0.001753858121876696
Iteration 110: loglikelihood = 2.2577399436020376e6, backtracks = 1, tol = 0.0015334939710686302
Iteration 111: loglikelihood = 2.0387305511493357e6, backtracks = 3, tol = 0.0018458430815414613
Iteration 112: loglikelihood = 2.170787911716063e6, backtracks = 1, tol = 0.0016302565555558499
Iteration 113: loglikelihood = 2.0926469568276824e6, backtracks = 3, tol = 0.001452176586047505
Iteration 114: loglikelihood = 2.1580189272087663e6, backtracks = 2, tol = 0.001242975494167873
Iteration 115: loglikelihood = 2.111702569260869e6, backtracks = 3, tol = 0.0011133619454067704
Iteration 116: loglikelihood = 2.2690753893042174e6, backtracks = 3, tol = 0.0007173001922917944
Iteration 117: loglikelihood = 2.0536453501908784e6, backtracks = 3, tol = 0.0013306565282855088
Iteration 118: loglikelihood = 2.127509220295493e6, backtracks = 1, tol = 0.0019499384314643703
Iteration 119: loglikelihood = 2.1972018084005085e6, backtracks = 3, tol = 0.0008478923179150532
Iteration 120: loglikelihood = 2.0594388347722343e6, backtracks = 3, tol = 0.0014889212763118847
Iteration 121: loglikelihood = 2.1113152250255924e6, backtracks = 1, tol = 0.0018243308618203242
Iteration 122: loglikelihood = 2.2724276155869365e6, backtracks = 3, tol = 0.000709370377603268
Iteration 123: loglikelihood = 2.0812575015285513e6, backtracks = 3, tol = 0.0012022522974976522
Iteration 124: loglikelihood = 2.2182735347841326e6, backtracks = 2, tol = 0.0011282037460337666
Iteration 125: loglikelihood = 2.0372580250655552e6, backtracks = 3, tol = 0.0017971177836425352
Iteration 126: loglikelihood = 2.2107418191322503e6, backtracks = 1, tol = 0.0015574210829616
Iteration 127: loglikelihood = 2.046454546663451e6, backtracks = 3, tol = 0.0016917602371319125
Iteration 128: loglikelihood = 2.1649928284604996e6, backtracks = 1, tol = 0.0017156792528310815
Iteration 129: loglikelihood = 2.105630354989947e6, backtracks = 3, tol = 0.0010992446446625723
Iteration 130: loglikelihood = 2.128483741156745e6, backtracks = 2, tol = 0.0013408093914403737
Iteration 131: loglikelihood = 2.2099108244300717e6, backtracks = 3, tol = 0.0008047021071518289
Iteration 132: loglikelihood = 2.045160492420855e6, backtracks = 3, tol = 0.0016454474213397786
Iteration 133: loglikelihood = 2.189445084868342e6, backtracks = 1, tol = 0.0016015576266343603
Iteration 134: loglikelihood = 2.065426535451197e6, backtracks = 3, tol = 0.0015219313641185483
Iteration 135: loglikelihood = 2.1065011672896426e6, backtracks = 1, tol = 0.0018436673554839524
Iteration 136: loglikelihood = 2.1185339280634085e6, backtracks = 2, tol = 0.0013625607657274407
Iteration 137: loglikelihood = 2.2594020271784533e6, backtracks = 3, tol = 0.0007287366042677498
Iteration 138: loglikelihood = 2.0343132829045397e6, backtracks = 3, tol = 0.001702026049155023
Iteration 139: loglikelihood = 2.043268422040414e6, backtracks = 0, tol = 0.0028899750227985963
Iteration 140: loglikelihood = 2.2221060843442385e6, backtracks = 1, tol = 0.0015231932960506375
Iteration 141: loglikelihood = 2.040001221708189e6, backtracks = 3, tol = 0.0016022709886698277
Iteration 142: loglikelihood = 2.2644684596771644e6, backtracks = 1, tol = 0.0014634687784579855
Iteration 143: loglikelihood = 2.0387960657234706e6, backtracks = 3, tol = 0.0014513695459363843
Iteration 144: loglikelihood = 2.266199738744527e6, backtracks = 1, tol = 0.0014325716615494436
Iteration 145: loglikelihood = 2.0453276448320188e6, backtracks = 3, tol = 0.0014704388393481315
Iteration 146: loglikelihood = 2.196648411990688e6, backtracks = 1, tol = 0.0011665347240000894
Iteration 147: loglikelihood = 2.0538394906372656e6, backtracks = 3, tol = 0.000807528948430441
Iteration 148: loglikelihood = 2.1194078486254597e6, backtracks = 1, tol = 0.0008148318217732434
Iteration 149: loglikelihood = 2.1968883748121606e6, backtracks = 3, tol = 0.00040742948765303455
Iteration 150: loglikelihood = 2.0997481290261773e6, backtracks = 3, tol = 0.0008503294345826261
Iteration 151: loglikelihood = 2.1458329645448653e6, backtracks = 2, tol = 0.000526704095504647
Iteration 152: loglikelihood = 2.1362541943698633e6, backtracks = 3, tol = 0.0005074752547441148
Iteration 153: loglikelihood = 2.1877507259579822e6, backtracks = 3, tol = 0.000364905740421141
Iteration 154: loglikelihood = 2.104982133968437e6, backtracks = 3, tol = 0.0005529615250062488
Iteration 155: loglikelihood = 2.1309516643678015e6, backtracks = 2, tol = 0.0006059899555882985
Iteration 156: loglikelihood = 2.1678854177862923e6, backtracks = 3, tol = 0.000506771053411672
Iteration 157: loglikelihood = 2.118794656008157e6, backtracks = 3, tol = 0.00047934810894908407
Iteration 158: loglikelihood = 2.2184293778129118e6, backtracks = 3, tol = 0.00045021440783187677
Iteration 159: loglikelihood = 2.0558703796337137e6, backtracks = 3, tol = 0.0006355884202575274
Iteration 160: loglikelihood = 2.135127548360603e6, backtracks = 1, tol = 0.0009506894546722875
Iteration 161: loglikelihood = 2.138955983847988e6, backtracks = 3, tol = 0.00044587981987244266
Iteration 162: loglikelihood = 2.180377714983443e6, backtracks = 3, tol = 0.00034768389483320433
Iteration 163: loglikelihood = 2.0882044547065897e6, backtracks = 3, tol = 0.0006087611725886817
Iteration 164: loglikelihood = 2.1764111196342716e6, backtracks = 2, tol = 0.0005041422226133847
Iteration 165: loglikelihood = 2.0893518098158487e6, backtracks = 3, tol = 0.0004578088505738707
Iteration 166: loglikelihood = 2.167212647874247e6, backtracks = 2, tol = 0.00045413190179268
Iteration 167: loglikelihood = 2.098137830502131e6, backtracks = 3, tol = 0.0003999188962616939
Iteration 168: loglikelihood = 2.151231986760035e6, backtracks = 2, tol = 0.00041685785149159704
Iteration 169: loglikelihood = 2.1049539641733775e6, backtracks = 3, tol = 0.0004009615845455356
Iteration 170: loglikelihood = 2.132773355369486e6, backtracks = 2, tol = 0.0006192589832834701
Iteration 171: loglikelihood = 2.1321875878682574e6, backtracks = 3, tol = 0.0004116128762973569
Iteration 172: loglikelihood = 2.162622279817749e6, backtracks = 3, tol = 0.00029849920035891693
Iteration 173: loglikelihood = 2.11206210092323e6, backtracks = 3, tol = 0.00038232261198865224
Iteration 174: loglikelihood = 2.231396966653416e6, backtracks = 3, tol = 0.00036264830140178615
Iteration 175: loglikelihood = 2.066499956737074e6, backtracks = 3, tol = 0.0005162884957301909
Iteration 176: loglikelihood = 2.0800506018076187e6, backtracks = 1, tol = 0.0007001484625546791
Iteration 177: loglikelihood = 2.121757948667086e6, backtracks = 2, tol = 0.0006080435204961242
Iteration 178: loglikelihood = 2.164041661878097e6, backtracks = 3, tol = 0.00036707984596393435
Iteration 179: loglikelihood = 2.1125493617788176e6, backtracks = 3, tol = 0.00047338797780645936
Iteration 180: loglikelihood = 2.2278244560655183e6, backtracks = 3, tol = 0.00034715449034051067
Iteration 181: loglikelihood = 2.0702430381033325e6, backtracks = 3, tol = 0.0005100147702460022
Iteration 182: loglikelihood = 2.0755566243261446e6, backtracks = 1, tol = 0.0006778000972430951
Iteration 183: loglikelihood = 2.1260864238197627e6, backtracks = 2, tol = 0.000638158076007401
Iteration 184: loglikelihood = 2.1529515130169494e6, backtracks = 3, tol = 0.0003948320278710568
Iteration 185: loglikelihood = 2.1167803700377326e6, backtracks = 3, tol = 0.0005001868318441282
Iteration 186: loglikelihood = 2.1696567674766816e6, backtracks = 3, tol = 0.00038421051384710913
Iteration 187: loglikelihood = 2.1007442397164013e6, backtracks = 3, tol = 0.00046000850030282497
Iteration 188: loglikelihood = 2.1125936033904483e6, backtracks = 2, tol = 0.00046000718164074245
Iteration 189: loglikelihood = 2.151969943431387e6, backtracks = 3, tol = 0.0004521641672365613
Iteration 190: loglikelihood = 2.1315847792196437e6, backtracks = 3, tol = 0.0003638633945962383
Iteration 191: loglikelihood = 2.1386377612261157e6, backtracks = 3, tol = 0.00036386242921536665
Iteration 192: loglikelihood = 2.143113860238862e6, backtracks = 3, tol = 0.0003225657290815448
Iteration 193: loglikelihood = 2.1281544999421937e6, backtracks = 3, tol = 0.0003566563644434738
Iteration 194: loglikelihood = 2.1542747369703026e6, backtracks = 3, tol = 0.0003566553452035477
Iteration 195: loglikelihood = 2.1165207592119426e6, backtracks = 3, tol = 0.0003957049843705375
Iteration 196: loglikelihood = 2.1681974694540384e6, backtracks = 3, tol = 0.0003957038522012247
Iteration 197: loglikelihood = 2.1019560747020217e6, backtracks = 3, tol = 0.0004529220892381571
Iteration 198: loglikelihood = 2.111075408384865e6, backtracks = 2, tol = 0.00045920496708569126
Iteration 199: loglikelihood = 2.160908209219382e6, backtracks = 3, tol = 0.0004592025189193924
Iteration 200: loglikelihood = 2.1245544415559554e6, backtracks = 3, tol = 0.00037604892330117545
Iteration 201: loglikelihood = 2.1545018586626397e6, backtracks = 3, tol = 0.00037604796671002324
Iteration 202: loglikelihood = 2.1277576876522438e6, backtracks = 3, tol = 0.0003529853844619751
Iteration 203: loglikelihood = 2.154663071685997e6, backtracks = 3, tol = 0.00035298449374201064
Iteration 204: loglikelihood = 2.125957904089718e6, backtracks = 3, tol = 0.0003541006189361698
Iteration 205: loglikelihood = 2.1586806940798266e6, backtracks = 3, tol = 0.0003540997252931031
Iteration 206: loglikelihood = 2.120930201754748e6, backtracks = 3, tol = 0.00036743577533100886
Iteration 207: loglikelihood = 2.1684626788319536e6, backtracks = 3, tol = 0.0003674348484306873
Iteration 208: loglikelihood = 2.110480665198967e6, backtracks = 3, tol = 0.0004016558563673626
Iteration 209: loglikelihood = 2.1852015332676666e6, backtracks = 3, tol = 0.0004016548435467603
Iteration 210: loglikelihood = 2.094420978341211e6, backtracks = 3, tol = 0.0004620934737992685
Iteration 211: loglikelihood = 2.127122739453131e6, backtracks = 2, tol = 0.000462092312952255
Iteration 212: loglikelihood = 2.149073500258875e6, backtracks = 3, tol = 0.0004061612328189355
Iteration 213: loglikelihood = 2.134504256023e6, backtracks = 3, tol = 0.00036545378538922876
Iteration 214: loglikelihood = 2.151263694801825e6, backtracks = 3, tol = 0.00033624440989189335
Iteration 215: loglikelihood = 2.1307390331254e6, backtracks = 3, tol = 0.00035731278243725587
Iteration 216: loglikelihood = 2.161420897873269e6, backtracks = 3, tol = 0.0003303182925919878
Iteration 217: loglikelihood = 2.111345730421113e6, backtracks = 3, tol = 0.0005931280719934227
Iteration 218: loglikelihood = 2.2198541217043214e6, backtracks = 3, tol = 0.0003520025473435658
Iteration 219: loglikelihood = 2.0674121621083925e6, backtracks = 3, tol = 0.000530810073672502
Iteration 220: loglikelihood = 2.0802453250101027e6, backtracks = 1, tol = 0.0009068626348938993
Iteration 221: loglikelihood = 2.118743917519046e6, backtracks = 2, tol = 0.000610915550166059
Iteration 222: loglikelihood = 2.173943302376626e6, backtracks = 3, tol = 0.00038792640503411185
Iteration 223: loglikelihood = 2.0959604414530087e6, backtracks = 3, tol = 0.0004512990104943123
Iteration 224: loglikelihood = 2.1225771499235416e6, backtracks = 2, tol = 0.000603512693875594
Iteration 225: loglikelihood = 2.1431867114838115e6, backtracks = 3, tol = 0.00041675637941670693
Iteration 226: loglikelihood = 2.146097664171706e6, backtracks = 3, tol = 0.0003253793938476526
Iteration 227: loglikelihood = 2.1245823905507037e6, backtracks = 3, tol = 0.0003639785357279841
Iteration 228: loglikelihood = 2.165280216700994e6, backtracks = 3, tol = 0.00036394105704291163
Iteration 229: loglikelihood = 2.1051729297961e6, backtracks = 3, tol = 0.00043108533116369
Iteration 230: loglikelihood = 2.112455170064195e6, backtracks = 2, tol = 0.0004549267823970406
Iteration 231: loglikelihood = 2.1669403195079486e6, backtracks = 3, tol = 0.00045461760638725653
Iteration 232: loglikelihood = 2.120449592825093e6, backtracks = 3, tol = 0.0003870344258813992
Iteration 233: loglikelihood = 2.16897763509953e6, backtracks = 3, tol = 0.0003867909523988232
Iteration 234: loglikelihood = 2.1140871715912265e6, backtracks = 3, tol = 0.00039351932777104706
Iteration 235: loglikelihood = 2.1840056227765167e6, backtracks = 3, tol = 0.0003932793475635078
Iteration 236: loglikelihood = 2.0974526638220083e6, backtracks = 3, tol = 0.0004460590314393221
Iteration 237: loglikelihood = 2.1231724792792476e6, backtracks = 2, tol = 0.0005023275340699327
Iteration 238: loglikelihood = 2.174231508649808e6, backtracks = 3, tol = 0.0003875320318355067
Iteration 239: loglikelihood = 2.102265453105193e6, backtracks = 3, tol = 0.0005880829627590299
Iteration 240: loglikelihood = 2.1158705395461316e6, backtracks = 2, tol = 0.0005839989730237215
Iteration 241: loglikelihood = 2.178022904696439e6, backtracks = 3, tol = 0.0004296705983518452
Iteration 242: loglikelihood = 2.1046078257496804e6, backtracks = 3, tol = 0.0004514567900692958
Iteration 243: loglikelihood = 2.10560390155328e6, backtracks = 2, tol = 0.0005788861969377995
Iteration 244: loglikelihood = 2.2658852924751104e6, backtracks = 3, tol = 0.0003657815048342822
Iteration 245: loglikelihood = 1.9426022250326735e6, backtracks = 3, tol = 0.0013200266928250362
Iteration 246: loglikelihood = 1.9813795462608342e6, backtracks = 0, tol = 0.00037348910437558696
Iteration 247: loglikelihood = 2.1230292832159954e6, backtracks = 0, tol = 0.0006382099987085374
Iteration 248: loglikelihood = 2.1991486695088404e6, backtracks = 3, tol = 0.0003343251474620296
Iteration 249: loglikelihood = 2.0482656200500657e6, backtracks = 3, tol = 0.0003893480061863913
Iteration 250: loglikelihood = 2.153344808606047e6, backtracks = 1, tol = 0.0003893470689346289
Iteration 251: loglikelihood = 2.1121806200313494e6, backtracks = 3, tol = 0.00032004204951628445
Iteration 252: loglikelihood = 2.1344817253168467e6, backtracks = 2, tol = 0.00027724472839931466
Iteration 253: loglikelihood = 2.1580002666927073e6, backtracks = 3, tol = 0.00024449126441720775
Iteration 254: loglikelihood = 2.137801122171615e6, backtracks = 3, tol = 0.0001906379803723373
Iteration 255: loglikelihood = 2.161402745161536e6, backtracks = 3, tol = 0.00017001725974500546
Iteration 256: loglikelihood = 2.102937510159772e6, backtracks = 3, tol = 0.0002472832424330344
Iteration 257: loglikelihood = 2.114320817646879e6, backtracks = 2, tol = 0.00022507433775646613
Iteration 258: loglikelihood = 2.2094619672525157e6, backtracks = 3, tol = 0.00019172015493109753
Iteration 259: loglikelihood = 2.0712306590700797e6, backtracks = 3, tol = 0.0002393156878907671
Iteration 260: loglikelihood = 2.204375260475316e6, backtracks = 2, tol = 0.00023274439495684317
Iteration 261: loglikelihood = 2.0713137898546816e6, backtracks = 3, tol = 0.00022877450502695
Iteration 262: loglikelihood = 2.208118784110293e6, backtracks = 2, tol = 0.0002278493901191778
Iteration 263: loglikelihood = 2.0690895046335254e6, backtracks = 3, tol = 0.00021299080637670503
Iteration 264: loglikelihood = 2.2358958440539874e6, backtracks = 2, tol = 0.0002095039631457419
Iteration 265: loglikelihood = 2.0536983645421332e6, backtracks = 3, tol = 0.0002274267871948098
Iteration 266: loglikelihood = 2.0956691276563653e6, backtracks = 1, tol = 0.00038393797098513983
Iteration 267: loglikelihood = 2.1541965516693126e6, backtracks = 3, tol = 9.036355595220718e-5

Compute time (sec):     4539.787247180939
Final loglikelihood:    2.2724276155869365e6
Iterations:             267
Trait 1's SNP PVE:      0.0178409194999977
Trait 2's SNP PVE:      0.04232486519501827
Trait 3's SNP PVE:      0.02446916995863271
Trait 4's SNP PVE:      0.03649763922610326
Trait 5's SNP PVE:      0.04818098699173014
Trait 6's SNP PVE:      0.054727051100212754
Trait 7's SNP PVE:      0.0500957663968989
Trait 8's SNP PVE:      0.03320721082638241
Trait 9's SNP PVE:      0.043210706423667464
Trait 10's SNP PVE:      0.03695480443510882
Trait 11's SNP PVE:      0.026776689227920734
Trait 12's SNP PVE:      0.025019994006137407
Trait 13's SNP PVE:      0.023074306682808476
Trait 14's SNP PVE:      0.026883760571690115
Trait 15's SNP PVE:      0.05149786047693182
Trait 16's SNP PVE:      0.05378609502700606
Trait 17's SNP PVE:      0.02677704890338828
Trait 18's SNP PVE:      0.013592562649030856

Estimated trait covariance:
18×18 DataFrame
 Row │ trait1    trait2     trait3     trait4       trait5      trait6     trait7     trait8      trait9     trait10    trait11    trait12    trait13     trait14      trait15     trait16     trait17     trait18
     │ Float64   Float64    Float64    Float64      Float64     Float64    Float64    Float64     Float64    Float64    Float64    Float64    Float64     Float64      Float64     Float64     Float64     Float64
─────┼────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
   1 │ 0.961262   0.661956  0.847897    0.402769     0.33137     0.438768   0.514933   0.769059    0.717984  0.788938   0.811874   0.842331    0.825106    0.804562     0.15278     0.1667      0.395057    0.624435
   2 │ 0.661956   0.948032  0.557685   -0.202822     0.787454    0.884674   0.913248   0.902928    0.907083  0.683842   0.379339   0.481195    0.663295    0.65234     -0.334057   -0.40853    -0.129373    0.388539
   3 │ 0.847897   0.557685  0.954111    0.17979      0.165714    0.353211   0.439503   0.751133    0.676253  0.715209   0.859243   0.945151    0.932864    0.920341     0.0536544   0.0117761   0.147172    0.471077
   4 │ 0.402769  -0.202822  0.17979     0.91354     -0.292047   -0.341377  -0.315482  -0.127349   -0.162637  0.130904   0.365607   0.258307    0.0528884   0.00634373   0.564355    0.794226    0.884544    0.487145
   5 │ 0.33137    0.787454  0.165714   -0.292047     0.945855    0.850106   0.816971   0.632606    0.655814  0.390138   0.0227619  0.0866165   0.293442    0.279834    -0.395466   -0.443924   -0.189301    0.228895
   6 │ 0.438768   0.884674  0.353211   -0.341377     0.850106    0.945628   0.930715   0.791467    0.806598  0.49433    0.15184    0.267006    0.48965     0.464051    -0.476417   -0.519161   -0.229649    0.314126
   7 │ 0.514933   0.913248  0.439503   -0.315482     0.816971    0.930715   0.948291   0.85194     0.849352  0.528883   0.218216   0.352484    0.572323    0.549707    -0.460254   -0.510899   -0.212939    0.352389
   8 │ 0.769059   0.902928  0.751133   -0.127349     0.632606    0.791467   0.85194    0.959712    0.921534  0.746578   0.574092   0.688411    0.826454    0.817697    -0.237145   -0.320405   -0.0910167   0.415239
   9 │ 0.717984   0.907083  0.676253   -0.162637     0.655814    0.806598   0.849352   0.921534    0.944592  0.765394   0.50357    0.611596    0.75971     0.74374     -0.283729   -0.360483   -0.109956    0.410021
  10 │ 0.788938   0.683842  0.715209    0.130904     0.390138    0.49433    0.528883   0.746578    0.765394  0.929658   0.758427   0.706585    0.693838    0.710687     0.161203    0.0330841   0.0859537   0.292251
  11 │ 0.811874   0.379339  0.859243    0.365607     0.0227619   0.15184    0.218216   0.574092    0.50357   0.758427   0.942085   0.888778    0.773427    0.779216     0.335257    0.277824    0.282037    0.365735
  12 │ 0.842331   0.481195  0.945151    0.258307     0.0866165   0.267006   0.352484   0.688411    0.611596  0.706585   0.888778   0.9522      0.89895     0.886257     0.136575    0.105239    0.211036    0.463981
  13 │ 0.825106   0.663295  0.932864    0.0528884    0.293442    0.48965    0.572323   0.826454    0.75971   0.693838   0.773427   0.89895     0.958104    0.934559    -0.108954   -0.146581    0.0570785   0.500088
  14 │ 0.804562   0.65234   0.920341    0.00634373   0.279834    0.464051   0.549707   0.817697    0.74374   0.710687   0.779216   0.886257    0.934559    0.949774    -0.0343858  -0.138736   -0.0268094   0.368425
  15 │ 0.15278   -0.334057  0.0536544   0.564355    -0.395466   -0.476417  -0.460254  -0.237145   -0.283729  0.161203   0.335257   0.136575   -0.108954   -0.0343858    0.903816    0.775911    0.365151   -0.221885
  16 │ 0.1667    -0.40853   0.0117761   0.794226    -0.443924   -0.519161  -0.510899  -0.320405   -0.360483  0.0330841  0.277824   0.105239   -0.146581   -0.138736     0.775911    0.886623    0.678899    0.0942677
  17 │ 0.395057  -0.129373  0.147172    0.884544    -0.189301   -0.229649  -0.212939  -0.0910167  -0.109956  0.0859537  0.282037   0.211036    0.0570785  -0.0268094    0.365151    0.678899    0.931699    0.657207
  18 │ 0.624435   0.388539  0.471077    0.487145     0.228895    0.314126   0.352389   0.415239    0.410021  0.292251   0.365735   0.463981    0.500088    0.368425    -0.221885    0.0942677   0.657207    0.972419

Trait 1: IHT estimated 239 nonzero SNP predictors
239×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.00471012
   2 │    11578  -0.00463269
   3 │    11579   0.00469133
   4 │    11580   0.00472849
   5 │    11581  -0.0046825
   6 │    11584  -0.00264578
   7 │    11590   0.00471954
   8 │    11592  -0.0027023
   9 │    11594   0.000636805
  10 │    11598  -0.00159568
  11 │    18165  -0.00292432
  12 │    18181  -0.00546048
  13 │    18182   0.00329801
  14 │    18183  -0.00546829
  15 │    18184   0.00554066
  16 │    18185   0.0055257
  17 │    18186   0.00549769
  18 │    18187  -0.00212268
  19 │    18188   0.00563077
  20 │    18189   0.00548641
  21 │    41945  -0.00271311
  22 │    41952  -0.0033948
  23 │    41954  -0.0033892
  24 │    41955  -0.00335166
  25 │    41956  -0.00338175
  26 │    41959   0.00283694
  27 │    41963  -0.00280096
  28 │    41964   0.00586928
  29 │    41965   0.005933
  30 │    41966  -0.00267097
  31 │    41967  -0.00277774
  32 │    41968   0.00455319
  33 │    41972  -0.00333181
  34 │    41974   0.00115969
  35 │    41975   0.00495413
  36 │    41977   0.0044084
  37 │    41978   0.00449054
  38 │    41979   0.00443745
  39 │    41985   0.00427564
  40 │    41986   0.00331085
  41 │    41988   0.00340545
  42 │    41989   0.00351642
  43 │    41990   0.0021635
  44 │    41992  -0.00306854
  45 │    41997  -0.00203233
  46 │    42916  -0.00148741
  47 │    42919  -0.00141595
  48 │    42921  -0.00132367
  49 │    42925  -0.00204673
  50 │    42927  -0.00144477
  51 │    42928  -0.00198815
  52 │    42930  -0.00110443
  53 │    42931  -0.00148438
  54 │    42932  -0.00121132
  55 │    42933  -0.0033917
  56 │    42934  -0.00315841
  57 │    42935  -0.00312407
  58 │    42936  -0.00175008
  59 │    42938  -0.00226778
  60 │    42941   0.00198505
  61 │    42942   0.00199288
  62 │    42943   0.0019604
  63 │    42945   0.00202727
  64 │    42947   0.00183771
  65 │    42956  -0.00176205
  66 │    42963   0.00202256
  67 │    45816  -0.00146649
  68 │    45817  -0.00132631
  69 │    45821  -0.00132195
  70 │    45822  -0.00133221
  71 │    45823  -0.00138207
  72 │   146549   0.00287211
  73 │   146552   0.0031126
  74 │   146554   0.00259068
  75 │   146557   0.00257849
  76 │   146560   0.00263047
  77 │   146561   0.00298036
  78 │   146564   0.0026296
  79 │   146566   0.00259495
  80 │   146569   0.00215955
  81 │   146576   0.00334925
  82 │   146579   0.00218768
  83 │   146588  -0.00112548
  84 │   146596   0.00139897
  85 │   158405   0.00243262
  86 │   158406   0.00242973
  87 │   158407   0.00234447
  88 │   158411   0.00183161
  89 │   173361  -0.00176647
  90 │   173406   0.0012602
  91 │   174881   0.000959758
  92 │   174915   0.00100434
  93 │   174926   0.0011466
  94 │   175000   0.00312825
  95 │   175005   0.00316686
  96 │   175041   0.00244595
  97 │   175075   0.00117909
  98 │   175096   0.00138949
  99 │   194353  -0.00327875
 100 │   194409  -0.00325692
 101 │   194415  -0.00336805
 102 │   208944  -0.00344951
 103 │   208947  -0.00481192
 104 │   208949  -0.00472862
 105 │   208951  -0.00643123
 106 │   225486   0.00146613
 107 │   225487   0.00150464
 108 │   225488   0.00183227
 109 │   225489   0.00184639
 110 │   225490   0.00194381
 111 │   225491   0.00199486
 112 │   225497  -0.00152363
 113 │   242599   0.00252065
 114 │   242601  -0.00418907
 115 │   242602  -0.00426918
 116 │   242603  -0.00421438
 117 │   242605  -0.00310714
 118 │   242606  -0.00305167
 119 │   242607  -0.00420668
 120 │   242608   0.00174415
 121 │   242609  -0.00309648
 122 │   242612  -0.0035545
 123 │   260644  -0.00126785
 124 │   260645  -0.00141751
 125 │   266007   0.00241614
 126 │   266008   0.00180544
 127 │   266009   0.00185641
 128 │   266010   0.00184208
 129 │   266011   0.0024606
 130 │   301459  -0.00172766
 131 │   301462  -0.00197477
 132 │   301463  -0.00179225
 133 │   301464  -0.00173041
 134 │   301466  -0.00172706
 135 │   301467  -0.00169377
 136 │   301468  -0.0016237
 137 │   301469  -0.000343863
 138 │   301471  -0.00169073
 139 │   301473  -0.00167896
 140 │   301476  -0.00194694
 141 │   301480  -0.0019745
 142 │   309993  -0.0034135
 143 │   309996  -0.00475265
 144 │   309998   0.00327238
 145 │   310000   0.00358495
 146 │   310003   0.00352566
 147 │   310006   0.00351651
 148 │   310010  -0.00631878
 149 │   310012   0.00372519
 150 │   310013   0.00372128
 151 │   310014  -0.00456318
 152 │   310015  -0.00483135
 153 │   310017   0.00384493
 154 │   310018  -0.00493147
 155 │   310019   0.00394076
 156 │   310020  -0.00489245
 157 │   310027  -0.00318405
 158 │   310033  -0.00468191
 159 │   310037  -0.00408501
 160 │   310039   0.00193109
 161 │   310042  -0.00367486
 162 │   310044  -0.00369731
 163 │   310047   0.00148414
 164 │   310056   0.000930828
 165 │   310062   0.00121721
 166 │   373948   0.00340473
 167 │   373950   0.00371787
 168 │   373951   0.00364648
 169 │   373952  -0.00343002
 170 │   373954  -0.00341165
 171 │   373955   0.00118801
 172 │   373956   0.00294864
 173 │   373962  -0.00187675
 174 │   373966   0.00142513
 175 │   373969  -0.00110871
 176 │   373973  -0.0013648
 177 │   373976   0.00390666
 178 │   373978   0.00176946
 179 │   373979  -0.00394012
 180 │   373987  -0.00253836
 181 │   373988  -0.00117713
 182 │   391781   0.00423058
 183 │   391782   0.00423846
 184 │   391783   0.00420875
 185 │   391787   0.00422023
 186 │   391789   0.00469969
 187 │   391792  -0.0038973
 188 │   391793   0.00330094
 189 │   391795  -0.0033095
 190 │   394184   0.00237349
 191 │   423244   0.00243561
 192 │   423245   0.00230459
 193 │   423246   0.00203546
 194 │   423247   0.00238281
 195 │   423250   0.00243438
 196 │   432754  -0.00706055
 197 │   432757  -0.00449631
 198 │   432759  -0.00722433
 199 │   432795  -0.00223555
 200 │   432801  -0.002144
 201 │   434519  -0.00172041
 202 │   434532  -0.00435202
 203 │   434545  -0.00474759
 204 │   434550   0.00162304
 205 │   434553  -0.00287004
 206 │   434560  -0.00317511
 207 │   434561  -0.00313738
 208 │   434564  -0.00162824
 209 │   434570  -0.00148297
 210 │   434573  -0.003808
 211 │   434574  -0.00379548
 212 │   434594  -0.00286913
 213 │   438345  -0.00534794
 214 │   438448  -0.00471868
 215 │   438455  -0.00490298
 216 │   438466  -0.00365605
 217 │   438469  -0.00589577
 218 │   438476  -0.00341437
 219 │   438479  -0.00491619
 220 │   438483  -0.0036063
 221 │   438489  -0.00296688
 222 │   438492  -0.003061
 223 │   438494  -0.00342765
 224 │   438499   0.00349998
 225 │   438500   0.0035129
 226 │   438505   0.00407919
 227 │   438511  -0.00289902
 228 │   438515  -0.00241789
 229 │   438518  -0.00619292
 230 │   438519   0.00444399
 231 │   438520   0.00586579
 232 │   438521   0.00267511
 233 │   438526   0.00563725
 234 │   438527   0.00171501
 235 │   438529   0.00199569
 236 │   438530  -0.00844705
 237 │   438531   0.00580717
 238 │   438534  -0.00440334
 239 │   449460   0.00058059

Trait 1: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1   8.38164e-7
   2 │        2   0.0165056
   3 │        3   0.00505943
   4 │        4   0.00433833
   5 │        5   0.00148101
   6 │        6  -0.00108373
   7 │        7   0.00114997
   8 │        8  -0.00199949
   9 │        9  -0.00111104
  10 │       10   0.000615633
  11 │       11  -0.000442392
  12 │       12   8.5275e-5
  13 │       13   0.00206544
  14 │       14  -0.000908801

Trait 2: IHT estimated 270 nonzero SNP predictors
270×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.00595413
   2 │    11578  -0.00603106
   3 │    11579   0.00609083
   4 │    11580   0.00605837
   5 │    11581  -0.00595956
   6 │    11584  -0.00371037
   7 │    11590   0.00575494
   8 │    11592  -0.00455211
   9 │    11598  -0.00290291
  10 │    18181  -0.00231971
  11 │    18183  -0.00227453
  12 │    18184   0.0021734
  13 │    18185   0.00218902
  14 │    18186   0.00222217
  15 │    18188   0.00195768
  16 │    18189   0.0020311
  17 │    33128  -0.0026306
  18 │    33129  -0.00266692
  19 │    33130  -0.00272976
  20 │    33132  -0.00258239
  21 │    41911   0.000474924
  22 │    41927  -0.000613065
  23 │    41945  -0.00654382
  24 │    41948  -0.000650576
  25 │    41950  -0.00132918
  26 │    41952  -0.00712631
  27 │    41953  -0.00270884
  28 │    41954  -0.00715749
  29 │    41955  -0.00711831
  30 │    41956  -0.00713322
  31 │    41959   0.00710629
  32 │    41963  -0.00722125
  33 │    41964   0.00550505
  34 │    41965   0.00523468
  35 │    41966  -0.00432116
  36 │    41967  -0.00721832
  37 │    41968   0.00459499
  38 │    41969  -0.00243618
  39 │    41972  -0.00323695
  40 │    41975   0.00331502
  41 │    41977   0.00343431
  42 │    41978   0.00346279
  43 │    41979   0.00347973
  44 │    41983  -0.00119536
  45 │    41985   0.00326449
  46 │    41988   0.00397013
  47 │    41989   0.00281377
  48 │    42899  -0.000738642
  49 │    42900   0.000531198
  50 │    42913  -0.00179995
  51 │    42916  -0.00264582
  52 │    42919  -0.00286691
  53 │    42921  -0.00255874
  54 │    42925  -0.00348486
  55 │    42927  -0.00282084
  56 │    42928  -0.0034811
  57 │    42930  -0.00243559
  58 │    42931  -0.00286693
  59 │    42932  -0.00290034
  60 │    42933  -0.00619666
  61 │    42934  -0.00585399
  62 │    42935  -0.00581142
  63 │    42936  -0.00269159
  64 │    42938  -0.00498974
  65 │    42941   0.00401159
  66 │    42942   0.00401418
  67 │    42943   0.00401023
  68 │    42944  -0.000777641
  69 │    42945   0.00407248
  70 │    42946  -0.000789362
  71 │    42947   0.00388906
  72 │    42956  -0.00117342
  73 │    42977   0.000506547
  74 │    61929  -0.00189991
  75 │    61930  -0.00210968
  76 │    61932  -0.00241658
  77 │    61934  -0.00105248
  78 │    61937  -0.00106511
  79 │    70930   0.00258283
  80 │    70931   0.00260404
  81 │    70933   0.00263655
  82 │    95584   0.000618236
  83 │    95588   0.000828817
  84 │    95611   0.000734026
  85 │    95625  -0.000421369
  86 │   144088   0.00103144
  87 │   144090   0.00183201
  88 │   144091   0.00183084
  89 │   146552   0.001626
  90 │   146557   0.00234637
  91 │   146560   0.00225692
  92 │   146561   0.00196476
  93 │   146564   0.00235163
  94 │   146566   0.00245292
  95 │   146576   0.00149064
  96 │   158405   0.00295509
  97 │   158406   0.00347374
  98 │   158407   0.00338988
  99 │   158411   0.00212758
 100 │   174951  -0.00101444
 101 │   175000   0.00414114
 102 │   175005   0.00383054
 103 │   188679   0.000531072
 104 │   188682   0.000667146
 105 │   188687   0.000676673
 106 │   188691   0.000600114
 107 │   190680  -0.000579869
 108 │   190681  -0.000742147
 109 │   190683  -0.000618485
 110 │   190685  -0.00070618
 111 │   194328  -0.00175526
 112 │   194351  -0.00106176
 113 │   194353  -0.00519844
 114 │   194377   0.00197879
 115 │   194387  -0.00149007
 116 │   194388  -0.00152123
 117 │   194389  -0.00132871
 118 │   194401   0.00143077
 119 │   194409  -0.00727407
 120 │   194415  -0.00748389
 121 │   194427  -0.00168426
 122 │   194439  -0.00163423
 123 │   194455  -0.00216047
 124 │   194489  -0.00114743
 125 │   208920   0.00127982
 126 │   208924  -0.0024131
 127 │   208925  -0.00300973
 128 │   208926  -0.00366172
 129 │   208927  -0.00300687
 130 │   208928  -0.00296571
 131 │   208934  -0.00367305
 132 │   208939  -0.0033536
 133 │   208941  -0.00338722
 134 │   208944  -0.00446331
 135 │   208947  -0.00444278
 136 │   208948  -0.00379996
 137 │   208949  -0.00453915
 138 │   208950  -0.00115068
 139 │   208951  -0.00400151
 140 │   208952  -0.00396228
 141 │   208954  -0.00349071
 142 │   208956  -0.00279502
 143 │   208958   0.00102952
 144 │   208966  -0.000899565
 145 │   227975   0.00201152
 146 │   227981   0.00207083
 147 │   227982  -0.00332536
 148 │   227983  -0.001705
 149 │   227987  -0.00405318
 150 │   227988  -0.00383619
 151 │   227989  -0.00541051
 152 │   227990  -0.00527539
 153 │   227991  -0.00669418
 154 │   227992  -0.00548806
 155 │   227993  -0.00674506
 156 │   227994  -0.00629195
 157 │   227995  -0.00575855
 158 │   227996  -0.00573287
 159 │   227997  -0.00267373
 160 │   227999  -0.00453235
 161 │   228000  -0.00664623
 162 │   228001  -0.0065948
 163 │   228002  -0.0064186
 164 │   228003  -0.0062666
 165 │   228004  -0.00642988
 166 │   228005  -0.00606578
 167 │   228006  -0.00532145
 168 │   228007  -0.00543858
 169 │   228008  -0.0064555
 170 │   228009  -0.00170108
 171 │   228011  -0.00284159
 172 │   228013  -0.00228643
 173 │   228014  -0.00641405
 174 │   228019  -0.00306283
 175 │   228020  -0.00246904
 176 │   228031  -0.0014886
 177 │   242590   0.000494167
 178 │   242593  -0.000920113
 179 │   242596   0.00153384
 180 │   242599   0.00337244
 181 │   242601  -0.00590906
 182 │   242602  -0.00594381
 183 │   242603  -0.00591943
 184 │   242605  -0.00483758
 185 │   242606  -0.00460773
 186 │   242607  -0.00607445
 187 │   242609  -0.00474528
 188 │   242612  -0.00531291
 189 │   242614   0.00173077
 190 │   301468   0.00521011
 191 │   301469   0.0034331
 192 │   301470   0.00341181
 193 │   301471   0.00522678
 194 │   301473   0.00511983
 195 │   309990  -0.0019027
 196 │   309993  -0.0057713
 197 │   309995  -0.00204013
 198 │   309996  -0.00739134
 199 │   309998   0.00594792
 200 │   309999  -0.00161084
 201 │   310000   0.00637451
 202 │   310003   0.00638443
 203 │   310006   0.00646758
 204 │   310010  -0.0102924
 205 │   310012   0.00635551
 206 │   310013   0.00611632
 207 │   310014  -0.00728417
 208 │   310015  -0.00754478
 209 │   310016  -0.00254273
 210 │   310017   0.00658333
 211 │   310018  -0.00762462
 212 │   310019   0.00658419
 213 │   310020  -0.00740901
 214 │   310023  -0.00105431
 215 │   310024   0.00256146
 216 │   310027  -0.00384985
 217 │   310030  -0.00237493
 218 │   310033  -0.00546918
 219 │   310037  -0.00418743
 220 │   310041  -0.00317626
 221 │   310042  -0.00344575
 222 │   310043  -0.000914822
 223 │   310044  -0.00339466
 224 │   310057  -0.00298783
 225 │   310059  -0.00276508
 226 │   310060  -0.00155921
 227 │   310069  -0.00221034
 228 │   310070  -0.00224865
 229 │   310072  -0.00227947
 230 │   310082   0.00224342
 231 │   310103   0.00196395
 232 │   371857   0.000743284
 233 │   391779  -0.00395577
 234 │   391780  -0.00380444
 235 │   391781  -0.00383187
 236 │   391782  -0.00392903
 237 │   391783  -0.00387729
 238 │   391785   0.00283118
 239 │   391787  -0.00378386
 240 │   391789  -0.00419888
 241 │   391791  -0.00449811
 242 │   391792   0.00327621
 243 │   391793  -0.00299444
 244 │   391794  -0.00456896
 245 │   391795   0.00297019
 246 │   394184   0.00199853
 247 │   407592   0.00188025
 248 │   407600   0.00187681
 249 │   432754  -0.00323392
 250 │   432757  -0.00269651
 251 │   432759  -0.00330967
 252 │   434501  -0.000565672
 253 │   434519  -0.00184899
 254 │   434532  -0.00380185
 255 │   434545  -0.00423018
 256 │   434550   0.00180676
 257 │   434553  -0.00206138
 258 │   434560  -0.00316579
 259 │   434561  -0.00317631
 260 │   434564  -0.00250592
 261 │   434570  -0.00185052
 262 │   434573  -0.00415337
 263 │   434574  -0.00418104
 264 │   434594  -0.00342059
 265 │   438519   0.00585202
 266 │   438520   0.00226143
 267 │   438521   0.00253739
 268 │   438526   0.00314732
 269 │   438529   0.00506335
 270 │   438531   0.00465584

Trait 2: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1   8.13693e-6
   2 │        2  -0.0211594
   3 │        3   0.00756145
   4 │        4   0.00690415
   5 │        5   0.00110957
   6 │        6  -0.00174214
   7 │        7   0.000776239
   8 │        8  -0.00162054
   9 │        9  -0.000428541
  10 │       10   0.000742035
  11 │       11  -0.000516303
  12 │       12   0.000412001
  13 │       13   0.00210243
  14 │       14  -0.00424999

Trait 3: IHT estimated 288 nonzero SNP predictors
288×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    10145  -0.00145107
   2 │    10160   0.00126437
   3 │    10164  -0.00102616
   4 │    10171   0.00112549
   5 │    18147  -0.00227747
   6 │    18165  -0.00324197
   7 │    18170  -0.00199215
   8 │    18171   0.00278647
   9 │    18172   0.000843137
  10 │    18174  -0.00188452
  11 │    18178   0.00277176
  12 │    18181  -0.00734344
  13 │    18182   0.00582349
  14 │    18183  -0.00745143
  15 │    18184   0.00729762
  16 │    18185   0.00741666
  17 │    18186   0.00743777
  18 │    18187  -0.00460279
  19 │    18188   0.00713357
  20 │    18189   0.0071974
  21 │    18191   0.00264992
  22 │    18197  -0.00293648
  23 │    18198  -0.00176679
  24 │    18212  -0.00172758
  25 │    18218  -0.00172719
  26 │    41946   0.000947861
  27 │    41950  -0.00130829
  28 │    41952  -0.0015686
  29 │    41954  -0.00157314
  30 │    41955  -0.00152913
  31 │    41956  -0.00162992
  32 │    41961  -0.000848585
  33 │    41964   0.00617994
  34 │    41965   0.00605016
  35 │    41966  -0.00322803
  36 │    41968   0.00491961
  37 │    41971  -0.0026722
  38 │    41972  -0.00338615
  39 │    41974   0.00216678
  40 │    41975   0.00513827
  41 │    41977   0.00551869
  42 │    41978   0.00558676
  43 │    41979   0.00553338
  44 │    41985   0.00458275
  45 │    41986   0.00522408
  46 │    41988   0.00421374
  47 │    41989   0.00391099
  48 │    41990   0.0040824
  49 │    41992  -0.00519191
  50 │    41997  -0.00399794
  51 │    42933  -0.00472919
  52 │    42934  -0.00431372
  53 │    42935  -0.00424755
  54 │    42936   0.000985524
  55 │    42938  -0.00158406
  56 │    42941   0.00101666
  57 │    42942   0.00101342
  58 │    42943   0.000918249
  59 │    42945   0.00102875
  60 │    42947   0.000945366
  61 │    45816  -0.0027297
  62 │    45817  -0.00280096
  63 │    45821  -0.00270831
  64 │    45822  -0.00349635
  65 │    45823  -0.00345652
  66 │   146505  -0.000251567
  67 │   146507   0.000305642
  68 │   146510  -0.000420851
  69 │   146511  -0.000176294
  70 │   146512  -0.000424967
  71 │   146513  -0.000331451
  72 │   146518   0.00034567
  73 │   146519   0.000342868
  74 │   146520  -0.000263651
  75 │   146522  -0.000361745
  76 │   146525   0.00237411
  77 │   146527   0.00204345
  78 │   146528   0.000635614
  79 │   146529   0.00262004
  80 │   146530   0.000974882
  81 │   146532   0.00201647
  82 │   146533  -0.000193766
  83 │   146536  -0.000176355
  84 │   146537   0.00238694
  85 │   146538   0.0022678
  86 │   146539   0.00049029
  87 │   146540   0.000638824
  88 │   146544   0.000488781
  89 │   146545   0.000793566
  90 │   146546   0.00238099
  91 │   146549   0.00332153
  92 │   146550  -0.000202003
  93 │   146552   0.00322358
  94 │   146553   0.000568622
  95 │   146554   0.00343677
  96 │   146557   0.00371526
  97 │   146558  -0.000186911
  98 │   146560   0.00369282
  99 │   146561   0.00396743
 100 │   146564   0.00370389
 101 │   146566   0.0038079
 102 │   146569   0.00271369
 103 │   146570  -0.000407014
 104 │   146572  -0.000316253
 105 │   146576   0.00362053
 106 │   146577   0.000725954
 107 │   146579   0.00278065
 108 │   146580  -0.000853671
 109 │   146581  -0.000389374
 110 │   146582   0.000365821
 111 │   146583  -0.000389077
 112 │   146585  -0.000354
 113 │   146586   0.000178124
 114 │   146587  -0.000353807
 115 │   146588  -0.00149677
 116 │   146589  -0.0004087
 117 │   146590  -0.000949263
 118 │   146591  -0.000297667
 119 │   146592  -0.000489458
 120 │   146593  -0.000252834
 121 │   146595  -0.000397825
 122 │   146596   0.00219583
 123 │   146597   0.000175387
 124 │   146598   0.00148987
 125 │   146602  -0.000338591
 126 │   146603  -0.000424758
 127 │   146605   0.000697495
 128 │   146606  -0.000243742
 129 │   146607   0.000409292
 130 │   146611  -0.000204026
 131 │   146612   0.000227153
 132 │   146615  -0.000254861
 133 │   146616   0.000319643
 134 │   146617   0.000325079
 135 │   146619  -0.000182823
 136 │   146620   0.000287117
 137 │   146628   0.000397071
 138 │   146630  -0.000274433
 139 │   146631   0.000252346
 140 │   146636  -0.000192499
 141 │   158405   0.00204073
 142 │   158406   0.00230311
 143 │   158407   0.0021546
 144 │   174915   0.00230581
 145 │   174926   0.00212189
 146 │   174927   0.000481124
 147 │   174933   0.000683824
 148 │   174936   0.000590623
 149 │   174985   0.0019002
 150 │   174986   0.000432006
 151 │   174988   0.00190042
 152 │   175000   0.00166293
 153 │   175005   0.00180763
 154 │   175032   0.00207618
 155 │   175040   0.00210964
 156 │   175041   0.0021606
 157 │   175075   0.0022099
 158 │   175096   0.00161748
 159 │   225488   0.00099214
 160 │   225489   0.000931573
 161 │   225490   0.00168895
 162 │   225491   0.00149892
 163 │   242599   0.00114577
 164 │   242601  -0.00436239
 165 │   242602  -0.00325071
 166 │   242603  -0.00423572
 167 │   242607  -0.00334696
 168 │   266000   0.000993985
 169 │   266003   0.000806865
 170 │   266004   0.000947149
 171 │   266006   0.000967066
 172 │   266007   0.00277616
 173 │   266008   0.00250758
 174 │   266009   0.00254379
 175 │   266010   0.0025239
 176 │   266011   0.00279772
 177 │   266021   0.00101093
 178 │   266031   0.00117901
 179 │   301456  -0.000854504
 180 │   301459  -0.00137954
 181 │   301462  -0.00138089
 182 │   301463  -0.00147819
 183 │   301464  -0.00101253
 184 │   301466  -0.00149513
 185 │   301467  -0.00146113
 186 │   301468  -0.00146361
 187 │   301469  -0.00133321
 188 │   301470  -0.0014001
 189 │   301471  -0.00147124
 190 │   301472  -0.000717686
 191 │   301473  -0.00155699
 192 │   301475  -0.000849954
 193 │   301476  -0.00155294
 194 │   301480  -0.0013346
 195 │   310010  -0.00699442
 196 │   312049   0.00170592
 197 │   312051   0.00195889
 198 │   312052   0.00193089
 199 │   312055   0.00187206
 200 │   391781  -0.00157728
 201 │   391788  -0.00101437
 202 │   391791  -0.00172345
 203 │   394184   0.00251714
 204 │   401797  -0.00212142
 205 │   408087  -0.00206227
 206 │   408092   0.00119082
 207 │   411582   0.00165091
 208 │   432723  -0.00150546
 209 │   432731  -0.00208397
 210 │   432735  -0.00281349
 211 │   432745  -0.00183583
 212 │   432746  -0.00187966
 213 │   432747  -0.00192356
 214 │   432754  -0.00719444
 215 │   432757  -0.00540191
 216 │   432759  -0.00723408
 217 │   432760  -0.00235572
 218 │   432761  -0.00157542
 219 │   434519  -0.0024708
 220 │   434532  -0.00410449
 221 │   434545  -0.00431249
 222 │   434553  -0.00272666
 223 │   434560  -0.00346682
 224 │   434561  -0.00342927
 225 │   434573  -0.00373287
 226 │   434574  -0.00378173
 227 │   434594  -0.0030785
 228 │   438286  -0.00303059
 229 │   438303  -0.00190562
 230 │   438325  -0.00308266
 231 │   438334  -0.00163562
 232 │   438339  -0.0021651
 233 │   438345  -0.00399709
 234 │   438363  -0.00214093
 235 │   438366  -0.00198315
 236 │   438383  -0.00165019
 237 │   438384  -0.000411987
 238 │   438391  -0.00210357
 239 │   438435  -0.00351909
 240 │   438439  -0.00283132
 241 │   438441  -0.00232569
 242 │   438442  -0.00335924
 243 │   438445  -0.0028089
 244 │   438448  -0.00547019
 245 │   438450  -0.00264292
 246 │   438455  -0.00611225
 247 │   438466  -0.00617728
 248 │   438467  -0.0036387
 249 │   438469  -0.0110122
 250 │   438470   0.0027803
 251 │   438476  -0.00475391
 252 │   438478  -0.00297646
 253 │   438479  -0.00806776
 254 │   438481  -0.00161139
 255 │   438483  -0.00557873
 256 │   438489  -0.00681063
 257 │   438492  -0.0070584
 258 │   438494  -0.007228
 259 │   438499   0.005653
 260 │   438500   0.00614355
 261 │   438505   0.00562759
 262 │   438507   0.0037114
 263 │   438509   0.0034653
 264 │   438511  -0.00634142
 265 │   438513   0.00289957
 266 │   438514   0.00295125
 267 │   438515  -0.00609199
 268 │   438516  -0.00303117
 269 │   438518  -0.0122749
 270 │   438519   0.00688261
 271 │   438520   0.00828706
 272 │   438521   0.00365792
 273 │   438525  -0.00685895
 274 │   438526   0.00918554
 275 │   438527   0.00369569
 276 │   438530  -0.0168539
 277 │   438531   0.0102765
 278 │   438533  -0.00640318
 279 │   438534  -0.00956261
 280 │   438536  -0.00283263
 281 │   438557  -0.0022888
 282 │   438562  -0.00224976
 283 │   438575  -0.00235278
 284 │   449460   0.000833477
 285 │   449595   0.0022457
 286 │   450535   0.00109128
 287 │   450537  -0.00145969
 288 │   450540   0.00209238

Trait 3: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -1.3302e-5
   2 │        2   0.00967396
   3 │        3   0.00138631
   4 │        4   0.000532398
   5 │        5   0.000674373
   6 │        6  -0.00117821
   7 │        7   0.00115626
   8 │        8  -0.00196533
   9 │        9  -0.00175936
  10 │       10   0.000678193
  11 │       11   0.000271374
  12 │       12  -0.000193647
  13 │       13   0.000735877
  14 │       14   0.000440069

Trait 4: IHT estimated 226 nonzero SNP predictors
226×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.00278283
   2 │    11578  -0.00287823
   3 │    11579   0.0028758
   4 │    11580   0.0027812
   5 │    11581  -0.00274846
   6 │    11590   0.00262752
   7 │    31767   0.00219404
   8 │    31770   0.00190333
   9 │    33121   0.00138692
  10 │    33122   0.00132967
  11 │    33128   0.00309333
  12 │    33129   0.00310362
  13 │    33130   0.00309012
  14 │    33132   0.00306532
  15 │    33136  -0.00161528
  16 │    41945   0.0032455
  17 │    41952   0.003127
  18 │    41954   0.00306089
  19 │    41955   0.00310323
  20 │    41956   0.00310329
  21 │    41959  -0.00390312
  22 │    41963   0.00396893
  23 │    41967   0.00390698
  24 │    70930  -0.000595824
  25 │    70931  -0.00068774
  26 │    70932  -0.000595076
  27 │    70933  -0.000649397
  28 │    70935  -0.000630615
  29 │   121556  -0.000888647
  30 │   121597  -0.00215125
  31 │   121617  -0.000920716
  32 │   208925   0.00119956
  33 │   208926   0.00156525
  34 │   208927   0.00116643
  35 │   208928   0.00123824
  36 │   208934   0.00155493
  37 │   208939   0.00103927
  38 │   208941   0.00103441
  39 │   208948   0.000826343
  40 │   208951   0.000739962
  41 │   208952   0.000824162
  42 │   208954   0.00113897
  43 │   225486   0.00285934
  44 │   225487   0.00297573
  45 │   225488   0.00368916
  46 │   225489   0.00357933
  47 │   225490   0.00316086
  48 │   225491   0.00328261
  49 │   225497  -0.0025828
  50 │   225506  -0.00179218
  51 │   227975  -0.00218923
  52 │   227981  -0.00257804
  53 │   227982   0.00108859
  54 │   227983   0.0023457
  55 │   227987   0.00424013
  56 │   227988   0.00416893
  57 │   227989   0.0052223
  58 │   227990   0.00510888
  59 │   227991   0.00551937
  60 │   227992   0.00546222
  61 │   227993   0.00548442
  62 │   227994   0.00543155
  63 │   227995   0.00561991
  64 │   227996   0.00577213
  65 │   227997   0.00313241
  66 │   227999   0.00426403
  67 │   228000   0.00566764
  68 │   228001   0.0055505
  69 │   228002   0.00541151
  70 │   228003   0.00571511
  71 │   228004   0.00545169
  72 │   228005   0.00546857
  73 │   228006   0.00546756
  74 │   228007   0.00544095
  75 │   228008   0.00523164
  76 │   228009   0.00120665
  77 │   228011   0.00293273
  78 │   228013   0.00276744
  79 │   228014   0.00555009
  80 │   228019   0.00294751
  81 │   228020   0.00306839
  82 │   240938   0.00145598
  83 │   240940   0.00168172
  84 │   240944   0.00151526
  85 │   240947   0.00147412
  86 │   240950   0.00124504
  87 │   250491   0.000802681
  88 │   260609   0.000631603
  89 │   260644  -0.00165691
  90 │   260645  -0.0013984
  91 │   286075  -0.00207122
  92 │   286080  -0.00209057
  93 │   286084  -0.00206814
  94 │   300066   0.000999134
  95 │   300068   0.00192851
  96 │   300076   0.000855309
  97 │   300084   0.00140229
  98 │   300091  -0.00133621
  99 │   300109  -0.0015229
 100 │   300112  -0.00160194
 101 │   300116  -0.00164927
 102 │   300124  -0.00149989
 103 │   300128  -0.00138723
 104 │   301456  -0.000425126
 105 │   301459  -0.00096663
 106 │   301462  -0.000971363
 107 │   301463  -0.00109852
 108 │   301464  -0.00102749
 109 │   301466  -0.000920746
 110 │   301467  -0.00109285
 111 │   301468  -0.00105324
 112 │   301469  -0.00171309
 113 │   301470  -0.00175047
 114 │   301471  -0.00105254
 115 │   301473  -0.00112642
 116 │   301476  -0.000997505
 117 │   301479  -0.000766033
 118 │   301480  -0.000847124
 119 │   303688  -0.00105975
 120 │   303690  -0.0011214
 121 │   303691  -0.0016729
 122 │   303694  -0.00128165
 123 │   303697  -0.00131466
 124 │   310035   0.0026855
 125 │   310039   0.00525498
 126 │   310047   0.00264672
 127 │   310056   0.00363115
 128 │   310062   0.00350276
 129 │   310064   0.00344013
 130 │   334237  -0.00140126
 131 │   334238  -0.0019781
 132 │   334259   0.0025121
 133 │   334263   0.000609481
 134 │   373938   0.00041478
 135 │   373948   0.00841933
 136 │   373950   0.00870749
 137 │   373951   0.00829166
 138 │   373952  -0.00889478
 139 │   373954  -0.00873927
 140 │   373955   0.00315522
 141 │   373956   0.00656767
 142 │   373962  -0.00586633
 143 │   373966   0.0042161
 144 │   373969  -0.00454891
 145 │   373973  -0.00421032
 146 │   373974  -0.000419704
 147 │   373976   0.00917177
 148 │   373978   0.00491206
 149 │   373979  -0.00886219
 150 │   373981  -0.000747733
 151 │   373987  -0.00671503
 152 │   373988  -0.00378211
 153 │   373991  -0.000596561
 154 │   373995   0.000645158
 155 │   374006   0.000613672
 156 │   391744  -0.00202962
 157 │   391746   0.00193933
 158 │   391750   0.000590971
 159 │   391754   0.00222308
 160 │   391757   0.00236534
 161 │   391760   0.00311523
 162 │   391762   0.00203805
 163 │   391767   0.000812497
 164 │   391768   0.0017481
 165 │   391777  -0.00227092
 166 │   391779   0.00817906
 167 │   391780   0.00804922
 168 │   391781   0.0126828
 169 │   391782   0.0130533
 170 │   391783   0.0130719
 171 │   391784  -0.00347964
 172 │   391785  -0.00798832
 173 │   391787   0.0131827
 174 │   391788   0.00606929
 175 │   391789   0.0119041
 176 │   391791   0.0111069
 177 │   391792  -0.0114711
 178 │   391793   0.011606
 179 │   391794   0.0110644
 180 │   391795  -0.0116922
 181 │   391796   0.00477883
 182 │   391798   0.00393462
 183 │   391799  -0.00603912
 184 │   391800  -0.00511555
 185 │   391801  -0.0052314
 186 │   391804  -0.00294541
 187 │   407582  -0.00220004
 188 │   407592  -0.00321686
 189 │   407600  -0.00339108
 190 │   423234   0.00263239
 191 │   423236   0.00190242
 192 │   423237   0.00227016
 193 │   423242   0.00248427
 194 │   423244   0.00495751
 195 │   423245   0.00489804
 196 │   423246   0.00415546
 197 │   423247   0.00510784
 198 │   423250   0.0049764
 199 │   423255   0.00281688
 200 │   423259   0.00161393
 201 │   423260   0.00246427
 202 │   423266   0.00102453
 203 │   423268   0.00105723
 204 │   423293   0.00109114
 205 │   423294   0.00142402
 206 │   432795  -0.00272011
 207 │   432796  -0.0014592
 208 │   432797  -0.00187044
 209 │   432801  -0.00264355
 210 │   438526  -0.00390099
 211 │   438531  -0.0031415
 212 │   438535   0.00309645
 213 │   438536   0.00277097
 214 │   438542   0.00278098
 215 │   450252  -0.00315379
 216 │   450500  -0.00112831
 217 │   450515   0.000884158
 218 │   450516   0.000577619
 219 │   450517   0.00058129
 220 │   450521   0.00158675
 221 │   450523   0.0015969
 222 │   450535  -0.00511613
 223 │   450537   0.00555122
 224 │   450538  -0.00460131
 225 │   450539  -0.00277392
 226 │   450540  -0.00495886

Trait 4: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -1.76586e-7
   2 │        2   0.0472524
   3 │        3   0.00597123
   4 │        4   0.00545353
   5 │        5   0.00456532
   6 │        6  -0.000849169
   7 │        7   0.00110126
   8 │        8  -0.000527446
   9 │        9  -0.000424545
  10 │       10   0.000566604
  11 │       11   0.000334761
  12 │       12  -2.04952e-5
  13 │       13   0.000525995
  14 │       14   0.000393243

Trait 5: IHT estimated 261 nonzero SNP predictors
261×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼───────────────────────
   1 │    11577  -0.00527567
   2 │    11578  -0.00531382
   3 │    11579   0.00537022
   4 │    11580   0.00531884
   5 │    11581  -0.00522323
   6 │    11584  -0.00323971
   7 │    11590   0.00504338
   8 │    11592  -0.00373084
   9 │    11598  -0.0026579
  10 │    33128  -0.00283267
  11 │    33129  -0.00285383
  12 │    33130  -0.00288249
  13 │    33132  -0.00279971
  14 │    41945  -0.00475945
  15 │    41952  -0.00515093
  16 │    41953  -0.00286328
  17 │    41954  -0.00514663
  18 │    41955  -0.00515586
  19 │    41956  -0.00514454
  20 │    41959   0.00571221
  21 │    41963  -0.00574099
  22 │    41967  -0.00576964
  23 │    41969  -0.00316697
  24 │    41983  -0.00305675
  25 │    42913  -0.00255394
  26 │    42916  -0.00281326
  27 │    42919  -0.00311834
  28 │    42921  -0.00236624
  29 │    42925  -0.00374336
  30 │    42927  -0.00310587
  31 │    42928  -0.00372634
  32 │    42930  -0.00253267
  33 │    42931  -0.00305374
  34 │    42932  -0.00298719
  35 │    42933  -0.00568278
  36 │    42934  -0.00541672
  37 │    42935  -0.00544651
  38 │    42938  -0.00453374
  39 │    42941   0.00368623
  40 │    42942   0.0036811
  41 │    42943   0.00369541
  42 │    42945   0.00371947
  43 │    42947   0.00361362
  44 │    61929  -0.00304508
  45 │    61930  -0.00353765
  46 │    61932  -0.00378401
  47 │    61934  -0.00296951
  48 │    61937  -0.00298234
  49 │    70920  -0.00249993
  50 │    70928   0.00255908
  51 │    70930   0.00246595
  52 │    70931   0.00248065
  53 │    70932   0.00243007
  54 │    70933   0.00243104
  55 │    70935   0.00248872
  56 │    70938   0.00235922
  57 │    70941   0.00222131
  58 │    95588   0.0023786
  59 │   144088   0.00257986
  60 │   144090   0.00312573
  61 │   144091   0.0031652
  62 │   158406   0.00242488
  63 │   158407   0.00243751
  64 │   174902   0.00201046
  65 │   174909   0.00202836
  66 │   174916   0.0019
  67 │   174920   0.00193516
  68 │   174973   0.00196673
  69 │   174992   0.00202397
  70 │   175039   0.00195244
  71 │   194314  -0.00248012
  72 │   194328  -0.0024679
  73 │   194351  -0.00306232
  74 │   194353  -0.00736557
  75 │   194363  -0.00186431
  76 │   194364   0.00263211
  77 │   194365  -0.00191347
  78 │   194371  -0.00247199
  79 │   194373  -0.00254154
  80 │   194377   0.00391663
  81 │   194378   0.00314845
  82 │   194384  -0.00219785
  83 │   194385  -0.00247116
  84 │   194387  -0.00481448
  85 │   194388  -0.00487326
  86 │   194389  -0.00482433
  87 │   194390   0.00264228
  88 │   194394   0.00232718
  89 │   194397   0.00218444
  90 │   194398  -0.00320977
  91 │   194401   0.00368992
  92 │   194408   0.00272867
  93 │   194409  -0.0107038
  94 │   194410   0.00330812
  95 │   194411   0.00276934
  96 │   194413   0.00262475
  97 │   194414   0.0025906
  98 │   194415  -0.0110343
  99 │   194419  -0.00337529
 100 │   194420   0.00368371
 101 │   194423   0.0033186
 102 │   194425  -0.00325394
 103 │   194427  -0.00461267
 104 │   194428  -0.00281929
 105 │   194432   0.00300017
 106 │   194433   0.00235114
 107 │   194435   0.00234034
 108 │   194437   0.00228792
 109 │   194439  -0.00421929
 110 │   194455  -0.00484527
 111 │   194472  -0.00228756
 112 │   194489  -0.00410966
 113 │   208920   0.00274784
 114 │   208924  -0.00406912
 115 │   208925  -0.00494559
 116 │   208926  -0.00488821
 117 │   208927  -0.00495531
 118 │   208928  -0.00500448
 119 │   208934  -0.00485203
 120 │   208939  -0.00499989
 121 │   208941  -0.00505558
 122 │   208944  -0.00436767
 123 │   208947  -0.00492007
 124 │   208948  -0.0051485
 125 │   208949  -0.00490278
 126 │   208951  -0.00529271
 127 │   208952  -0.00504111
 128 │   208954  -0.00499508
 129 │   208956  -0.00379957
 130 │   208958   0.00239089
 131 │   208966  -0.002449
 132 │   225860   0.00214146
 133 │   225918   0.00207198
 134 │   225927  -0.00205251
 135 │   225929  -0.00209799
 136 │   226040   0.00211878
 137 │   227975   0.00323507
 138 │   227981   0.00270627
 139 │   227982  -0.004154
 140 │   227983  -0.00251204
 141 │   227987  -0.00478669
 142 │   227988  -0.00465863
 143 │   227989  -0.00606576
 144 │   227990  -0.00593429
 145 │   227991  -0.0075659
 146 │   227992  -0.00598028
 147 │   227993  -0.00757186
 148 │   227994  -0.00718559
 149 │   227995  -0.00628942
 150 │   227996  -0.00633583
 151 │   227997  -0.00372584
 152 │   227999  -0.00512624
 153 │   228000  -0.00712913
 154 │   228001  -0.00752986
 155 │   228002  -0.00743669
 156 │   228003  -0.00705013
 157 │   228004  -0.00744414
 158 │   228005  -0.0068487
 159 │   228006  -0.00625169
 160 │   228007  -0.00624566
 161 │   228008  -0.00733725
 162 │   228009  -0.00246404
 163 │   228011  -0.00353848
 164 │   228013  -0.0029902
 165 │   228014  -0.00729998
 166 │   228019  -0.00297567
 167 │   228020  -0.00283069
 168 │   228031  -0.00268888
 169 │   242601  -0.0043993
 170 │   242602  -0.00466986
 171 │   242603  -0.00448417
 172 │   242605  -0.00414743
 173 │   242606  -0.00405469
 174 │   242607  -0.00467853
 175 │   242609  -0.00414105
 176 │   242612  -0.00437566
 177 │   278270  -0.00147684
 178 │   278282  -0.00145132
 179 │   278287  -0.00146602
 180 │   278292  -0.00142312
 181 │   278296  -0.00144748
 182 │   278299  -0.00143541
 183 │   278303  -0.00144121
 184 │   278313  -0.00145416
 185 │   278316  -0.00130695
 186 │   278317  -0.00131945
 187 │   278318  -0.00127892
 188 │   301456   0.00333291
 189 │   301457   0.00214196
 190 │   301459   0.0039051
 191 │   301462   0.00399366
 192 │   301463   0.00404697
 193 │   301464   0.003729
 194 │   301466   0.00404947
 195 │   301467   0.00413514
 196 │   301468   0.0041774
 197 │   301469   0.00420628
 198 │   301470   0.00418776
 199 │   301471   0.00416427
 200 │   301472   0.00283509
 201 │   301473   0.00414616
 202 │   301474   0.00212521
 203 │   301475   0.00333077
 204 │   301476   0.00411919
 205 │   301479   0.00253834
 206 │   301480   0.00378673
 207 │   301481   0.00176553
 208 │   301482   0.00166179
 209 │   301489  -0.00177657
 210 │   309990  -0.00282315
 211 │   309993  -0.00529567
 212 │   309995  -0.00285742
 213 │   309996  -0.0069928
 214 │   309998   0.00569364
 215 │   309999  -0.00246046
 216 │   310000   0.00603881
 217 │   310003   0.00601133
 218 │   310006   0.00611132
 219 │   310010  -0.00979271
 220 │   310012   0.00616073
 221 │   310013   0.0060113
 222 │   310014  -0.00670983
 223 │   310015  -0.00722417
 224 │   310017   0.00624427
 225 │   310018  -0.00723131
 226 │   310019   0.00626549
 227 │   310020  -0.00698454
 228 │   310024   0.00365061
 229 │   310027  -0.0035588
 230 │   310030  -0.00395057
 231 │   310033  -0.00539036
 232 │   310037  -0.00370647
 233 │   310041  -0.00363159
 234 │   310057  -0.00467062
 235 │   310059  -0.00429456
 236 │   310060  -0.0035469
 237 │   310069  -0.00392077
 238 │   310070  -0.00395507
 239 │   310072  -0.00393289
 240 │   310082   0.00384311
 241 │   310103   0.00343827
 242 │   348293   0.00236178
 243 │   371857   0.00298075
 244 │   373976  -0.00426263
 245 │   373979   0.00400945
 246 │   407592   0.00239284
 247 │   407600   0.00254664
 248 │   411013  -0.00314214
 249 │   411030  -0.0028747
 250 │   434532  -0.00275341
 251 │   434545  -0.00338096
 252 │   434573  -0.00319946
 253 │   434574  -0.00318919
 254 │   438469   0.00345333
 255 │   438517   0.00268389
 256 │   438518   0.00521406
 257 │   438521   0.00283445
 258 │   438525   0.0040498
 259 │   438529   0.00570676
 260 │   438530   0.00742618
 261 │   438533   0.00445141

Trait 5: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -1.20168e-5
   2 │        2  -0.0262513
   3 │        3   0.00632276
   4 │        4   0.00614365
   5 │        5   0.000419509
   6 │        6  -0.000325161
   7 │        7   0.000208495
   8 │        8   0.000717146
   9 │        9   0.000890117
  10 │       10  -5.80286e-5
  11 │       11   4.65475e-5
  12 │       12   0.000474678
  13 │       13   0.00172473
  14 │       14  -0.00242828

Trait 6: IHT estimated 265 nonzero SNP predictors
265×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.00489992
   2 │    11578  -0.00495562
   3 │    11579   0.00495713
   4 │    11580   0.00496572
   5 │    11581  -0.00487641
   6 │    11584  -0.00298812
   7 │    11590   0.00474782
   8 │    11592  -0.00353086
   9 │    11598  -0.00275781
  10 │    33128  -0.0035755
  11 │    33129  -0.00360473
  12 │    33130  -0.00359964
  13 │    33132  -0.00346979
  14 │    33136   0.00241612
  15 │    41945  -0.00536264
  16 │    41952  -0.00574156
  17 │    41953  -0.00378575
  18 │    41954  -0.00574245
  19 │    41955  -0.00573328
  20 │    41956  -0.00572409
  21 │    41959   0.00582833
  22 │    41963  -0.00593163
  23 │    41964   0.00441189
  24 │    41965   0.00439069
  25 │    41966  -0.00321327
  26 │    41967  -0.00589922
  27 │    41968   0.00341189
  28 │    41969  -0.00248846
  29 │    41972  -0.00296531
  30 │    41975   0.00368512
  31 │    41983  -0.0029554
  32 │    42900   0.00328891
  33 │    42913  -0.00330481
  34 │    42916  -0.0032977
  35 │    42919  -0.00355175
  36 │    42921  -0.00297805
  37 │    42925  -0.00447379
  38 │    42927  -0.00357786
  39 │    42928  -0.0044511
  40 │    42930  -0.00300997
  41 │    42931  -0.00356794
  42 │    42932  -0.00346712
  43 │    42933  -0.00673749
  44 │    42934  -0.00652426
  45 │    42935  -0.00655165
  46 │    42936  -0.00269489
  47 │    42938  -0.00533606
  48 │    42941   0.00438556
  49 │    42942   0.00440715
  50 │    42943   0.00443562
  51 │    42945   0.00451676
  52 │    42947   0.00438117
  53 │    42956  -0.00273231
  54 │    42977   0.00296512
  55 │    61929  -0.00298395
  56 │    61930  -0.00363561
  57 │    61932  -0.00384619
  58 │    61934  -0.00331837
  59 │    61937  -0.003348
  60 │    61945  -0.00230595
  61 │    70920  -0.00183151
  62 │    70928   0.00164461
  63 │    70930   0.00196969
  64 │    70931   0.00195292
  65 │    70932   0.00189923
  66 │    70933   0.00192657
  67 │    70935   0.00186063
  68 │    70938   0.0017296
  69 │    70941   0.00154886
  70 │    95588   0.0026329
  71 │   144088   0.00286398
  72 │   144090   0.00361972
  73 │   144091   0.00363253
  74 │   158406   0.00277043
  75 │   158407   0.00275281
  76 │   174909   0.00334732
  77 │   188679   0.00188413
  78 │   188681   0.0018896
  79 │   188682   0.00187399
  80 │   188687   0.00182599
  81 │   188691   0.00181715
  82 │   190680  -0.00188784
  83 │   190681  -0.00211556
  84 │   190683  -0.00191297
  85 │   190685  -0.00187459
  86 │   190686  -0.00190302
  87 │   194328  -0.00246371
  88 │   194351  -0.00290182
  89 │   194353  -0.00582363
  90 │   194377   0.00364788
  91 │   194387  -0.00424526
  92 │   194388  -0.00426185
  93 │   194389  -0.00417691
  94 │   194401   0.00346519
  95 │   194409  -0.00832013
  96 │   194410   0.0027315
  97 │   194415  -0.00859719
  98 │   194419  -0.00308477
  99 │   194420   0.00152632
 100 │   194423   0.00111447
 101 │   194425  -0.00109417
 102 │   194427  -0.00324447
 103 │   194432   0.00321032
 104 │   194439  -0.00330769
 105 │   194455  -0.00393327
 106 │   194489  -0.00323159
 107 │   208920   0.00328307
 108 │   208924  -0.00441988
 109 │   208925  -0.00510667
 110 │   208926  -0.00469255
 111 │   208927  -0.00515162
 112 │   208928  -0.0051976
 113 │   208934  -0.00469003
 114 │   208939  -0.00516788
 115 │   208941  -0.00516116
 116 │   208944  -0.00389434
 117 │   208947  -0.00469482
 118 │   208948  -0.00524403
 119 │   208949  -0.00462032
 120 │   208950  -0.00275241
 121 │   208951  -0.00533472
 122 │   208952  -0.00490104
 123 │   208954  -0.00542371
 124 │   208956  -0.00371989
 125 │   208958   0.00288549
 126 │   208966  -0.00255543
 127 │   225918   0.00210037
 128 │   225927  -0.00181883
 129 │   225929  -0.00199031
 130 │   227975   0.00344544
 131 │   227981   0.00333492
 132 │   227982  -0.00463697
 133 │   227983  -0.00295262
 134 │   227987  -0.00560858
 135 │   227988  -0.00530709
 136 │   227989  -0.00686176
 137 │   227990  -0.00678759
 138 │   227991  -0.00850192
 139 │   227992  -0.00714123
 140 │   227993  -0.0084733
 141 │   227994  -0.00822008
 142 │   227995  -0.00739191
 143 │   227996  -0.00745255
 144 │   227997  -0.00419951
 145 │   227999  -0.00594616
 146 │   228000  -0.00840919
 147 │   228001  -0.00847244
 148 │   228002  -0.00831212
 149 │   228003  -0.00819446
 150 │   228004  -0.00832138
 151 │   228005  -0.00792602
 152 │   228006  -0.00703563
 153 │   228007  -0.00705561
 154 │   228008  -0.00826091
 155 │   228009  -0.00278142
 156 │   228011  -0.00416241
 157 │   228013  -0.00351945
 158 │   228014  -0.00836584
 159 │   228019  -0.00364274
 160 │   228020  -0.00332446
 161 │   228031  -0.00356238
 162 │   242596   0.00243599
 163 │   242599   0.00293216
 164 │   242601  -0.00496473
 165 │   242602  -0.00524893
 166 │   242603  -0.0050301
 167 │   242605  -0.00428952
 168 │   242606  -0.00424706
 169 │   242607  -0.00522781
 170 │   242609  -0.00435874
 171 │   242612  -0.00459084
 172 │   242614   0.00287149
 173 │   301456   0.00201943
 174 │   301457   0.000988206
 175 │   301459   0.00267036
 176 │   301462   0.00274365
 177 │   301463   0.00282068
 178 │   301464   0.00248725
 179 │   301466   0.00275205
 180 │   301467   0.00283796
 181 │   301468   0.00284164
 182 │   301469   0.00329597
 183 │   301470   0.00338272
 184 │   301471   0.00285642
 185 │   301472   0.00139418
 186 │   301473   0.00288908
 187 │   301475   0.00251559
 188 │   301476   0.00262199
 189 │   301479   0.00145273
 190 │   301480   0.00234863
 191 │   301489  -0.00103592
 192 │   309990  -0.00290055
 193 │   309993  -0.00540671
 194 │   309995  -0.00244605
 195 │   309996  -0.0065097
 196 │   309998   0.00556462
 197 │   309999  -0.00212814
 198 │   310000   0.00603601
 199 │   310003   0.00603298
 200 │   310006   0.00615293
 201 │   310010  -0.00952049
 202 │   310012   0.00622655
 203 │   310013   0.00607194
 204 │   310014  -0.00626461
 205 │   310015  -0.00672882
 206 │   310017   0.0064368
 207 │   310018  -0.00680143
 208 │   310019   0.00649027
 209 │   310020  -0.0065763
 210 │   310021  -0.00103198
 211 │   310023  -0.0023864
 212 │   310024   0.00409208
 213 │   310027  -0.0034844
 214 │   310030  -0.00387452
 215 │   310033  -0.00529092
 216 │   310037  -0.00407342
 217 │   310041  -0.00388775
 218 │   310042  -0.00230602
 219 │   310043  -0.00223359
 220 │   310044  -0.00228178
 221 │   310057  -0.00445333
 222 │   310059  -0.00434128
 223 │   310060  -0.00340865
 224 │   310069  -0.00420809
 225 │   310070  -0.00422437
 226 │   310072  -0.00412025
 227 │   310082   0.00404452
 228 │   310103   0.00352362
 229 │   334004  -0.0023117
 230 │   371857   0.00280391
 231 │   391779  -0.00292349
 232 │   391780  -0.00261309
 233 │   391781  -0.00449136
 234 │   391782  -0.00444693
 235 │   391783  -0.0044222
 236 │   391785   0.0024679
 237 │   391787  -0.00438399
 238 │   391789  -0.00395001
 239 │   391791  -0.00396382
 240 │   391792   0.00346505
 241 │   391793  -0.00289671
 242 │   391794  -0.00390994
 243 │   391795   0.00321832
 244 │   407582   0.00194181
 245 │   407592   0.00251484
 246 │   407600   0.00244519
 247 │   411013  -0.00199058
 248 │   411030  -0.00192926
 249 │   434532  -0.00348811
 250 │   434545  -0.00404465
 251 │   434560  -0.003207
 252 │   434561  -0.00328262
 253 │   434564  -0.00297668
 254 │   434573  -0.00365329
 255 │   434574  -0.00367234
 256 │   434594  -0.00296473
 257 │   438519   0.0029049
 258 │   438521   0.00338992
 259 │   438526   0.00322332
 260 │   438529   0.00509036
 261 │   438531   0.00342876
 262 │   450535   0.000832889
 263 │   450537  -0.00114542
 264 │   450538   0.00105295
 265 │   450540   0.00117106

Trait 6: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -1.41789e-5
   2 │        2  -0.02785
   3 │        3   0.00788558
   4 │        4   0.00756113
   5 │        5   0.000844527
   6 │        6  -0.00099076
   7 │        7   0.000567379
   8 │        8  -0.000665814
   9 │        9   0.000535911
  10 │       10   0.00024253
  11 │       11  -0.000191663
  12 │       12   0.000191233
  13 │       13   0.00208764
  14 │       14  -0.00253818

Trait 7: IHT estimated 278 nonzero SNP predictors
278×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.00515404
   2 │    11578  -0.00520232
   3 │    11579   0.00529551
   4 │    11580   0.0052462
   5 │    11581  -0.00515837
   6 │    11584  -0.00335123
   7 │    11590   0.00498435
   8 │    11592  -0.0036616
   9 │    11598  -0.00258126
  10 │    33128  -0.00343638
  11 │    33129  -0.0034076
  12 │    33130  -0.00344886
  13 │    33132  -0.00349183
  14 │    33136   0.00201798
  15 │    41945  -0.00587919
  16 │    41948  -0.00155683
  17 │    41950  -0.00173153
  18 │    41952  -0.00647509
  19 │    41953  -0.00277436
  20 │    41954  -0.00641624
  21 │    41955  -0.00641738
  22 │    41956  -0.00637528
  23 │    41959   0.00655825
  24 │    41963  -0.00660797
  25 │    41964   0.00450875
  26 │    41965   0.0044263
  27 │    41966  -0.00332119
  28 │    41967  -0.0066369
  29 │    41968   0.00383657
  30 │    41969  -0.00298748
  31 │    41972  -0.00305089
  32 │    41975   0.00273439
  33 │    41983  -0.00212086
  34 │    41985   0.00218649
  35 │    41988   0.00216583
  36 │    42900   0.00187039
  37 │    42905  -0.00169974
  38 │    42913  -0.00219712
  39 │    42916  -0.0033476
  40 │    42919  -0.00363388
  41 │    42921  -0.00298888
  42 │    42925  -0.00421892
  43 │    42927  -0.00362178
  44 │    42928  -0.00420437
  45 │    42930  -0.00317741
  46 │    42931  -0.0035893
  47 │    42932  -0.00345699
  48 │    42933  -0.0064201
  49 │    42934  -0.0062233
  50 │    42935  -0.00614742
  51 │    42936  -0.00275821
  52 │    42938  -0.00534989
  53 │    42941   0.00433566
  54 │    42942   0.00434439
  55 │    42943   0.00420194
  56 │    42945   0.00442357
  57 │    42947   0.00424074
  58 │    42956  -0.00266654
  59 │    42977   0.00200352
  60 │    61929  -0.0032013
  61 │    61930  -0.00356747
  62 │    61932  -0.00384797
  63 │    61934  -0.00201988
  64 │    61937  -0.00196553
  65 │    61945  -0.00143091
  66 │    70920  -0.00127674
  67 │    70928   0.00125277
  68 │    70930   0.00111065
  69 │    70931   0.00108738
  70 │    70932   0.00107662
  71 │    70933   0.00108429
  72 │    70935   0.00111566
  73 │    70938   0.000931713
  74 │    70941   0.00084849
  75 │   144088   0.00224316
  76 │   144090   0.00323602
  77 │   144091   0.00319235
  78 │   158405   0.00216856
  79 │   158406   0.00239467
  80 │   158407   0.002326
  81 │   174902   0.00132937
  82 │   175000   0.00249058
  83 │   188679   0.00110267
  84 │   188681   0.00101154
  85 │   188682   0.00126974
  86 │   188685   0.00066992
  87 │   188687   0.000950768
  88 │   188690   0.000729512
  89 │   188691   0.000926649
  90 │   190680  -0.00129165
  91 │   190681  -0.00144184
  92 │   190683  -0.00130174
  93 │   190685  -0.0011364
  94 │   190686  -0.00116027
  95 │   194328  -0.00255583
  96 │   194351  -0.00192318
  97 │   194353  -0.00475336
  98 │   194377   0.00228295
  99 │   194387  -0.00219126
 100 │   194388  -0.00229003
 101 │   194389  -0.00227065
 102 │   194401   0.00177693
 103 │   194409  -0.0061187
 104 │   194410   0.00145474
 105 │   194415  -0.00624722
 106 │   194419  -0.0010584
 107 │   194427  -0.00225773
 108 │   194432   0.00109868
 109 │   194439  -0.00247676
 110 │   194455  -0.00316764
 111 │   194489  -0.00155799
 112 │   208920   0.00231696
 113 │   208924  -0.00405202
 114 │   208925  -0.0047562
 115 │   208926  -0.00483147
 116 │   208927  -0.00483008
 117 │   208928  -0.00469425
 118 │   208931   0.000787681
 119 │   208934  -0.00479243
 120 │   208939  -0.0047292
 121 │   208941  -0.00487643
 122 │   208944  -0.00464457
 123 │   208947  -0.00482871
 124 │   208948  -0.00496603
 125 │   208949  -0.0048824
 126 │   208950  -0.00173316
 127 │   208951  -0.00512345
 128 │   208952  -0.00515738
 129 │   208954  -0.004842
 130 │   208956  -0.00395463
 131 │   208958   0.00179797
 132 │   208966  -0.00181038
 133 │   225918   0.00120536
 134 │   225927  -0.00113727
 135 │   225929  -0.00129614
 136 │   226031  -0.000566586
 137 │   226040   0.00057114
 138 │   227975   0.00346973
 139 │   227981   0.00351609
 140 │   227982  -0.00418964
 141 │   227983  -0.00227889
 142 │   227987  -0.00555714
 143 │   227988  -0.00537025
 144 │   227989  -0.00620348
 145 │   227990  -0.00606952
 146 │   227991  -0.00792012
 147 │   227992  -0.00635949
 148 │   227993  -0.00792955
 149 │   227994  -0.00752136
 150 │   227995  -0.00676857
 151 │   227996  -0.00683122
 152 │   227997  -0.00415878
 153 │   227999  -0.00541372
 154 │   228000  -0.00779989
 155 │   228001  -0.00779006
 156 │   228002  -0.00752395
 157 │   228003  -0.0074121
 158 │   228004  -0.00753278
 159 │   228005  -0.00717314
 160 │   228006  -0.00636013
 161 │   228007  -0.00637292
 162 │   228008  -0.0074802
 163 │   228009  -0.0020871
 164 │   228011  -0.00452772
 165 │   228013  -0.00329641
 166 │   228014  -0.00762944
 167 │   228019  -0.00373981
 168 │   228020  -0.00366297
 169 │   228031  -0.0021593
 170 │   242593  -0.00198804
 171 │   242596   0.00274492
 172 │   242599   0.00261711
 173 │   242601  -0.00537406
 174 │   242602  -0.0053346
 175 │   242603  -0.00545113
 176 │   242605  -0.00426718
 177 │   242606  -0.00422633
 178 │   242607  -0.0053774
 179 │   242609  -0.00429719
 180 │   242612  -0.00453219
 181 │   242614   0.00205054
 182 │   301456   0.00189623
 183 │   301459   0.00204089
 184 │   301462   0.00197256
 185 │   301463   0.00202849
 186 │   301464   0.00192655
 187 │   301466   0.00178336
 188 │   301467   0.00207051
 189 │   301468   0.00212192
 190 │   301469   0.00206697
 191 │   301470   0.00210494
 192 │   301471   0.00208124
 193 │   301472   0.000680243
 194 │   301473   0.00204677
 195 │   301475   0.0011477
 196 │   301476   0.00213981
 197 │   301480   0.00170128
 198 │   309988   0.00134502
 199 │   309990  -0.00289123
 200 │   309993  -0.00521411
 201 │   309995  -0.00239575
 202 │   309996  -0.00671227
 203 │   309998   0.00593845
 204 │   309999  -0.00212186
 205 │   310000   0.0061452
 206 │   310003   0.00608609
 207 │   310006   0.00617253
 208 │   310010  -0.00959612
 209 │   310012   0.00626486
 210 │   310013   0.00612701
 211 │   310014  -0.0063708
 212 │   310015  -0.00680913
 213 │   310016  -0.00200054
 214 │   310017   0.00646911
 215 │   310018  -0.00686059
 216 │   310019   0.00647526
 217 │   310020  -0.00665001
 218 │   310023  -0.00194338
 219 │   310024   0.00437016
 220 │   310027  -0.00356887
 221 │   310030  -0.0039269
 222 │   310033  -0.00535287
 223 │   310037  -0.00415318
 224 │   310041  -0.00389981
 225 │   310042  -0.00290867
 226 │   310043  -0.00191859
 227 │   310044  -0.00288683
 228 │   310057  -0.00443589
 229 │   310059  -0.00430178
 230 │   310060  -0.00261431
 231 │   310069  -0.0039164
 232 │   310070  -0.00393909
 233 │   310072  -0.00389407
 234 │   310082   0.00380636
 235 │   310103   0.00311996
 236 │   334000  -0.00112172
 237 │   334004  -0.00130911
 238 │   371857   0.00194441
 239 │   373976  -0.00454863
 240 │   391779  -0.00301721
 241 │   391780  -0.00282753
 242 │   391781  -0.00386068
 243 │   391782  -0.00402508
 244 │   391783  -0.00406931
 245 │   391785   0.0023707
 246 │   391787  -0.00407087
 247 │   391789  -0.00382762
 248 │   391791  -0.00406906
 249 │   391792   0.00307833
 250 │   391793  -0.00283189
 251 │   391794  -0.00411492
 252 │   391795   0.00263703
 253 │   407582   0.00142608
 254 │   407592   0.00193446
 255 │   407600   0.00211479
 256 │   411013  -0.00184402
 257 │   432754  -0.00129494
 258 │   432759  -0.00134592
 259 │   434532  -0.00407705
 260 │   434545  -0.00484353
 261 │   434550   0.00176407
 262 │   434553  -0.00205217
 263 │   434560  -0.00356178
 264 │   434561  -0.00351854
 265 │   434564  -0.00268696
 266 │   434570  -0.00174619
 267 │   434573  -0.00409291
 268 │   434574  -0.00418975
 269 │   434594  -0.00301158
 270 │   438519   0.00429639
 271 │   438521   0.00179309
 272 │   438526   0.00275726
 273 │   438529   0.00405131
 274 │   438531   0.00359186
 275 │   450535   0.00119826
 276 │   450537  -0.00135475
 277 │   450538   0.00102476
 278 │   450540   0.00129273

Trait 7: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1   2.95342e-5
   2 │        2  -0.0228342
   3 │        3   0.00800419
   4 │        4   0.00767887
   5 │        5   0.00102314
   6 │        6  -0.00141575
   7 │        7   0.000856222
   8 │        8  -0.000994679
   9 │        9  -6.45225e-5
  10 │       10  -0.000377097
  11 │       11  -0.000207575
  12 │       12   4.8658e-5
  13 │       13   0.00201291
  14 │       14  -0.00133414

Trait 8: IHT estimated 271 nonzero SNP predictors
271×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.0047392
   2 │    11578  -0.00473825
   3 │    11579   0.00477753
   4 │    11580   0.00474295
   5 │    11581  -0.00473975
   6 │    11584  -0.00326621
   7 │    11590   0.00453714
   8 │    11592  -0.00305955
   9 │    11598  -0.00231069
  10 │    18181  -0.00355778
  11 │    18182   0.00275384
  12 │    18183  -0.00363136
  13 │    18184   0.00382439
  14 │    18185   0.00359573
  15 │    18186   0.00362366
  16 │    18187  -0.00114743
  17 │    18188   0.0038584
  18 │    18189   0.00369285
  19 │    33128  -0.00182993
  20 │    33129  -0.00184505
  21 │    33130  -0.00182946
  22 │    33132  -0.00170101
  23 │    41911   0.000833483
  24 │    41915  -0.000848446
  25 │    41927  -0.000957729
  26 │    41945  -0.00548959
  27 │    41946   0.00158237
  28 │    41948  -0.0029449
  29 │    41950  -0.00288261
  30 │    41952  -0.00627531
  31 │    41953  -0.00264765
  32 │    41954  -0.00629855
  33 │    41955  -0.00625786
  34 │    41956  -0.00627452
  35 │    41959   0.00656429
  36 │    41963  -0.00663769
  37 │    41964   0.0061244
  38 │    41965   0.0060571
  39 │    41966  -0.00427553
  40 │    41967  -0.00657879
  41 │    41968   0.00528219
  42 │    41969  -0.00253159
  43 │    41972  -0.0039314
  44 │    41975   0.00466461
  45 │    41977   0.00322685
  46 │    41978   0.00329378
  47 │    41979   0.00326253
  48 │    41983  -0.00217845
  49 │    41985   0.0038284
  50 │    41986   0.00281291
  51 │    41988   0.00391248
  52 │    41989   0.00275076
  53 │    41990   0.00152225
  54 │    41992  -0.00278237
  55 │    41997  -0.00174809
  56 │    42016  -0.00125315
  57 │    42913  -0.0030831
  58 │    42916  -0.00214816
  59 │    42919  -0.00239268
  60 │    42921  -0.00200286
  61 │    42925  -0.00338079
  62 │    42927  -0.00240684
  63 │    42928  -0.00333711
  64 │    42930  -0.00202356
  65 │    42931  -0.0023919
  66 │    42932  -0.0022622
  67 │    42933  -0.00549243
  68 │    42934  -0.00533327
  69 │    42935  -0.00533636
  70 │    42936  -0.00264348
  71 │    42938  -0.00416561
  72 │    42941   0.00360906
  73 │    42942   0.00357276
  74 │    42943   0.00359103
  75 │    42945   0.00367819
  76 │    42947   0.00345898
  77 │    45822  -0.00154391
  78 │    45823  -0.00149963
  79 │    61929  -0.00229731
  80 │    61930  -0.00270037
  81 │    61932  -0.00291451
  82 │   144090   0.00250085
  83 │   144091   0.00257388
  84 │   146527   0.00206866
  85 │   146532   0.0020411
  86 │   146549   0.00218647
  87 │   146552   0.00248776
  88 │   146554   0.00231119
  89 │   146557   0.0022701
  90 │   146560   0.00226437
  91 │   146561   0.00262585
  92 │   146564   0.00233501
  93 │   146566   0.00253444
  94 │   146576   0.00256792
  95 │   146579   0.00264967
  96 │   158405   0.00317459
  97 │   158406   0.00353035
  98 │   158407   0.0034836
  99 │   158411   0.00195035
 100 │   174878   0.000539744
 101 │   174881   0.000619822
 102 │   174882   0.000529241
 103 │   174915   0.000515812
 104 │   174926   0.000480201
 105 │   174927   0.000408799
 106 │   174933   0.000413108
 107 │   174936   0.000492006
 108 │   174985   0.00110102
 109 │   174988   0.00113109
 110 │   175000   0.00303556
 111 │   175005   0.00310394
 112 │   175009   0.000452819
 113 │   175032   0.00116954
 114 │   175040   0.00114718
 115 │   175041   0.00118163
 116 │   175075   0.000667031
 117 │   194328  -0.00231409
 118 │   194353  -0.00375364
 119 │   194377   0.0017674
 120 │   194409  -0.00363311
 121 │   194415  -0.00378304
 122 │   194455  -0.00263394
 123 │   208924  -0.00248798
 124 │   208925  -0.00308567
 125 │   208926  -0.00328287
 126 │   208927  -0.00307237
 127 │   208928  -0.00300248
 128 │   208934  -0.00326713
 129 │   208939  -0.00312369
 130 │   208941  -0.00314586
 131 │   208944  -0.0027816
 132 │   208947  -0.00326555
 133 │   208948  -0.00309907
 134 │   208949  -0.00325873
 135 │   208951  -0.00324172
 136 │   208952  -0.00308017
 137 │   208954  -0.00319418
 138 │   208956  -0.00271712
 139 │   227975   0.00241979
 140 │   227981   0.00228737
 141 │   227982  -0.00341302
 142 │   227987  -0.00394788
 143 │   227988  -0.00372774
 144 │   227989  -0.004068
 145 │   227990  -0.0041585
 146 │   227991  -0.00544931
 147 │   227992  -0.00434355
 148 │   227993  -0.00540195
 149 │   227994  -0.00522569
 150 │   227995  -0.00431879
 151 │   227996  -0.00433591
 152 │   227997  -0.00287425
 153 │   227999  -0.00340026
 154 │   228000  -0.00538437
 155 │   228001  -0.00543208
 156 │   228002  -0.00521962
 157 │   228003  -0.00507089
 158 │   228004  -0.00524345
 159 │   228005  -0.00493615
 160 │   228006  -0.0039804
 161 │   228007  -0.00401409
 162 │   228008  -0.00534205
 163 │   228011  -0.00288834
 164 │   228013  -0.00263589
 165 │   228014  -0.00531227
 166 │   228019  -0.00291167
 167 │   228020  -0.00236371
 168 │   242593  -0.00277618
 169 │   242596   0.00228957
 170 │   242599   0.00351497
 171 │   242601  -0.00477437
 172 │   242602  -0.00480213
 173 │   242603  -0.00478473
 174 │   242605  -0.00385942
 175 │   242606  -0.00371913
 176 │   242607  -0.00481152
 177 │   242608   0.00176082
 178 │   242609  -0.00390392
 179 │   242612  -0.00409964
 180 │   309990  -0.00307382
 181 │   309993  -0.00391832
 182 │   309996  -0.0057325
 183 │   309998   0.00491933
 184 │   310000   0.00527486
 185 │   310003   0.00519234
 186 │   310006   0.0053171
 187 │   310010  -0.00831639
 188 │   310012   0.00534701
 189 │   310013   0.00518114
 190 │   310014  -0.00557962
 191 │   310015  -0.00598485
 192 │   310016  -0.00110838
 193 │   310017   0.0055357
 194 │   310018  -0.00605197
 195 │   310019   0.00560513
 196 │   310020  -0.00594001
 197 │   310024   0.00321186
 198 │   310027  -0.00232855
 199 │   310030  -0.00331766
 200 │   310033  -0.00423565
 201 │   310037  -0.00282805
 202 │   310041  -0.00247934
 203 │   310042  -0.00158162
 204 │   310044  -0.00155953
 205 │   310057  -0.00295998
 206 │   310059  -0.00290891
 207 │   310060  -0.00184155
 208 │   310069  -0.00261155
 209 │   310070  -0.00262268
 210 │   310072  -0.00256649
 211 │   310082   0.00250578
 212 │   310103   0.00275621
 213 │   391779  -0.00225068
 214 │   391780  -0.00244268
 215 │   391781  -0.00374598
 216 │   391782  -0.00372528
 217 │   391783  -0.0037211
 218 │   391785   0.0021842
 219 │   391787  -0.00362141
 220 │   391789  -0.00353979
 221 │   391791  -0.00331398
 222 │   391792   0.00248368
 223 │   391793  -0.00261607
 224 │   391794  -0.0032588
 225 │   391795   0.00275415
 226 │   394184   0.002369
 227 │   432754  -0.00571571
 228 │   432757  -0.00424284
 229 │   432759  -0.0058292
 230 │   434501  -0.00159851
 231 │   434519  -0.00221787
 232 │   434532  -0.00457965
 233 │   434545  -0.00587811
 234 │   434550   0.00219562
 235 │   434553  -0.00299613
 236 │   434560  -0.00404429
 237 │   434561  -0.00397729
 238 │   434564  -0.00260597
 239 │   434570  -0.00220511
 240 │   434573  -0.00484187
 241 │   434574  -0.004907
 242 │   434594  -0.00354261
 243 │   438345  -0.00426227
 244 │   438448  -0.00280069
 245 │   438455  -0.00287245
 246 │   438466  -0.00233165
 247 │   438469  -0.0034212
 248 │   438476  -0.00266192
 249 │   438479  -0.00246709
 250 │   438483  -0.0025338
 251 │   438489  -0.00179444
 252 │   438492  -0.0019167
 253 │   438494  -0.0020181
 254 │   438499   0.00169195
 255 │   438500   0.00218635
 256 │   438505   0.002032
 257 │   438511  -0.0020055
 258 │   438513   0.00134526
 259 │   438514   0.00130332
 260 │   438515  -0.00213039
 261 │   438518  -0.00153719
 262 │   438519   0.00437476
 263 │   438520   0.00413376
 264 │   438521   0.00311732
 265 │   438526   0.00420497
 266 │   438527   0.00177664
 267 │   438529   0.00434328
 268 │   438530  -0.00324874
 269 │   438531   0.00454728
 270 │   438534  -0.00334782
 271 │   449460   0.00162783

Trait 8: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1   4.52848e-6
   2 │        2  -0.00471238
   3 │        3   0.0029431
   4 │        4   0.00221494
   5 │        5   0.00111555
   6 │        6  -0.000672318
   7 │        7   0.00109524
   8 │        8  -0.00181958
   9 │        9  -0.000914768
  10 │       10   0.000179149
  11 │       11  -0.00027374
  12 │       12   0.000283031
  13 │       13   0.000631285
  14 │       14  -0.00200018

Trait 9: IHT estimated 315 nonzero SNP predictors
315×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.00518429
   2 │    11578  -0.0052937
   3 │    11579   0.00533087
   4 │    11580   0.00532761
   5 │    11581  -0.00522258
   6 │    11584  -0.00344354
   7 │    11590   0.00496667
   8 │    11592  -0.00395292
   9 │    11598  -0.00280608
  10 │    18181  -0.00391704
  11 │    18182   0.00250169
  12 │    18183  -0.0039254
  13 │    18184   0.00389624
  14 │    18185   0.00392297
  15 │    18186   0.00394141
  16 │    18187  -0.00235598
  17 │    18188   0.00395505
  18 │    18189   0.00386966
  19 │    33128  -0.0021943
  20 │    33129  -0.00224511
  21 │    33130  -0.00221328
  22 │    33132  -0.00207957
  23 │    41911   0.00146983
  24 │    41915  -0.00118402
  25 │    41927  -0.00119358
  26 │    41945  -0.00664247
  27 │    41946   0.00242898
  28 │    41948  -0.00307049
  29 │    41950  -0.00321518
  30 │    41952  -0.00735867
  31 │    41953  -0.00283805
  32 │    41954  -0.00733651
  33 │    41955  -0.00734347
  34 │    41956  -0.00732529
  35 │    41958  -0.000752685
  36 │    41959   0.00746072
  37 │    41963  -0.00758024
  38 │    41964   0.00683182
  39 │    41965   0.00677028
  40 │    41966  -0.00607587
  41 │    41967  -0.00754091
  42 │    41968   0.00578864
  43 │    41969  -0.0020836
  44 │    41972  -0.00453863
  45 │    41975   0.0045814
  46 │    41977   0.0037209
  47 │    41978   0.00374236
  48 │    41979   0.00371184
  49 │    41983  -0.00222964
  50 │    41985   0.00361855
  51 │    41986   0.00290761
  52 │    41988   0.00389235
  53 │    41989   0.00286342
  54 │    41990   0.00222062
  55 │    41992  -0.00274585
  56 │    41997  -0.00193645
  57 │    42016  -0.00193853
  58 │    42899  -0.00140176
  59 │    42900   0.00101724
  60 │    42905  -0.000778193
  61 │    42913  -0.00152234
  62 │    42916  -0.00251281
  63 │    42919  -0.00252849
  64 │    42921  -0.00222196
  65 │    42925  -0.00296399
  66 │    42927  -0.00257065
  67 │    42928  -0.00297493
  68 │    42930  -0.00205961
  69 │    42931  -0.00256582
  70 │    42932  -0.00245269
  71 │    42933  -0.00608957
  72 │    42934  -0.0057965
  73 │    42935  -0.00582586
  74 │    42936  -0.00358048
  75 │    42938  -0.00507152
  76 │    42941   0.00401826
  77 │    42942   0.00399557
  78 │    42943   0.00395454
  79 │    42944  -0.00159892
  80 │    42945   0.00404809
  81 │    42946  -0.00160756
  82 │    42947   0.0039014
  83 │    42956  -0.00164393
  84 │    42977   0.00127071
  85 │    61929  -0.00142922
  86 │    61930  -0.00166046
  87 │    61932  -0.00175932
  88 │    61934  -0.000807106
  89 │    61937  -0.000785128
  90 │    95584   0.00210593
  91 │    95588   0.00220327
  92 │    95611   0.00211032
  93 │    95625  -0.00204269
  94 │   144088   0.00126517
  95 │   144090   0.00192389
  96 │   144091   0.00201993
  97 │   146549   0.00226767
  98 │   146552   0.0022046
  99 │   146554   0.00193387
 100 │   146557   0.00250035
 101 │   146560   0.00248713
 102 │   146561   0.00251528
 103 │   146564   0.00250318
 104 │   146566   0.00250696
 105 │   146576   0.00243589
 106 │   158405   0.00379858
 107 │   158406   0.00405459
 108 │   158407   0.00398599
 109 │   158411   0.00294233
 110 │   173137   0.000597995
 111 │   173141   0.000602138
 112 │   173144   0.000617618
 113 │   173163   0.00057744
 114 │   173169   0.000425103
 115 │   174173   0.000704715
 116 │   174769   0.000496363
 117 │   174878   0.000439761
 118 │   174881   0.000468913
 119 │   174915   0.000855078
 120 │   174926   0.000868165
 121 │   174927   0.00087233
 122 │   174933   0.000870239
 123 │   174936   0.000899159
 124 │   174951  -0.000497154
 125 │   174965  -0.000483122
 126 │   174969   0.000875999
 127 │   174971  -0.000476511
 128 │   174984  -0.000485861
 129 │   174985   0.00111141
 130 │   174986   0.000892319
 131 │   174988   0.00115093
 132 │   175000   0.00184543
 133 │   175005   0.00185734
 134 │   175009   0.000972851
 135 │   175032   0.000854517
 136 │   175040   0.000850944
 137 │   175041   0.00087858
 138 │   175056  -0.000782047
 139 │   175075   0.000947841
 140 │   190681  -0.000479094
 141 │   190683  -0.000419599
 142 │   190685  -0.000534459
 143 │   194328  -0.00201249
 144 │   194332   0.00185973
 145 │   194334   0.00187502
 146 │   194353  -0.00300246
 147 │   194409  -0.00246096
 148 │   194415  -0.00254036
 149 │   194455  -0.00249088
 150 │   208920   0.00117465
 151 │   208924  -0.00199897
 152 │   208925  -0.00215023
 153 │   208926  -0.00224259
 154 │   208927  -0.00221968
 155 │   208928  -0.00206633
 156 │   208934  -0.0022185
 157 │   208939  -0.00223617
 158 │   208941  -0.00230318
 159 │   208944  -0.002506
 160 │   208947  -0.00237637
 161 │   208948  -0.002523
 162 │   208949  -0.00236779
 163 │   208950  -0.00198706
 164 │   208951  -0.00266665
 165 │   208952  -0.00236695
 166 │   208954  -0.00267115
 167 │   208956  -0.00184351
 168 │   208958   0.00117979
 169 │   227975   0.00149817
 170 │   227981   0.00323712
 171 │   227982  -0.00229923
 172 │   227983  -0.000877464
 173 │   227987  -0.00335741
 174 │   227988  -0.00317358
 175 │   227989  -0.00532079
 176 │   227990  -0.00523249
 177 │   227991  -0.00672054
 178 │   227992  -0.00565237
 179 │   227993  -0.00675543
 180 │   227994  -0.00640431
 181 │   227995  -0.00605594
 182 │   227996  -0.0061598
 183 │   227997  -0.00238836
 184 │   227999  -0.00473076
 185 │   228000  -0.00688991
 186 │   228001  -0.00670876
 187 │   228002  -0.00644119
 188 │   228003  -0.00660141
 189 │   228004  -0.0064423
 190 │   228005  -0.00628612
 191 │   228006  -0.00561643
 192 │   228007  -0.00568495
 193 │   228008  -0.00647421
 194 │   228009  -0.000503717
 195 │   228011  -0.00253437
 196 │   228013  -0.0016836
 197 │   228014  -0.00641421
 198 │   228019  -0.0028821
 199 │   228020  -0.00224943
 200 │   228031  -0.00109178
 201 │   242590   0.00147329
 202 │   242593  -0.00152712
 203 │   242596   0.00240619
 204 │   242599   0.00307597
 205 │   242601  -0.00620237
 206 │   242602  -0.00620847
 207 │   242603  -0.00626185
 208 │   242605  -0.00487133
 209 │   242606  -0.00476079
 210 │   242607  -0.00624877
 211 │   242609  -0.00481604
 212 │   242612  -0.0051293
 213 │   242614   0.00182425
 214 │   309988   0.00162543
 215 │   309990  -0.00214759
 216 │   309993  -0.00497437
 217 │   309995  -0.00179166
 218 │   309996  -0.00671074
 219 │   309998   0.00545546
 220 │   309999  -0.00234576
 221 │   310000   0.00585008
 222 │   310003   0.00583967
 223 │   310006   0.00590966
 224 │   310010  -0.00929334
 225 │   310012   0.00585186
 226 │   310013   0.00570407
 227 │   310014  -0.00629847
 228 │   310015  -0.00672546
 229 │   310016  -0.00269026
 230 │   310017   0.00603302
 231 │   310018  -0.00684054
 232 │   310019   0.00610387
 233 │   310020  -0.00663129
 234 │   310023  -0.00200831
 235 │   310024   0.00293823
 236 │   310027  -0.00318265
 237 │   310030  -0.00243567
 238 │   310033  -0.00431252
 239 │   310037  -0.00234229
 240 │   310041  -0.00179351
 241 │   310042  -0.00168286
 242 │   310044  -0.00165035
 243 │   310057  -0.00234204
 244 │   310059  -0.00224348
 245 │   310060  -0.000578835
 246 │   310069  -0.00199918
 247 │   310070  -0.00200548
 248 │   310072  -0.00194214
 249 │   310082   0.00188276
 250 │   310103   0.00204328
 251 │   312051   0.00144802
 252 │   312052   0.00147082
 253 │   334000  -0.000847794
 254 │   334004  -0.000872972
 255 │   371857   0.00199468
 256 │   373948   0.00386349
 257 │   373950   0.00421059
 258 │   373951   0.00427046
 259 │   373952  -0.00406147
 260 │   373954  -0.00407364
 261 │   373956   0.0029473
 262 │   373962  -0.00254216
 263 │   373966   0.00174513
 264 │   373969  -0.0019313
 265 │   373973  -0.00170545
 266 │   373976   0.00579749
 267 │   373979  -0.00597046
 268 │   373987  -0.00499779
 269 │   391779  -0.00410323
 270 │   391780  -0.00391687
 271 │   391781  -0.00566503
 272 │   391782  -0.00573845
 273 │   391783  -0.00571652
 274 │   391785   0.00416676
 275 │   391787  -0.00563824
 276 │   391788  -0.00200717
 277 │   391789  -0.0054447
 278 │   391791  -0.00550103
 279 │   391792   0.00454072
 280 │   391793  -0.00451645
 281 │   391794  -0.0055962
 282 │   391795   0.0044125
 283 │   391799   0.00219585
 284 │   391801   0.00198936
 285 │   394184   0.00254861
 286 │   432754  -0.00492469
 287 │   432757  -0.00377172
 288 │   432759  -0.00506157
 289 │   434519  -0.00219573
 290 │   434532  -0.0035982
 291 │   434545  -0.00428291
 292 │   434553  -0.00331002
 293 │   434560  -0.00357126
 294 │   434561  -0.0036203
 295 │   434564  -0.00296833
 296 │   434573  -0.00395979
 297 │   434574  -0.00391713
 298 │   434594  -0.0030926
 299 │   438469  -0.00228906
 300 │   438500   0.00270413
 301 │   438511  -0.00140485
 302 │   438519   0.00486635
 303 │   438520   0.00436609
 304 │   438521   0.00385417
 305 │   438526   0.00469036
 306 │   438529   0.00452329
 307 │   438530  -0.00135314
 308 │   438531   0.00535762
 309 │   438534  -0.00151216
 310 │   449460   0.00218528
 311 │   449595   0.00204569
 312 │   450535   0.00262371
 313 │   450537  -0.00259039
 314 │   450538   0.00232007
 315 │   450540   0.00266984

Trait 9: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1   2.12031e-6
   2 │        2  -0.0130875
   3 │        3   0.0122603
   4 │        4   0.0117612
   5 │        5   0.000112829
   6 │        6  -0.000435353
   7 │        7   0.000624132
   8 │        8  -0.00110595
   9 │        9   7.72857e-5
  10 │       10   0.000109389
  11 │       11  -0.000131541
  12 │       12   0.0007428
  13 │       13  -0.000879667
  14 │       14  -0.00276738

Trait 10: IHT estimated 306 nonzero SNP predictors
306×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    10145  -0.00238354
   2 │    11577  -0.00506004
   3 │    11578  -0.00501746
   4 │    11579   0.00510867
   5 │    11580   0.00501078
   6 │    11581  -0.00508406
   7 │    11584  -0.00287914
   8 │    11590   0.00513704
   9 │    11592  -0.00379343
  10 │    11598  -0.00281521
  11 │    18165  -0.00244769
  12 │    18181  -0.00537573
  13 │    18182   0.00390455
  14 │    18183  -0.0054007
  15 │    18184   0.00524541
  16 │    18185   0.00538393
  17 │    18186   0.00540667
  18 │    18187  -0.0031096
  19 │    18188   0.00517459
  20 │    18189   0.00522328
  21 │    41945  -0.00505941
  22 │    41946   0.00256632
  23 │    41948  -0.00290141
  24 │    41950  -0.0030121
  25 │    41952  -0.00560605
  26 │    41954  -0.00563006
  27 │    41955  -0.00562936
  28 │    41956  -0.00563032
  29 │    41959   0.00527021
  30 │    41963  -0.00525145
  31 │    41964   0.00626056
  32 │    41965   0.00620395
  33 │    41966  -0.00412181
  34 │    41967  -0.00525288
  35 │    41968   0.00539007
  36 │    41971  -0.00230236
  37 │    41972  -0.00354986
  38 │    41974   0.00267235
  39 │    41975   0.00544932
  40 │    41976  -0.00272522
  41 │    41977   0.00596935
  42 │    41978   0.00599586
  43 │    41979   0.00594964
  44 │    41985   0.00475106
  45 │    41986   0.00523377
  46 │    41988   0.00515093
  47 │    41989   0.00396894
  48 │    41990   0.0043113
  49 │    41992  -0.00523939
  50 │    41997  -0.00355233
  51 │    42016  -0.0022782
  52 │    42933  -0.00460827
  53 │    42934  -0.00452979
  54 │    42935  -0.00448101
  55 │    42938  -0.00357456
  56 │    42941   0.00278966
  57 │    42942   0.00279697
  58 │    42943   0.00275786
  59 │    42945   0.00283665
  60 │    45816  -0.00187162
  61 │    45817  -0.00183663
  62 │    45821  -0.00174027
  63 │    45822  -0.00187884
  64 │    45823  -0.00177907
  65 │    95584   0.00305105
  66 │    95588   0.00297111
  67 │    95595   0.00212682
  68 │    95611   0.00266474
  69 │    95616  -0.00186489
  70 │    95625  -0.00233634
  71 │   146549   0.00265445
  72 │   146552   0.0035926
  73 │   146554   0.00341814
  74 │   146557   0.00387292
  75 │   146560   0.00384602
  76 │   146561   0.00392529
  77 │   146564   0.00389492
  78 │   146566   0.00395796
  79 │   146576   0.00362859
  80 │   146579   0.00282571
  81 │   158405   0.00291175
  82 │   158406   0.00299248
  83 │   158407   0.00290658
  84 │   158411   0.0024166
  85 │   174873   0.000912603
  86 │   174878   0.00094952
  87 │   174881   0.000982514
  88 │   174882   0.000899845
  89 │   174915   0.000537389
  90 │   174926   0.000544708
  91 │   174927   0.000403361
  92 │   174933   0.000429823
  93 │   174936   0.000485658
  94 │   174969   0.000410734
  95 │   174972   0.000381006
  96 │   174985   0.00103167
  97 │   174986   0.00040335
  98 │   174988   0.00106262
  99 │   175000   0.00219718
 100 │   175005   0.00229857
 101 │   175009   0.0005582
 102 │   175032   0.00123788
 103 │   175040   0.0012174
 104 │   175041   0.00123159
 105 │   175075   0.000661555
 106 │   175096   0.000502687
 107 │   194332   0.00275349
 108 │   194334   0.00288777
 109 │   196900  -0.00166873
 110 │   196912  -0.00151933
 111 │   196947  -0.00182179
 112 │   227989  -0.00339666
 113 │   227990  -0.00345029
 114 │   227991  -0.00371252
 115 │   227992  -0.00366489
 116 │   227993  -0.00368852
 117 │   227994  -0.00360181
 118 │   227995  -0.00380621
 119 │   227996  -0.00377668
 120 │   227999  -0.00323633
 121 │   228000  -0.00383738
 122 │   228001  -0.00368467
 123 │   228002  -0.00365562
 124 │   228003  -0.00369553
 125 │   228004  -0.00361579
 126 │   228005  -0.00366584
 127 │   228006  -0.00338237
 128 │   228007  -0.0034263
 129 │   228008  -0.00372132
 130 │   228014  -0.003768
 131 │   242599   0.00333726
 132 │   242601  -0.00501464
 133 │   242602  -0.00481933
 134 │   242603  -0.00500358
 135 │   242605  -0.00392338
 136 │   242606  -0.003807
 137 │   242607  -0.00487981
 138 │   242609  -0.0039448
 139 │   242612  -0.00435643
 140 │   266000   0.00142666
 141 │   266002   0.00129762
 142 │   266003   0.00137837
 143 │   266004   0.00142199
 144 │   266006   0.00142048
 145 │   266007   0.00196531
 146 │   266008   0.00185556
 147 │   266009   0.00190451
 148 │   266010   0.00190159
 149 │   266011   0.00199124
 150 │   301456  -0.00340748
 151 │   301459  -0.00390027
 152 │   301462  -0.00394425
 153 │   301463  -0.00396734
 154 │   301464  -0.00366161
 155 │   301466  -0.00378276
 156 │   301467  -0.00390771
 157 │   301468  -0.00384317
 158 │   301469  -0.00351194
 159 │   301470  -0.00348468
 160 │   301471  -0.00390066
 161 │   301472  -0.00325333
 162 │   301473  -0.0039594
 163 │   301476  -0.00388197
 164 │   301480  -0.00386408
 165 │   309993  -0.00393581
 166 │   309996  -0.00474024
 167 │   309998   0.00399772
 168 │   310000   0.00420993
 169 │   310003   0.00412646
 170 │   310006   0.00413621
 171 │   310010  -0.00676584
 172 │   310012   0.00413079
 173 │   310013   0.00403222
 174 │   310014  -0.00484868
 175 │   310015  -0.00503142
 176 │   310017   0.0043208
 177 │   310018  -0.00510317
 178 │   310019   0.0043336
 179 │   310020  -0.00522396
 180 │   310033  -0.00499405
 181 │   333520  -0.0010017
 182 │   333522  -0.00150217
 183 │   333524   0.000702446
 184 │   333526   0.00070218
 185 │   333528  -0.0013318
 186 │   333530  -0.00128953
 187 │   333533   0.000695002
 188 │   333535   0.000727064
 189 │   333536   0.000704639
 190 │   333542   0.000470736
 191 │   373912   0.00125585
 192 │   373913   0.00145721
 193 │   373915  -0.00204574
 194 │   373916   0.000666967
 195 │   373917   0.0011629
 196 │   373924  -0.00192621
 197 │   373926   0.0019594
 198 │   373927   0.00107279
 199 │   373928  -0.00307114
 200 │   373931  -0.00143051
 201 │   373932   0.00116406
 202 │   373937  -0.002583
 203 │   373938   0.00293727
 204 │   373939  -0.00192658
 205 │   373948   0.0107297
 206 │   373949  -0.00252109
 207 │   373950   0.0118027
 208 │   373951   0.0119202
 209 │   373952  -0.0117678
 210 │   373954  -0.0117657
 211 │   373955   0.00297014
 212 │   373956   0.0104335
 213 │   373957   0.00118031
 214 │   373958   0.000938256
 215 │   373962  -0.00749787
 216 │   373963   0.00210879
 217 │   373964   0.000818314
 218 │   373966   0.00547538
 219 │   373969  -0.00520452
 220 │   373972  -0.00253422
 221 │   373973  -0.00698215
 222 │   373974  -0.00355245
 223 │   373976   0.0138746
 224 │   373978   0.00581092
 225 │   373979  -0.0136818
 226 │   373981  -0.00401215
 227 │   373982  -0.00274673
 228 │   373986  -0.00219966
 229 │   373987  -0.00935831
 230 │   373988  -0.00575035
 231 │   373990  -0.00223202
 232 │   373991  -0.0029974
 233 │   373995   0.00303016
 234 │   374005  -0.00204848
 235 │   374006   0.0016769
 236 │   374030   0.0024043
 237 │   374052  -0.00237109
 238 │   391779  -0.0037288
 239 │   391780  -0.00410809
 240 │   391781  -0.00590885
 241 │   391782  -0.00604239
 242 │   391783  -0.0060358
 243 │   391785   0.00368643
 244 │   391787  -0.00594078
 245 │   391789  -0.00506155
 246 │   391791  -0.00511205
 247 │   391792   0.00455387
 248 │   391793  -0.00435391
 249 │   391794  -0.0050595
 250 │   391795   0.00463452
 251 │   391799   0.00340147
 252 │   391801   0.00312577
 253 │   394184   0.00277495
 254 │   411579   0.0025368
 255 │   411582   0.00328587
 256 │   411645   0.0023165
 257 │   432731  -0.00227639
 258 │   432735  -0.00219535
 259 │   432745  -0.00162829
 260 │   432747  -0.00169641
 261 │   432754  -0.0064612
 262 │   432757  -0.00462611
 263 │   432759  -0.006528
 264 │   432760  -0.00168343
 265 │   432761  -0.00250477
 266 │   434532  -0.00387041
 267 │   434545  -0.00413601
 268 │   434553  -0.00247023
 269 │   434560  -0.00341316
 270 │   434561  -0.00343165
 271 │   434573  -0.00379749
 272 │   434574  -0.00382673
 273 │   434594  -0.00278212
 274 │   438448  -0.00231378
 275 │   438455  -0.00223927
 276 │   438466  -0.00205132
 277 │   438469  -0.00422509
 278 │   438479  -0.0027431
 279 │   438483  -0.00212939
 280 │   438489  -0.00193787
 281 │   438492  -0.00223374
 282 │   438494  -0.00223556
 283 │   438499   0.00197881
 284 │   438500   0.00257083
 285 │   438505   0.00196689
 286 │   438511  -0.0034967
 287 │   438514   0.00206748
 288 │   438515  -0.0018735
 289 │   438518  -0.003399
 290 │   438519   0.00479387
 291 │   438520   0.00403074
 292 │   438521   0.00281879
 293 │   438526   0.00436155
 294 │   438527   0.00230239
 295 │   438529   0.00386704
 296 │   438530  -0.0057787
 297 │   438531   0.00529085
 298 │   438534  -0.00470485
 299 │   439403  -0.000836284
 300 │   439406   0.000977093
 301 │   439415   0.000473912
 302 │   439420   0.000494161
 303 │   449460   0.00247179
 304 │   449472  -0.00181575
 305 │   450537   0.00343534
 306 │   450538  -0.0034722

Trait 10: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -8.69474e-6
   2 │        2   0.0221913
   3 │        3   0.0111238
   4 │        4   0.010356
   5 │        5   0.0012731
   6 │        6  -0.000465345
   7 │        7   0.00169089
   8 │        8  -0.00161116
   9 │        9  -0.000587529
  10 │       10  -3.89631e-5
  11 │       11  -5.04644e-5
  12 │       12   1.24807e-5
  13 │       13   0.00114531
  14 │       14   0.00216013

Trait 11: IHT estimated 225 nonzero SNP predictors
225×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    10145  -0.00245611
   2 │    10157   0.00126433
   3 │    10164  -0.00180432
   4 │    10171   0.00177109
   5 │    11577  -0.00183638
   6 │    11579   0.00190078
   7 │    11581  -0.00192428
   8 │    11590   0.00187614
   9 │    18165  -0.00351943
  10 │    18170  -0.00237181
  11 │    18178   0.00253389
  12 │    18181  -0.00665583
  13 │    18182   0.00553402
  14 │    18183  -0.00675903
  15 │    18184   0.00654726
  16 │    18185   0.00668425
  17 │    18186   0.00670517
  18 │    18187  -0.00357774
  19 │    18188   0.00651723
  20 │    18189   0.00654634
  21 │    18191   0.00215712
  22 │    18197  -0.00310476
  23 │    31767   0.00119778
  24 │    31770   0.000887512
  25 │    41940  -0.00245722
  26 │    41961  -0.00332344
  27 │    41964   0.00350403
  28 │    41965   0.00348322
  29 │    41968   0.00392755
  30 │    41971  -0.003038
  31 │    41974   0.00357891
  32 │    41975   0.00412692
  33 │    41977   0.00595315
  34 │    41978   0.00601112
  35 │    41979   0.00595108
  36 │    41985   0.00396714
  37 │    41986   0.00581211
  38 │    41988   0.00328721
  39 │    41989   0.00328025
  40 │    41990   0.00466087
  41 │    41992  -0.00579169
  42 │    41997  -0.0046774
  43 │    45816  -0.00359119
  44 │    45817  -0.00369272
  45 │    45821  -0.00355939
  46 │    45822  -0.00410364
  47 │    45823  -0.00406205
  48 │   146525   0.00182771
  49 │   146527   0.00245376
  50 │   146529   0.00258949
  51 │   146530   0.00159367
  52 │   146532   0.00242221
  53 │   146537   0.00191433
  54 │   146539   0.00187983
  55 │   146544   0.00185344
  56 │   146546   0.00190259
  57 │   146549   0.00323871
  58 │   146552   0.00341384
  59 │   146554   0.00368641
  60 │   146557   0.00401349
  61 │   146560   0.00396235
  62 │   146561   0.0039189
  63 │   146564   0.00395889
  64 │   146566   0.00393435
  65 │   146569   0.00298071
  66 │   146576   0.00377784
  67 │   146579   0.00346939
  68 │   146588  -0.00300938
  69 │   146596   0.00255063
  70 │   146598   0.00250041
  71 │   175032   0.00488881
  72 │   175040   0.00480909
  73 │   175041   0.00495295
  74 │   227989   0.00201933
  75 │   227991   0.00147299
  76 │   227993   0.00148858
  77 │   227994   0.00149538
  78 │   227996   0.00182095
  79 │   228000   0.00136645
  80 │   228001   0.00144864
  81 │   228002   0.00136533
  82 │   228003   0.00137024
  83 │   228004   0.0013651
  84 │   228005   0.00121879
  85 │   228006   0.00197407
  86 │   228007   0.00195882
  87 │   228008   0.00129958
  88 │   228014   0.00147027
  89 │   242601  -0.00338374
  90 │   242603  -0.00335091
  91 │   266000   0.00189346
  92 │   266002   0.00186193
  93 │   266003   0.00192463
  94 │   266004   0.00189295
  95 │   266006   0.00183431
  96 │   266007   0.00321897
  97 │   266008   0.00315282
  98 │   266009   0.00322376
  99 │   266010   0.00322063
 100 │   266011   0.00331323
 101 │   266021   0.00142979
 102 │   266031   0.00144805
 103 │   266037   0.00129289
 104 │   286075  -0.00080915
 105 │   286080  -0.00084352
 106 │   286084  -0.000798928
 107 │   301456  -0.00309606
 108 │   301457  -0.00198084
 109 │   301458   0.00155647
 110 │   301459  -0.0037639
 111 │   301462  -0.00381248
 112 │   301463  -0.0039294
 113 │   301464  -0.00353939
 114 │   301466  -0.00378555
 115 │   301467  -0.00383862
 116 │   301468  -0.00381728
 117 │   301469  -0.00376322
 118 │   301470  -0.00374358
 119 │   301471  -0.00382888
 120 │   301472  -0.00299797
 121 │   301473  -0.00380008
 122 │   301475  -0.00269848
 123 │   301476  -0.00369142
 124 │   301479  -0.00214783
 125 │   301480  -0.00317489
 126 │   301481  -0.000842731
 127 │   301482  -0.00112489
 128 │   301488   0.000573645
 129 │   301489   0.00114654
 130 │   301492   0.000514598
 131 │   301493   0.000538351
 132 │   333520  -0.00283287
 133 │   333522  -0.00285672
 134 │   373928  -0.00328103
 135 │   373948   0.00440744
 136 │   373950   0.0047893
 137 │   373951   0.00447169
 138 │   373952  -0.00451144
 139 │   373954  -0.00455522
 140 │   373955   0.00277272
 141 │   373956   0.00284267
 142 │   373962  -0.00257191
 143 │   373966   0.00213592
 144 │   373969  -0.00236415
 145 │   373973  -0.00166531
 146 │   373976   0.0045324
 147 │   373978   0.00279039
 148 │   373979  -0.00456307
 149 │   373987  -0.0042409
 150 │   373988  -0.00200629
 151 │   407592  -0.000739909
 152 │   407600  -0.000813836
 153 │   408087  -0.00189504
 154 │   411579   0.0021387
 155 │   411582   0.00288601
 156 │   411645   0.00181623
 157 │   432723  -0.00203476
 158 │   432731  -0.00237571
 159 │   432735  -0.00289145
 160 │   432745  -0.00242052
 161 │   432747  -0.00251797
 162 │   432754  -0.00718652
 163 │   432757  -0.00528322
 164 │   432759  -0.00724622
 165 │   432760  -0.00275805
 166 │   432761  -0.00268105
 167 │   434532  -0.00352959
 168 │   434545  -0.00376522
 169 │   434553  -0.00279078
 170 │   434560  -0.00313241
 171 │   434561  -0.0032058
 172 │   434573  -0.00352703
 173 │   434574  -0.00349114
 174 │   434594  -0.00272506
 175 │   438286  -0.00245463
 176 │   438303  -0.00184732
 177 │   438325  -0.00266531
 178 │   438339  -0.00203967
 179 │   438345  -0.00334146
 180 │   438363  -0.00215809
 181 │   438366  -0.00148542
 182 │   438391  -0.00158827
 183 │   438435  -0.00299975
 184 │   438439  -0.00225975
 185 │   438441  -0.00155011
 186 │   438442  -0.00283334
 187 │   438445  -0.00241668
 188 │   438448  -0.00568648
 189 │   438450  -0.00238526
 190 │   438455  -0.00626978
 191 │   438466  -0.00673951
 192 │   438467  -0.00313861
 193 │   438469  -0.0110702
 194 │   438470   0.0027802
 195 │   438476  -0.00449737
 196 │   438478  -0.00277203
 197 │   438479  -0.00851429
 198 │   438481  -0.00223503
 199 │   438483  -0.00584469
 200 │   438489  -0.00708639
 201 │   438492  -0.00743327
 202 │   438494  -0.00754458
 203 │   438499   0.00532199
 204 │   438500   0.00580292
 205 │   438505   0.00540557
 206 │   438507   0.00302066
 207 │   438509   0.0037384
 208 │   438511  -0.00661759
 209 │   438513   0.00304068
 210 │   438514   0.00310253
 211 │   438515  -0.00591045
 212 │   438516  -0.00280172
 213 │   438518  -0.0127765
 214 │   438519   0.00636857
 215 │   438520   0.00699395
 216 │   438525  -0.00625567
 217 │   438526   0.0072736
 218 │   438527   0.0049464
 219 │   438530  -0.0176627
 220 │   438531   0.00865176
 221 │   438533  -0.00630477
 222 │   438534  -0.00994495
 223 │   438557  -0.00180649
 224 │   438562  -0.00163089
 225 │   438575  -0.00172229

Trait 11: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1   3.44271e-5
   2 │        2   0.0272691
   3 │        3   0.000133474
   4 │        4  -0.000744848
   5 │        5  -0.000377684
   6 │        6   0.000554739
   7 │        7   0.000626849
   8 │        8  -0.00224934
   9 │        9  -0.00210149
  10 │       10   0.00122625
  11 │       11  -0.00121601
  12 │       12   0.000113612
  13 │       13   0.00127929
  14 │       14   9.61175e-5

Trait 12: IHT estimated 250 nonzero SNP predictors
250×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    10145  -0.00202285
   2 │    10160   0.00205467
   3 │    10164  -0.00153924
   4 │    10171   0.00163664
   5 │    18147  -0.0023048
   6 │    18165  -0.00324224
   7 │    18170  -0.0021026
   8 │    18171   0.00262862
   9 │    18174  -0.00237239
  10 │    18178   0.00280392
  11 │    18181  -0.0073543
  12 │    18182   0.00601327
  13 │    18183  -0.00741785
  14 │    18184   0.00716683
  15 │    18185   0.00735314
  16 │    18186   0.0073484
  17 │    18187  -0.00449193
  18 │    18188   0.00715153
  19 │    18189   0.00725909
  20 │    18191   0.00263186
  21 │    18197  -0.00298097
  22 │    18198  -0.00151588
  23 │    18212  -0.00163627
  24 │    18218  -0.00153227
  25 │    41961  -0.00241835
  26 │    41964   0.0056495
  27 │    41965   0.00561797
  28 │    41966  -0.00307321
  29 │    41968   0.00495346
  30 │    41971  -0.00252794
  31 │    41972  -0.00307373
  32 │    41974   0.00293887
  33 │    41975   0.00508161
  34 │    41977   0.00545431
  35 │    41978   0.00546707
  36 │    41979   0.00541015
  37 │    41985   0.0048356
  38 │    41986   0.00526233
  39 │    41988   0.00444444
  40 │    41989   0.00394782
  41 │    41990   0.00459088
  42 │    41992  -0.00522753
  43 │    41997  -0.0041871
  44 │    42933  -0.00373725
  45 │    42934  -0.00398372
  46 │    42935  -0.00399063
  47 │    45816  -0.00306562
  48 │    45817  -0.00312236
  49 │    45821  -0.0030303
  50 │    45822  -0.00375677
  51 │    45823  -0.00371556
  52 │   146505  -0.000226045
  53 │   146510  -0.000393902
  54 │   146512  -0.000423047
  55 │   146513  -0.000347501
  56 │   146518   0.000652092
  57 │   146519   0.000650221
  58 │   146520  -0.000238826
  59 │   146525   0.00239104
  60 │   146527   0.00220018
  61 │   146528  -0.00039604
  62 │   146529   0.00159385
  63 │   146530   0.00137464
  64 │   146531   0.000575304
  65 │   146532   0.00218766
  66 │   146537   0.00214719
  67 │   146538   0.00152673
  68 │   146539   0.00207366
  69 │   146540  -0.000400996
  70 │   146544   0.00199635
  71 │   146545   0.00110983
  72 │   146546   0.00223347
  73 │   146549   0.00302691
  74 │   146552   0.00374441
  75 │   146553  -0.000350385
  76 │   146554   0.00401459
  77 │   146557   0.00380159
  78 │   146560   0.00372603
  79 │   146561   0.00376704
  80 │   146564   0.00372038
  81 │   146566   0.00392075
  82 │   146569   0.00215432
  83 │   146576   0.00363391
  84 │   146577   0.000253034
  85 │   146579   0.00337145
  86 │   146580  -0.00172131
  87 │   146581  -0.000315724
  88 │   146583  -0.000315692
  89 │   146585  -0.000369015
  90 │   146587  -0.00036853
  91 │   146588  -0.00219
  92 │   146589   0.00025282
  93 │   146590  -0.000382631
  94 │   146591  -0.000223811
  95 │   146592  -0.000747794
  96 │   146595   0.000246047
  97 │   146596   0.0020031
  98 │   146598   0.00188509
  99 │   146602   0.000217185
 100 │   146603  -0.000203473
 101 │   146605  -0.000241021
 102 │   146607   0.000196611
 103 │   146609   0.000233826
 104 │   146617  -0.000211518
 105 │   158405   0.00161712
 106 │   158406   0.00183237
 107 │   158407   0.00176614
 108 │   174915   0.00238674
 109 │   174926   0.00243939
 110 │   174985   0.00206523
 111 │   174988   0.0020535
 112 │   175000   0.00158609
 113 │   175005   0.00144011
 114 │   175032   0.00223745
 115 │   175040   0.00221969
 116 │   175041   0.00232441
 117 │   175075   0.0023456
 118 │   175096   0.00238067
 119 │   225488   0.00152241
 120 │   225489   0.00145449
 121 │   225490   0.00160568
 122 │   225491   0.00155995
 123 │   227991   0.000830742
 124 │   227993   0.000835467
 125 │   227994   0.000817708
 126 │   228001   0.000830346
 127 │   228002   0.000852187
 128 │   228004   0.000854989
 129 │   228008   0.000787143
 130 │   228014   0.000841283
 131 │   242601  -0.00290579
 132 │   242602  -0.00286115
 133 │   242603  -0.00295282
 134 │   242607  -0.00287277
 135 │   242608   0.00160245
 136 │   266000   0.00116982
 137 │   266003   0.00121085
 138 │   266004   0.00124878
 139 │   266006   0.00115992
 140 │   266007   0.00270091
 141 │   266008   0.00251678
 142 │   266009   0.00258418
 143 │   266010   0.00255398
 144 │   266011   0.00274606
 145 │   266021   0.0016797
 146 │   266031   0.0019051
 147 │   301456  -0.00146267
 148 │   301459  -0.0021506
 149 │   301462  -0.00218349
 150 │   301463  -0.00222072
 151 │   301464  -0.00186405
 152 │   301466  -0.0022933
 153 │   301467  -0.0021603
 154 │   301468  -0.00210994
 155 │   301469  -0.00228906
 156 │   301470  -0.00227253
 157 │   301471  -0.0021364
 158 │   301472  -0.00134516
 159 │   301473  -0.00215065
 160 │   301475  -0.00154003
 161 │   301476  -0.00202303
 162 │   301479  -0.000492678
 163 │   301480  -0.00209087
 164 │   312049   0.00155478
 165 │   312051   0.00166876
 166 │   312052   0.00171892
 167 │   312055   0.00179624
 168 │   391780   0.000903104
 169 │   391795  -0.00109019
 170 │   394184   0.00224866
 171 │   401797  -0.00198128
 172 │   408087  -0.00148701
 173 │   408092   0.00157454
 174 │   411582   0.00254877
 175 │   432723  -0.00194596
 176 │   432731  -0.00199944
 177 │   432735  -0.00290358
 178 │   432745  -0.00181702
 179 │   432746  -0.00183214
 180 │   432747  -0.00191793
 181 │   432754  -0.0071475
 182 │   432757  -0.00551182
 183 │   432759  -0.00721029
 184 │   432760  -0.00229697
 185 │   432761  -0.00227405
 186 │   434519  -0.00219008
 187 │   434532  -0.00386389
 188 │   434545  -0.00408882
 189 │   434553  -0.00250213
 190 │   434560  -0.00311915
 191 │   434561  -0.00320607
 192 │   434573  -0.00356223
 193 │   434574  -0.00359489
 194 │   434594  -0.00303869
 195 │   438286  -0.00312064
 196 │   438303  -0.00187278
 197 │   438325  -0.00323957
 198 │   438334  -0.00141365
 199 │   438339  -0.00221175
 200 │   438345  -0.00408391
 201 │   438363  -0.00216731
 202 │   438366  -0.0020213
 203 │   438383  -0.0017143
 204 │   438391  -0.00224765
 205 │   438435  -0.0034813
 206 │   438439  -0.00270533
 207 │   438441  -0.00248105
 208 │   438442  -0.00332591
 209 │   438445  -0.00270829
 210 │   438448  -0.00555863
 211 │   438450  -0.00267095
 212 │   438455  -0.00627691
 213 │   438466  -0.00610768
 214 │   438467  -0.00385803
 215 │   438469  -0.0111678
 216 │   438470   0.00296056
 217 │   438476  -0.0047113
 218 │   438478  -0.00285422
 219 │   438479  -0.00818397
 220 │   438481  -0.00218432
 221 │   438483  -0.00567441
 222 │   438489  -0.00687133
 223 │   438492  -0.00719912
 224 │   438494  -0.00742041
 225 │   438499   0.0057345
 226 │   438500   0.00634177
 227 │   438505   0.00579579
 228 │   438507   0.00392616
 229 │   438509   0.00358778
 230 │   438511  -0.00635601
 231 │   438513   0.00293941
 232 │   438514   0.00297612
 233 │   438515  -0.00616784
 234 │   438516  -0.00323977
 235 │   438518  -0.012308
 236 │   438519   0.00665162
 237 │   438520   0.00825863
 238 │   438521   0.00333673
 239 │   438525  -0.0070769
 240 │   438526   0.00897144
 241 │   438527   0.00378361
 242 │   438530  -0.0171206
 243 │   438531   0.010055
 244 │   438533  -0.00641192
 245 │   438534  -0.0097684
 246 │   438536  -0.00261762
 247 │   438557  -0.00229847
 248 │   438562  -0.00222159
 249 │   438575  -0.00246098
 250 │   449595   0.00216702

Trait 12: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -4.75878e-7
   2 │        2   0.0155273
   3 │        3   0.000599099
   4 │        4  -0.000237143
   5 │        5   0.000738109
   6 │        6  -0.000914153
   7 │        7   0.00102905
   8 │        8  -0.00213521
   9 │        9  -0.00181762
  10 │       10   0.000791273
  11 │       11   0.000353266
  12 │       12  -0.000204445
  13 │       13   0.000414018
  14 │       14   0.00103066

Trait 13: IHT estimated 249 nonzero SNP predictors
249×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    18147  -0.00211039
   2 │    18165  -0.00286324
   3 │    18170  -0.00170969
   4 │    18171   0.00303996
   5 │    18174  -0.00314862
   6 │    18178   0.00274143
   7 │    18181  -0.00678484
   8 │    18182   0.00531592
   9 │    18183  -0.00683518
  10 │    18184   0.00677583
  11 │    18185   0.0068098
  12 │    18186   0.00683026
  13 │    18187  -0.00425289
  14 │    18188   0.00675922
  15 │    18189   0.0066971
  16 │    18191   0.00278666
  17 │    18197  -0.00284448
  18 │    18198  -0.00211531
  19 │    18212  -0.00204827
  20 │    18218  -0.00198455
  21 │    41945  -0.00112618
  22 │    41946   0.00234542
  23 │    41948  -0.000894174
  24 │    41950  -0.00301253
  25 │    41952  -0.00296128
  26 │    41954  -0.00286514
  27 │    41955  -0.00285782
  28 │    41956  -0.00284923
  29 │    41959   0.00132288
  30 │    41963  -0.00142281
  31 │    41964   0.0052726
  32 │    41965   0.00523756
  33 │    41966  -0.00279257
  34 │    41967  -0.00137194
  35 │    41968   0.00496849
  36 │    41971  -0.00269598
  37 │    41972  -0.00340344
  38 │    41974   0.0021619
  39 │    41975   0.00472476
  40 │    41977   0.00512764
  41 │    41978   0.00517903
  42 │    41979   0.00510955
  43 │    41985   0.00451972
  44 │    41986   0.00473215
  45 │    41988   0.00359999
  46 │    41989   0.00329921
  47 │    41990   0.00361036
  48 │    41992  -0.00463796
  49 │    41997  -0.00349597
  50 │    42925  -0.00207028
  51 │    42928  -0.00203959
  52 │    42933  -0.00452676
  53 │    42934  -0.00440269
  54 │    42935  -0.00433773
  55 │    42938  -0.00433543
  56 │    42941   0.00263308
  57 │    42942   0.00267778
  58 │    42943   0.0025941
  59 │    42945   0.00269765
  60 │    42947   0.00260761
  61 │    45816  -0.00209396
  62 │    45817  -0.00202158
  63 │    45821  -0.00202331
  64 │    45822  -0.00302884
  65 │    45823  -0.00298331
  66 │   146510  -0.000174865
  67 │   146512  -0.000174768
  68 │   146525   0.00221376
  69 │   146527   0.00243272
  70 │   146528  -0.000177873
  71 │   146529   0.00248841
  72 │   146532   0.00235726
  73 │   146537   0.00240491
  74 │   146538   0.00237831
  75 │   146539   0.00234453
  76 │   146544   0.000189779
  77 │   146546   0.0023249
  78 │   146549   0.00248107
  79 │   146552   0.00364555
  80 │   146554   0.00303724
  81 │   146557   0.00383552
  82 │   146560   0.00374013
  83 │   146561   0.00393378
  84 │   146564   0.0037153
  85 │   146566   0.00379766
  86 │   146569   0.00269292
  87 │   146576   0.00393125
  88 │   146579   0.0030634
  89 │   146583  -0.000543405
  90 │   146588  -0.000195236
  91 │   146596   0.000186107
  92 │   146598   0.000185689
  93 │   158405   0.00235336
  94 │   158406   0.00259566
  95 │   158407   0.00249654
  96 │   174881   0.000468949
  97 │   174882   0.000426033
  98 │   174915   0.00191934
  99 │   174926   0.00191328
 100 │   174933   0.00220778
 101 │   174936   0.0022154
 102 │   174985   0.00175877
 103 │   174988   0.00171647
 104 │   175000   0.00188995
 105 │   175005   0.00191299
 106 │   175032   0.00188365
 107 │   175040   0.00186029
 108 │   175041   0.00196601
 109 │   175075   0.00196111
 110 │   225490   0.0020495
 111 │   225491   0.00212805
 112 │   227991  -0.00153548
 113 │   227993  -0.00154119
 114 │   227994  -0.00158122
 115 │   228000  -0.00133518
 116 │   228001  -0.00154145
 117 │   228002  -0.00150843
 118 │   228003  -0.00127543
 119 │   228004  -0.00151518
 120 │   228005  -0.00128142
 121 │   228008  -0.00150499
 122 │   228014  -0.00144846
 123 │   242599   0.00274345
 124 │   242601  -0.00335706
 125 │   242602  -0.00377742
 126 │   242603  -0.00340466
 127 │   242605  -0.00132107
 128 │   242606  -0.00125355
 129 │   242607  -0.00373484
 130 │   242608   0.00237416
 131 │   242609  -0.00136393
 132 │   242612  -0.00135758
 133 │   266000   0.00100917
 134 │   266004   0.00102134
 135 │   266006   0.000991064
 136 │   266007   0.00255889
 137 │   266008   0.0023114
 138 │   266009   0.00233649
 139 │   266010   0.00235061
 140 │   266011   0.00267476
 141 │   309996  -0.00187405
 142 │   310000   0.00127915
 143 │   310003   0.00116075
 144 │   310006   0.00108535
 145 │   310010  -0.00321682
 146 │   310012   0.00187857
 147 │   310013   0.00175614
 148 │   310014  -0.00185102
 149 │   310015  -0.00218391
 150 │   310017   0.00148303
 151 │   310018  -0.00215434
 152 │   310019   0.00140372
 153 │   310020  -0.00162291
 154 │   310033  -0.00175904
 155 │   312049   0.00213165
 156 │   312051   0.00229448
 157 │   312052   0.00239998
 158 │   312055   0.00185005
 159 │   391781  -0.00232593
 160 │   391782  -0.00243962
 161 │   391783  -0.00247018
 162 │   391787  -0.00238597
 163 │   391789  -0.00263496
 164 │   391791  -0.00248324
 165 │   391794  -0.00223743
 166 │   394184   0.00249879
 167 │   401797  -0.0023265
 168 │   408087  -0.00355061
 169 │   432731  -0.00307587
 170 │   432735  -0.0024799
 171 │   432745  -0.00186753
 172 │   432746  -0.00192544
 173 │   432747  -0.00189843
 174 │   432754  -0.00671369
 175 │   432757  -0.00471883
 176 │   432759  -0.00687423
 177 │   432760  -0.00249609
 178 │   434519  -0.00285331
 179 │   434532  -0.00413143
 180 │   434545  -0.00439558
 181 │   434553  -0.00297309
 182 │   434560  -0.00363273
 183 │   434561  -0.00365703
 184 │   434573  -0.00391735
 185 │   434574  -0.00393912
 186 │   434594  -0.00267958
 187 │   438286  -0.00273108
 188 │   438303  -0.00210616
 189 │   438325  -0.00297171
 190 │   438334  -0.00195529
 191 │   438339  -0.00230128
 192 │   438345  -0.00338412
 193 │   438363  -0.00213425
 194 │   438366  -0.00185855
 195 │   438383  -0.00241924
 196 │   438391  -0.00203775
 197 │   438435  -0.00357965
 198 │   438439  -0.00293077
 199 │   438441  -0.00232472
 200 │   438442  -0.00342057
 201 │   438445  -0.00287625
 202 │   438448  -0.00479923
 203 │   438450  -0.00274408
 204 │   438455  -0.0052145
 205 │   438466  -0.00589195
 206 │   438467  -0.00323078
 207 │   438469  -0.00949625
 208 │   438470   0.00223272
 209 │   438476  -0.00433699
 210 │   438478  -0.00353408
 211 │   438479  -0.00763247
 212 │   438483  -0.00501794
 213 │   438489  -0.00616804
 214 │   438492  -0.00657022
 215 │   438494  -0.00662689
 216 │   438499   0.00536025
 217 │   438500   0.00541367
 218 │   438505   0.00504702
 219 │   438507   0.00351816
 220 │   438509   0.00292866
 221 │   438511  -0.00561124
 222 │   438513   0.00292589
 223 │   438514   0.00291073
 224 │   438515  -0.0055147
 225 │   438516  -0.00268733
 226 │   438518  -0.0103638
 227 │   438519   0.00630274
 228 │   438520   0.00805477
 229 │   438521   0.00335449
 230 │   438525  -0.00593635
 231 │   438526   0.00883346
 232 │   438527   0.00322532
 233 │   438530  -0.0144289
 234 │   438531   0.00935258
 235 │   438533  -0.00615011
 236 │   438534  -0.00816775
 237 │   438536  -0.00308732
 238 │   438557  -0.00237899
 239 │   438562  -0.00215105
 240 │   438575  -0.00225981
 241 │   449460   0.00198821
 242 │   449579   0.000701596
 243 │   449595   0.00170444
 244 │   450535   0.00374606
 245 │   450537  -0.00371372
 246 │   450538   0.00305223
 247 │   450539   0.000768667
 248 │   450540   0.00350413
 249 │   450546  -0.00106044

Trait 13: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -1.12356e-5
   2 │        2  -0.000562643
   3 │        3   0.00337255
   4 │        4   0.00268592
   5 │        5   0.0012285
   6 │        6  -0.0019699
   7 │        7   0.00141274
   8 │        8  -0.00129408
   9 │        9  -0.00161498
  10 │       10   3.3708e-5
  11 │       11   0.000113204
  12 │       12  -0.000322304
  13 │       13   0.00136042
  14 │       14  -0.00122175

Trait 14: IHT estimated 241 nonzero SNP predictors
241×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    10145  -0.00152287
   2 │    10164  -0.000666205
   3 │    10171   0.000669074
   4 │    18147  -0.00277035
   5 │    18165  -0.00355448
   6 │    18170  -0.00238076
   7 │    18171   0.00288403
   8 │    18172   0.00119878
   9 │    18173   0.00112621
  10 │    18174  -0.00143766
  11 │    18178   0.00275734
  12 │    18179  -0.000741703
  13 │    18180  -0.000711832
  14 │    18181  -0.00758489
  15 │    18182   0.00579764
  16 │    18183  -0.00760682
  17 │    18184   0.00728785
  18 │    18185   0.00754198
  19 │    18186   0.00759324
  20 │    18187  -0.00423822
  21 │    18188   0.00724324
  22 │    18189   0.00734319
  23 │    18191   0.00209842
  24 │    18195  -0.000747997
  25 │    18197  -0.0030949
  26 │    18198  -0.00193292
  27 │    18212  -0.0018439
  28 │    18218  -0.00232337
  29 │    41945  -0.00219875
  30 │    41946   0.00289181
  31 │    41948  -0.000996951
  32 │    41950  -0.00189816
  33 │    41952  -0.00352249
  34 │    41954  -0.003525
  35 │    41955  -0.00347922
  36 │    41956  -0.00351438
  37 │    41959   0.00235722
  38 │    41961  -0.00204391
  39 │    41963  -0.00235495
  40 │    41964   0.0052119
  41 │    41965   0.00524898
  42 │    41966  -0.00420727
  43 │    41967  -0.00232897
  44 │    41968   0.00469579
  45 │    41971  -0.00284092
  46 │    41972  -0.00276735
  47 │    41974   0.00306991
  48 │    41975   0.00467604
  49 │    41976  -0.00121278
  50 │    41977   0.00595852
  51 │    41978   0.00596677
  52 │    41979   0.00589863
  53 │    41985   0.00420351
  54 │    41986   0.00541159
  55 │    41988   0.0042763
  56 │    41989   0.00357181
  57 │    41990   0.00448113
  58 │    41992  -0.00541815
  59 │    41997  -0.00421964
  60 │    42925  -0.00146465
  61 │    42928  -0.0014459
  62 │    42933  -0.00368573
  63 │    42934  -0.00356055
  64 │    42935  -0.00349387
  65 │    42938  -0.00299159
  66 │    42941   0.00239401
  67 │    42942   0.00235658
  68 │    42943   0.00235657
  69 │    42945   0.00237737
  70 │    42947   0.00228311
  71 │    45816  -0.00234942
  72 │    45817  -0.00248069
  73 │    45821  -0.00231578
  74 │    45822  -0.00283623
  75 │    45823  -0.00271829
  76 │   146525   0.00190265
  77 │   146527   0.00207795
  78 │   146529   0.00172026
  79 │   146530   0.0013779
  80 │   146532   0.00210789
  81 │   146537   0.00175073
  82 │   146538   0.00170047
  83 │   146539   0.00173014
  84 │   146544   0.00170675
  85 │   146545   0.00164625
  86 │   146546   0.0017782
  87 │   146549   0.00292656
  88 │   146552   0.0036511
  89 │   146554   0.00369669
  90 │   146557   0.00385465
  91 │   146560   0.00382251
  92 │   146561   0.00403615
  93 │   146564   0.00385025
  94 │   146566   0.00408374
  95 │   146569   0.00221736
  96 │   146576   0.00346261
  97 │   146579   0.00294252
  98 │   146580  -0.0012695
  99 │   146588  -0.00197306
 100 │   146596   0.00176213
 101 │   158405   0.00338372
 102 │   158406   0.00357334
 103 │   158407   0.00347756
 104 │   169086  -0.000601188
 105 │   169137  -0.000594952
 106 │   174915   0.00108911
 107 │   174926   0.00111005
 108 │   174927   0.00107923
 109 │   174933   0.00109078
 110 │   174936   0.00107913
 111 │   174946   0.00100542
 112 │   174969   0.00112644
 113 │   174972   0.00101203
 114 │   174985   0.0015443
 115 │   174986   0.00111352
 116 │   174988   0.00153189
 117 │   175000   0.00239076
 118 │   175005   0.00239546
 119 │   175009   0.00106447
 120 │   175032   0.00150737
 121 │   175040   0.00151208
 122 │   175041   0.00156045
 123 │   175075   0.00121296
 124 │   175096   0.000906012
 125 │   242599   0.00260263
 126 │   242601  -0.00376912
 127 │   242602  -0.00359586
 128 │   242603  -0.00380432
 129 │   242605  -0.00212136
 130 │   242607  -0.00370103
 131 │   242608   0.00226259
 132 │   242609  -0.00217636
 133 │   242612  -0.0022899
 134 │   266007   0.00265923
 135 │   266008   0.00268411
 136 │   266009   0.00272352
 137 │   266010   0.00269856
 138 │   266011   0.00267193
 139 │   309996  -0.00187578
 140 │   310010  -0.00350917
 141 │   310012   0.00264447
 142 │   310013   0.00258661
 143 │   310014  -0.00188363
 144 │   310015  -0.00213236
 145 │   310017   0.00255407
 146 │   310018  -0.00206269
 147 │   310019   0.00248031
 148 │   310020  -0.00188937
 149 │   312049   0.00192794
 150 │   312051   0.00207901
 151 │   312052   0.00211866
 152 │   312055   0.00210976
 153 │   394184   0.0035394
 154 │   401797  -0.00247732
 155 │   408087  -0.00194836
 156 │   408092   0.00177533
 157 │   411582   0.000855935
 158 │   432723  -0.00127577
 159 │   432731  -0.00160576
 160 │   432735  -0.00270839
 161 │   432745  -0.00190233
 162 │   432746  -0.00179921
 163 │   432747  -0.00199376
 164 │   432754  -0.00687854
 165 │   432757  -0.00556197
 166 │   432759  -0.0070201
 167 │   432760  -0.00205971
 168 │   432761  -0.00167297
 169 │   432778   0.00100833
 170 │   434519  -0.00310136
 171 │   434532  -0.00446958
 172 │   434545  -0.00466773
 173 │   434553  -0.00283869
 174 │   434560  -0.00350259
 175 │   434561  -0.00352349
 176 │   434564  -0.00210725
 177 │   434573  -0.00400226
 178 │   434574  -0.00399587
 179 │   434594  -0.00347793
 180 │   438286  -0.00289974
 181 │   438303  -0.00140769
 182 │   438313  -0.000657796
 183 │   438325  -0.00302439
 184 │   438334  -0.00103861
 185 │   438337  -0.000870799
 186 │   438339  -0.00202234
 187 │   438345  -0.00355328
 188 │   438363  -0.00225653
 189 │   438366  -0.00194605
 190 │   438383  -0.0015181
 191 │   438384  -0.00151125
 192 │   438391  -0.00142433
 193 │   438435  -0.00347396
 194 │   438439  -0.00253939
 195 │   438441  -0.00214436
 196 │   438442  -0.00337657
 197 │   438445  -0.00318772
 198 │   438446   0.000675225
 199 │   438448  -0.0053823
 200 │   438450  -0.00200795
 201 │   438455  -0.00624166
 202 │   438466  -0.00618105
 203 │   438467  -0.00340807
 204 │   438469  -0.0114136
 205 │   438470   0.00306288
 206 │   438473  -0.00102298
 207 │   438476  -0.00450772
 208 │   438478  -0.00237882
 209 │   438479  -0.00841984
 210 │   438481  -0.00194718
 211 │   438483  -0.00545449
 212 │   438489  -0.00682493
 213 │   438492  -0.00712787
 214 │   438494  -0.00718532
 215 │   438499   0.00529746
 216 │   438500   0.00587149
 217 │   438505   0.00522737
 218 │   438507   0.00311587
 219 │   438509   0.00369328
 220 │   438511  -0.00713121
 221 │   438513   0.00297661
 222 │   438514   0.00297069
 223 │   438515  -0.0064512
 224 │   438516  -0.00285509
 225 │   438518  -0.0135997
 226 │   438519   0.00793523
 227 │   438520   0.00893441
 228 │   438521   0.00438785
 229 │   438525  -0.00694076
 230 │   438526   0.00991472
 231 │   438527   0.00444502
 232 │   438530  -0.0180254
 233 │   438531   0.0119348
 234 │   438533  -0.0065247
 235 │   438534  -0.0105183
 236 │   438536  -0.00271124
 237 │   438557  -0.00223192
 238 │   438562  -0.00204002
 239 │   438575  -0.00229167
 240 │   449460   0.00239461
 241 │   449595   0.00271886

Trait 14: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -2.26976e-5
   2 │        2   0.00227568
   3 │        3   0.00166643
   4 │        4   0.000681997
   5 │        5  -0.000910931
   6 │        6  -0.00053623
   7 │        7   0.000854885
   8 │        8  -0.0020937
   9 │        9  -0.00116577
  10 │       10   0.000701073
  11 │       11   0.0002943
  12 │       12  -0.000150661
  13 │       13   0.000443575
  14 │       14   0.000888923

Trait 15: IHT estimated 273 nonzero SNP predictors
273×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    18181  -0.00259023
   2 │    18183  -0.00265824
   3 │    18184   0.00251995
   4 │    18185   0.00264414
   5 │    18186   0.00264053
   6 │    18188   0.00250131
   7 │    18189   0.00260638
   8 │    22376  -0.00199207
   9 │    22383  -0.00169232
  10 │    41977   0.00231322
  11 │    41978   0.00230143
  12 │    41979   0.00231879
  13 │    41986   0.00200692
  14 │    41990   0.00177569
  15 │    41992  -0.00204059
  16 │    42916   0.000838561
  17 │    42919   0.00100342
  18 │    42925   0.00126672
  19 │    42927   0.000883948
  20 │    42928   0.00119734
  21 │    42931   0.000915652
  22 │    42932   0.000901801
  23 │    42933   0.00282235
  24 │    42934   0.00251476
  25 │    42935   0.00252451
  26 │    42938   0.0021536
  27 │    42941  -0.00157937
  28 │    42942  -0.00157861
  29 │    42943  -0.00156754
  30 │    42945  -0.00157978
  31 │    42947  -0.00154669
  32 │    61929   0.00231187
  33 │    61930   0.00242708
  34 │    61932   0.00266261
  35 │    70930  -0.00247102
  36 │    70931  -0.00256426
  37 │    70932  -0.00253293
  38 │    70933  -0.00255271
  39 │    70935  -0.00258248
  40 │    70938  -0.0023544
  41 │   144090  -0.00284388
  42 │   144091  -0.00257274
  43 │   178101  -0.00233779
  44 │   196927  -0.00233856
  45 │   196947  -0.00220569
  46 │   196957  -0.00207445
  47 │   208920  -0.00153907
  48 │   208924   0.00244942
  49 │   208925   0.00276699
  50 │   208926   0.00254909
  51 │   208927   0.00278996
  52 │   208928   0.00284785
  53 │   208934   0.00253787
  54 │   208939   0.00268058
  55 │   208941   0.00267434
  56 │   208944   0.00171239
  57 │   208947   0.00245216
  58 │   208948   0.0027755
  59 │   208949   0.00234586
  60 │   208951   0.00273595
  61 │   208952   0.00263253
  62 │   208954   0.00264359
  63 │   208956   0.00195683
  64 │   225261   0.00250954
  65 │   226098   0.00226036
  66 │   227982   0.00314829
  67 │   227987   0.00409229
  68 │   227988   0.00399978
  69 │   227989   0.00457475
  70 │   227990   0.00454239
  71 │   227991   0.00546916
  72 │   227992   0.00464065
  73 │   227993   0.00550666
  74 │   227994   0.00531735
  75 │   227995   0.00470347
  76 │   227996   0.00479065
  77 │   227997   0.00322037
  78 │   227999   0.00370812
  79 │   228000   0.00517174
  80 │   228001   0.00543512
  81 │   228002   0.00524924
  82 │   228003   0.00501835
  83 │   228004   0.00527272
  84 │   228005   0.00484493
  85 │   228006   0.00461164
  86 │   228007   0.00466179
  87 │   228008   0.00509603
  88 │   228013   0.00336196
  89 │   228014   0.00530834
  90 │   228019   0.0035474
  91 │   228020   0.00336307
  92 │   286075  -0.00185885
  93 │   286080  -0.0018859
  94 │   286084  -0.00184357
  95 │   300066   0.00290095
  96 │   300068   0.00289332
  97 │   300075   0.00288246
  98 │   301456  -0.00365376
  99 │   301457  -0.00252102
 100 │   301458   0.00177479
 101 │   301459  -0.00462257
 102 │   301462  -0.00462164
 103 │   301463  -0.00482479
 104 │   301464  -0.00430919
 105 │   301466  -0.00462973
 106 │   301467  -0.00474939
 107 │   301468  -0.00475667
 108 │   301469  -0.00453416
 109 │   301470  -0.0045948
 110 │   301471  -0.00479777
 111 │   301472  -0.0037437
 112 │   301473  -0.00475517
 113 │   301474  -0.00192711
 114 │   301475  -0.00367449
 115 │   301476  -0.00464156
 116 │   301479  -0.00290868
 117 │   301480  -0.00409471
 118 │   301481  -0.00224003
 119 │   301482  -0.00210646
 120 │   301485   0.00120573
 121 │   301487   0.00122026
 122 │   301488   0.00187173
 123 │   301489   0.00245746
 124 │   301492   0.00120497
 125 │   301493   0.00122086
 126 │   301494  -0.00128304
 127 │   309993   0.00163676
 128 │   309996   0.00260826
 129 │   310010   0.00309994
 130 │   310014   0.00233532
 131 │   310015   0.00262411
 132 │   310018   0.00265869
 133 │   310020   0.00221511
 134 │   310027   0.00163494
 135 │   310033   0.00217009
 136 │   310037   0.00203878
 137 │   310041   0.00205094
 138 │   310057   0.00226435
 139 │   310059   0.00214076
 140 │   310060   0.00197673
 141 │   310069   0.00191589
 142 │   310070   0.00191036
 143 │   310072   0.00194425
 144 │   310082  -0.00193027
 145 │   334232  -0.00274411
 146 │   334263   0.00320612
 147 │   334268  -0.00235964
 148 │   373913   0.00275872
 149 │   373926   0.00230121
 150 │   373927   0.00199837
 151 │   373928  -0.00353034
 152 │   373931  -0.00315015
 153 │   373937  -0.00346304
 154 │   373938   0.00388818
 155 │   373939  -0.00251482
 156 │   373948   0.011045
 157 │   373949  -0.00195879
 158 │   373950   0.0116613
 159 │   373951   0.0111935
 160 │   373952  -0.0113153
 161 │   373954  -0.0112349
 162 │   373955   0.00400193
 163 │   373956   0.0093248
 164 │   373957   0.00279115
 165 │   373962  -0.00776248
 166 │   373963   0.00244297
 167 │   373966   0.0065494
 168 │   373969  -0.00615574
 169 │   373973  -0.00549418
 170 │   373974  -0.00308803
 171 │   373976   0.0113159
 172 │   373978   0.00581201
 173 │   373979  -0.010978
 174 │   373981  -0.00323197
 175 │   373982  -0.00228191
 176 │   373987  -0.0083769
 177 │   373988  -0.0051883
 178 │   373990  -0.00201078
 179 │   373991  -0.00306454
 180 │   373994   0.00278229
 181 │   373995   0.00328435
 182 │   374006   0.00328692
 183 │   391744  -0.00215969
 184 │   391746   0.00230611
 185 │   391754   0.00262695
 186 │   391760   0.0032853
 187 │   391762   0.00290851
 188 │   391767   0.00288297
 189 │   391779   0.0084021
 190 │   391780   0.00757635
 191 │   391781   0.0124427
 192 │   391782   0.0126406
 193 │   391783   0.012653
 194 │   391784  -0.00430838
 195 │   391785  -0.00713252
 196 │   391787   0.0126498
 197 │   391788   0.00635264
 198 │   391789   0.0115356
 199 │   391791   0.0111602
 200 │   391792  -0.0105616
 201 │   391793   0.0102096
 202 │   391794   0.0109633
 203 │   391795  -0.0101749
 204 │   391796   0.00332248
 205 │   391798   0.00472938
 206 │   391799  -0.00486055
 207 │   391800  -0.00538055
 208 │   391801  -0.00431417
 209 │   391804  -0.00359562
 210 │   391820  -0.00251129
 211 │   407592  -0.00225971
 212 │   407600  -0.0023999
 213 │   438469  -0.00429608
 214 │   438479  -0.00303428
 215 │   438483  -0.00239864
 216 │   438518  -0.00433002
 217 │   438525  -0.00251726
 218 │   438530  -0.00657584
 219 │   438534  -0.00367063
 220 │   450456  -0.000885339
 221 │   450457  -0.000887675
 222 │   450470   0.000386155
 223 │   450473   0.000666995
 224 │   450479  -0.00352058
 225 │   450486  -0.000757701
 226 │   450487  -0.00210436
 227 │   450489  -0.00223827
 228 │   450491  -0.00226142
 229 │   450494  -0.000878554
 230 │   450496  -0.00134347
 231 │   450499  -0.000520331
 232 │   450501   0.00236545
 233 │   450502   0.00239752
 234 │   450504   0.000388667
 235 │   450505   0.000466232
 236 │   450506  -0.00327058
 237 │   450521   0.00225897
 238 │   450523   0.00230628
 239 │   450524   0.00301205
 240 │   450525   0.00264334
 241 │   450526   0.00298914
 242 │   450528   0.00235017
 243 │   450529  -0.00152488
 244 │   450530   0.00232172
 245 │   450531   0.00235871
 246 │   450532   0.00266126
 247 │   450533   0.00049376
 248 │   450535  -0.010209
 249 │   450536   0.00310399
 250 │   450537   0.0102742
 251 │   450538  -0.0107125
 252 │   450539  -0.007166
 253 │   450540  -0.0110046
 254 │   450541   0.00352848
 255 │   450543   0.00370892
 256 │   450544   0.00110899
 257 │   450545   0.00416236
 258 │   450546   0.00598938
 259 │   450550   0.00574645
 260 │   450551   0.00402063
 261 │   450553   0.0042188
 262 │   450555  -0.00496722
 263 │   450556  -0.00415515
 264 │   450559  -0.00494978
 265 │   450560  -0.00498716
 266 │   450562   0.00206439
 267 │   450570   0.00195989
 268 │   450577  -0.00352623
 269 │   450580  -0.0017192
 270 │   450581  -0.00201031
 271 │   450582  -0.00161713
 272 │   450583  -0.00147844
 273 │   450586  -0.00140629

Trait 15: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1   4.87212e-6
   2 │        2   0.0444579
   3 │        3   0.000380352
   4 │        4   0.000194246
   5 │        5  -0.00110025
   6 │        6   0.00122169
   7 │        7  -7.81245e-5
   8 │        8  -0.000624924
   9 │        9  -0.00149127
  10 │       10   0.000474329
  11 │       11  -0.000459003
  12 │       12   0.000195984
  13 │       13  -0.00325457
  14 │       14   0.0031164

Trait 16: IHT estimated 279 nonzero SNP predictors
279×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    31767   0.00275667
   2 │    31770   0.00252795
   3 │    33128   0.00253528
   4 │    33129   0.00255047
   5 │    33130   0.0025864
   6 │    33132   0.00275404
   7 │    41945   0.00300232
   8 │    41952   0.00303253
   9 │    41954   0.00297727
  10 │    41955   0.0029937
  11 │    41956   0.00295524
  12 │    41959  -0.00349052
  13 │    41963   0.00362684
  14 │    41967   0.00362881
  15 │    61929   0.000863794
  16 │    61930   0.000926528
  17 │    61932   0.00112686
  18 │    70920   0.000802463
  19 │    70928  -0.000832455
  20 │    70930  -0.00106415
  21 │    70931  -0.00112912
  22 │    70932  -0.00112304
  23 │    70933  -0.00110308
  24 │    70935  -0.00110394
  25 │    70938  -0.000917466
  26 │    70941  -0.000791764
  27 │   121556  -0.0017669
  28 │   121597  -0.00230429
  29 │   121617  -0.00170391
  30 │   144090  -0.00141218
  31 │   144091  -0.00117886
  32 │   178101  -0.00210407
  33 │   196927  -0.0018275
  34 │   196947  -0.0017144
  35 │   196957  -0.00172661
  36 │   208924   0.00143798
  37 │   208925   0.00173344
  38 │   208926   0.00220394
  39 │   208927   0.00181667
  40 │   208928   0.00172953
  41 │   208934   0.00216246
  42 │   208939   0.00175455
  43 │   208941   0.00177918
  44 │   208947   0.00223267
  45 │   208948   0.00195325
  46 │   208949   0.00225479
  47 │   208951   0.00209995
  48 │   208952   0.00225077
  49 │   208954   0.00184508
  50 │   225488   0.00392754
  51 │   225489   0.00387419
  52 │   227975  -0.00236733
  53 │   227981  -0.00209205
  54 │   227982   0.00260494
  55 │   227983   0.00226827
  56 │   227987   0.00421587
  57 │   227988   0.00405809
  58 │   227989   0.005434
  59 │   227990   0.00550744
  60 │   227991   0.00588317
  61 │   227992   0.00563576
  62 │   227993   0.00588762
  63 │   227994   0.00561063
  64 │   227995   0.00588241
  65 │   227996   0.00590553
  66 │   227997   0.00289911
  67 │   227999   0.00461476
  68 │   228000   0.00568596
  69 │   228001   0.00578407
  70 │   228002   0.00559338
  71 │   228003   0.0054279
  72 │   228004   0.0056518
  73 │   228005   0.00528128
  74 │   228006   0.005699
  75 │   228007   0.00571649
  76 │   228008   0.00555222
  77 │   228009   0.00181695
  78 │   228011   0.00227219
  79 │   228013   0.00269507
  80 │   228014   0.00568039
  81 │   228019   0.00295305
  82 │   228020   0.0030549
  83 │   228031   0.00130023
  84 │   240940   0.00252822
  85 │   240944   0.00255569
  86 │   240947   0.00254837
  87 │   250491   0.00168709
  88 │   250494   0.00143934
  89 │   286075  -0.00328299
  90 │   286080  -0.00335892
  91 │   286084  -0.00328675
  92 │   300051   0.00105744
  93 │   300057   0.00044979
  94 │   300058   0.00105425
  95 │   300064  -0.000686785
  96 │   300066   0.00130351
  97 │   300068   0.00126409
  98 │   300075   0.00125086
  99 │   300076   0.000721307
 100 │   300078   0.000562479
 101 │   300084   0.00148103
 102 │   300091  -0.00135409
 103 │   300100  -0.00106504
 104 │   300109  -0.0014118
 105 │   300112  -0.00153026
 106 │   300114  -0.00107516
 107 │   300116  -0.0014886
 108 │   300124  -0.00151883
 109 │   300128  -0.00152688
 110 │   301456  -0.00210554
 111 │   301457  -0.00127377
 112 │   301458   0.00123015
 113 │   301459  -0.00248915
 114 │   301462  -0.00262153
 115 │   301463  -0.002592
 116 │   301464  -0.00231109
 117 │   301466  -0.00253224
 118 │   301467  -0.0026082
 119 │   301468  -0.00255412
 120 │   301469  -0.0025501
 121 │   301470  -0.00245056
 122 │   301471  -0.00262193
 123 │   301472  -0.00287522
 124 │   301473  -0.00266235
 125 │   301474  -0.000400237
 126 │   301475  -0.00271322
 127 │   301476  -0.0027235
 128 │   301479  -0.00127535
 129 │   301480  -0.00244035
 130 │   301481  -0.00151888
 131 │   301482  -0.00166628
 132 │   301488   0.000901408
 133 │   301489   0.00188472
 134 │   301492   0.000829504
 135 │   301493   0.00081161
 136 │   309993   0.00205015
 137 │   309996   0.00202926
 138 │   310010   0.00383245
 139 │   310014   0.00185375
 140 │   310015   0.00216292
 141 │   310018   0.0021592
 142 │   310020   0.00193222
 143 │   310033   0.00200434
 144 │   310037   0.00121582
 145 │   310039   0.00302619
 146 │   310041   0.00106387
 147 │   310057   0.00108329
 148 │   310059   0.000985352
 149 │   310060   0.00132941
 150 │   310069   0.000819369
 151 │   310070   0.000845877
 152 │   310072   0.000766262
 153 │   310082  -0.000691209
 154 │   333936   0.00176022
 155 │   334232  -0.00252843
 156 │   334237  -0.00240297
 157 │   334238  -0.00238179
 158 │   334259   0.0027645
 159 │   334263   0.00277194
 160 │   334268  -0.00196481
 161 │   373913   0.00192571
 162 │   373926   0.00212005
 163 │   373928  -0.00317201
 164 │   373931  -0.0026665
 165 │   373937  -0.00247212
 166 │   373938   0.00363807
 167 │   373939  -0.00223658
 168 │   373948   0.0115319
 169 │   373950   0.012028
 170 │   373951   0.0116345
 171 │   373952  -0.0118402
 172 │   373954  -0.0117524
 173 │   373955   0.00399198
 174 │   373956   0.00990221
 175 │   373957   0.00223856
 176 │   373958   0.00147409
 177 │   373962  -0.00806028
 178 │   373963   0.00211894
 179 │   373966   0.0064337
 180 │   373969  -0.00587424
 181 │   373973  -0.00595668
 182 │   373974  -0.00314786
 183 │   373976   0.0116867
 184 │   373978   0.00565504
 185 │   373979  -0.0113426
 186 │   373981  -0.00346509
 187 │   373982  -0.00199094
 188 │   373987  -0.00841942
 189 │   373988  -0.00514063
 190 │   373991  -0.00280847
 191 │   373994   0.0017968
 192 │   373995   0.0030228
 193 │   373997  -0.00141047
 194 │   374006   0.00241173
 195 │   391735  -0.00170709
 196 │   391744  -0.00280349
 197 │   391746   0.00314416
 198 │   391750   0.00189978
 199 │   391754   0.00349529
 200 │   391757   0.00288571
 201 │   391760   0.00370684
 202 │   391762   0.00347191
 203 │   391767   0.00200895
 204 │   391768   0.00200221
 205 │   391771  -0.000983759
 206 │   391772  -0.000987832
 207 │   391777  -0.00246477
 208 │   391779   0.0100382
 209 │   391780   0.0101602
 210 │   391781   0.0140284
 211 │   391782   0.0141883
 212 │   391783   0.0142089
 213 │   391784  -0.00397608
 214 │   391785  -0.00915634
 215 │   391787   0.0140803
 216 │   391788   0.00608872
 217 │   391789   0.0136666
 218 │   391791   0.013403
 219 │   391792  -0.0126972
 220 │   391793   0.0127768
 221 │   391794   0.0132272
 222 │   391795  -0.0129933
 223 │   391796   0.00517261
 224 │   391798   0.00568802
 225 │   391799  -0.00822954
 226 │   391800  -0.00709015
 227 │   391801  -0.00753011
 228 │   391804  -0.0039044
 229 │   391809   0.00217438
 230 │   391820  -0.00184062
 231 │   393668  -0.00146398
 232 │   393704  -0.00169026
 233 │   396633   0.00145864
 234 │   407582  -0.00335567
 235 │   407592  -0.00396812
 236 │   407600  -0.00422434
 237 │   423242   0.00274059
 238 │   423244   0.0035499
 239 │   423245   0.0036285
 240 │   423246   0.00285501
 241 │   423247   0.00350107
 242 │   423250   0.00350185
 243 │   423255   0.00314478
 244 │   438535   0.00362795
 245 │   438542   0.00349329
 246 │   450252  -0.00311967
 247 │   450479  -0.00225329
 248 │   450489  -0.00167313
 249 │   450491  -0.00259313
 250 │   450496  -0.00251177
 251 │   450506  -0.00338431
 252 │   450521   0.0021092
 253 │   450523   0.00214284
 254 │   450524   0.00227924
 255 │   450525   0.00230045
 256 │   450526   0.00234405
 257 │   450528   0.00184103
 258 │   450530   0.00166106
 259 │   450531   0.00195862
 260 │   450532   0.00184398
 261 │   450535  -0.00912006
 262 │   450536   0.00259921
 263 │   450537   0.00914317
 264 │   450538  -0.00940617
 265 │   450539  -0.00614096
 266 │   450540  -0.0096828
 267 │   450541   0.00260295
 268 │   450543   0.00367765
 269 │   450545   0.00377194
 270 │   450546   0.00488543
 271 │   450550   0.00499669
 272 │   450551   0.003873
 273 │   450553   0.00344254
 274 │   450555  -0.00313091
 275 │   450556  -0.00346831
 276 │   450559  -0.00320716
 277 │   450560  -0.00318273
 278 │   450570   0.00167569
 279 │   450577  -0.00291706

Trait 16: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -3.86688e-6
   2 │        2   0.0528515
   3 │        3   0.00470772
   4 │        4   0.00455212
   5 │        5   0.00101648
   6 │        6   0.000947895
   7 │        7   0.000648875
   8 │        8  -0.000150694
   9 │        9  -0.000545551
  10 │       10   0.000773634
  11 │       11   9.7489e-5
  12 │       12  -0.000303566
  13 │       13  -0.00163765
  14 │       14   0.00178061

Trait 17: IHT estimated 221 nonzero SNP predictors
221×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.00372443
   2 │    11578  -0.0037195
   3 │    11579   0.00374973
   4 │    11580   0.00363591
   5 │    11581  -0.00377233
   6 │    11590   0.00361629
   7 │    11592  -0.00153647
   8 │    18181   0.00182013
   9 │    18183   0.00185863
  10 │    18184  -0.00175474
  11 │    18185  -0.00185283
  12 │    18186  -0.00189378
  13 │    18187   0.000944351
  14 │    18188  -0.00187273
  15 │    18189  -0.00200998
  16 │    20416   0.000868771
  17 │    20444   0.000943284
  18 │    20445   0.000860809
  19 │    31767   0.00232643
  20 │    31770   0.00217123
  21 │    33121   0.00157365
  22 │    33122   0.00174658
  23 │    33128   0.00282227
  24 │    33129   0.00286685
  25 │    33130   0.00289134
  26 │    33132   0.00303961
  27 │    33136  -0.00176309
  28 │    41945   0.00279914
  29 │    41952   0.00355673
  30 │    41954   0.00354092
  31 │    41955   0.00353645
  32 │    41956   0.00354689
  33 │    41959  -0.00274077
  34 │    41963   0.00274256
  35 │    41964  -0.00303963
  36 │    41965  -0.00297188
  37 │    41967   0.00276431
  38 │    41972   0.000385213
  39 │    41975  -0.00256988
  40 │    42933  -0.00301888
  41 │    42934  -0.00246353
  42 │    42935  -0.00245567
  43 │    42938  -0.00259061
  44 │    42941   0.00113175
  45 │    42942   0.00111644
  46 │    42943   0.00112447
  47 │    42945   0.00113087
  48 │    42947   0.00115114
  49 │   121597  -0.00352074
  50 │   170790  -0.0010028
  51 │   171544  -0.000815531
  52 │   171553  -0.000810461
  53 │   172964  -0.000848572
  54 │   173033  -0.000569147
  55 │   173481  -0.000483253
  56 │   173640  -0.00110589
  57 │   173642  -0.00050837
  58 │   173657  -0.000474239
  59 │   173658  -0.000535044
  60 │   173683  -0.000671165
  61 │   225486   0.00363605
  62 │   225487   0.00369001
  63 │   225488   0.00414085
  64 │   225489   0.00413085
  65 │   225490   0.00385044
  66 │   225491   0.00381097
  67 │   225497  -0.00319544
  68 │   225506  -0.00306196
  69 │   227975  -0.00202025
  70 │   227981  -0.00267093
  71 │   227983   0.00219999
  72 │   227987   0.00362118
  73 │   227988   0.0034286
  74 │   227989   0.00419117
  75 │   227990   0.00418879
  76 │   227991   0.00464316
  77 │   227992   0.0043391
  78 │   227993   0.00464669
  79 │   227994   0.00439603
  80 │   227995   0.00469513
  81 │   227996   0.00470296
  82 │   227997   0.0031293
  83 │   227999   0.0036618
  84 │   228000   0.00448838
  85 │   228001   0.00453784
  86 │   228002   0.00449347
  87 │   228003   0.00430213
  88 │   228004   0.00456203
  89 │   228005   0.00406572
  90 │   228006   0.00461256
  91 │   228007   0.00464504
  92 │   228008   0.00439044
  93 │   228011   0.00224927
  94 │   228013   0.00295888
  95 │   228014   0.00421178
  96 │   228019   0.00220741
  97 │   228020   0.00274207
  98 │   240938   0.00156145
  99 │   240940   0.00153031
 100 │   240944   0.00159112
 101 │   240947   0.00158077
 102 │   240950   0.00154063
 103 │   286075  -0.00206572
 104 │   286080  -0.00210927
 105 │   286084  -0.00206292
 106 │   300068   0.0032946
 107 │   300084   0.00170175
 108 │   300091  -0.00162089
 109 │   300109  -0.0015328
 110 │   300112  -0.00155544
 111 │   300116  -0.0015492
 112 │   300124  -0.00155476
 113 │   300128  -0.00157988
 114 │   303688  -0.00220085
 115 │   303690  -0.00231993
 116 │   303691  -0.00278176
 117 │   303694  -0.00235357
 118 │   303697  -0.00232609
 119 │   310035   0.00172321
 120 │   310039   0.0035249
 121 │   310042  -0.00430295
 122 │   310044  -0.00433107
 123 │   310047   0.00291285
 124 │   310053   0.00043713
 125 │   310056   0.00367002
 126 │   310062   0.00374245
 127 │   310064   0.00190256
 128 │   334238  -0.0031392
 129 │   334259   0.00253223
 130 │   373948   0.00706645
 131 │   373950   0.00732264
 132 │   373951   0.00710635
 133 │   373952  -0.00690768
 134 │   373954  -0.00682256
 135 │   373955   0.00285975
 136 │   373956   0.00554433
 137 │   373962  -0.00501317
 138 │   373966   0.00352246
 139 │   373969  -0.00345021
 140 │   373973  -0.00317863
 141 │   373976   0.00799181
 142 │   373978   0.00412364
 143 │   373979  -0.00775648
 144 │   373987  -0.00610568
 145 │   373988  -0.00297561
 146 │   391744  -0.00211515
 147 │   391746   0.00185564
 148 │   391754   0.00208811
 149 │   391757   0.00199832
 150 │   391760   0.00327334
 151 │   391762   0.00211583
 152 │   391768   0.00279839
 153 │   391777  -0.00282097
 154 │   391779   0.00694509
 155 │   391780   0.00669164
 156 │   391781   0.00985978
 157 │   391782   0.0100117
 158 │   391783   0.00997603
 159 │   391784  -0.00304324
 160 │   391785  -0.00627908
 161 │   391787   0.0100274
 162 │   391788   0.00450503
 163 │   391789   0.00953685
 164 │   391791   0.00918001
 165 │   391792  -0.00900267
 166 │   391793   0.00903008
 167 │   391794   0.00880617
 168 │   391795  -0.00951134
 169 │   391796   0.00337729
 170 │   391798   0.00368332
 171 │   391799  -0.00564639
 172 │   391800  -0.00532963
 173 │   391801  -0.00488972
 174 │   391804  -0.00283019
 175 │   407582  -0.00253157
 176 │   407592  -0.00273149
 177 │   407600  -0.00274739
 178 │   423234   0.00276797
 179 │   423236   0.00174447
 180 │   423237   0.00245533
 181 │   423239   0.000970196
 182 │   423242   0.00263143
 183 │   423244   0.00553973
 184 │   423245   0.00554585
 185 │   423246   0.0048473
 186 │   423247   0.00558876
 187 │   423250   0.00556185
 188 │   423255   0.00387319
 189 │   423259   0.00243166
 190 │   423260   0.00199066
 191 │   423262   0.000436827
 192 │   423266   0.00130247
 193 │   423268   0.00132722
 194 │   423293   0.00184107
 195 │   423294   0.00167724
 196 │   432754   0.00187092
 197 │   432759   0.00198011
 198 │   432795  -0.00287838
 199 │   432796  -0.0017055
 200 │   432797  -0.00204169
 201 │   432801  -0.00293563
 202 │   438455   0.00233214
 203 │   438466   0.00154931
 204 │   438469   0.0027549
 205 │   438479   0.00189751
 206 │   438499  -0.00125146
 207 │   438500  -0.00142293
 208 │   438505  -0.000919122
 209 │   438518   0.00287296
 210 │   438519  -0.00170062
 211 │   438520  -0.00261958
 212 │   438525   0.00181662
 213 │   438526  -0.00446476
 214 │   438530   0.0029172
 215 │   438531  -0.00453159
 216 │   438535   0.00306341
 217 │   438536   0.00243627
 218 │   438537   0.000792307
 219 │   438541   0.000467366
 220 │   438542   0.00256043
 221 │   450252  -0.00287448

Trait 17: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1  -1.72688e-5
   2 │        2   0.0396341
   3 │        3   0.00499244
   4 │        4   0.00465069
   5 │        5   0.00130891
   6 │        6  -0.00175825
   7 │        7   0.000745011
   8 │        8   0.00017887
   9 │        9   0.00132243
  10 │       10  -0.000661045
  11 │       11   0.0015115
  12 │       12  -0.000228132
  13 │       13   0.000522613
  14 │       14  -0.00265682

Trait 18: IHT estimated 221 nonzero SNP predictors
221×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │    11577  -0.00444054
   2 │    11578  -0.00451507
   3 │    11579   0.00452605
   4 │    11580   0.0044351
   5 │    11581  -0.00434865
   6 │    11584  -0.00209962
   7 │    11590   0.0042223
   8 │    11592  -0.00323683
   9 │    20416   0.00239497
  10 │    20444   0.00266144
  11 │    20445   0.00264407
  12 │    22362   0.000746334
  13 │    22363   0.000833534
  14 │    22376   0.00113763
  15 │    22383   0.00102196
  16 │    42900   0.000637428
  17 │    42903   0.000860985
  18 │    42905  -0.000487076
  19 │    42908   0.000959057
  20 │    42913  -0.000937909
  21 │    42916  -0.00146295
  22 │    42919  -0.00167099
  23 │    42921  -0.00159386
  24 │    42925  -0.00247592
  25 │    42927  -0.00168468
  26 │    42928  -0.00244424
  27 │    42930  -0.00118711
  28 │    42931  -0.00180664
  29 │    42932  -0.00173017
  30 │    42933  -0.00569931
  31 │    42934  -0.00528655
  32 │    42935  -0.00530041
  33 │    42936  -0.00342186
  34 │    42938  -0.00436016
  35 │    42939   0.000963625
  36 │    42940   0.000949172
  37 │    42941   0.00343131
  38 │    42942   0.00340653
  39 │    42943   0.00341629
  40 │    42944  -0.00233467
  41 │    42945   0.00337316
  42 │    42946  -0.00230888
  43 │    42947   0.00314876
  44 │    42948   0.00100801
  45 │    42954   0.00089225
  46 │    42956  -0.00217532
  47 │    42959   0.00115942
  48 │    42963   0.00154094
  49 │    42970   0.000689145
  50 │    42975   0.000701005
  51 │    42977   0.00107434
  52 │    42980   0.000730196
  53 │   172632   0.000677523
  54 │   172749  -0.000685363
  55 │   172788  -0.000546077
  56 │   172964  -0.000743081
  57 │   173033  -0.000864969
  58 │   173137   0.00062754
  59 │   173141   0.000616935
  60 │   173144   0.000666888
  61 │   173163   0.000881023
  62 │   173169   0.000879555
  63 │   173356  -0.000941288
  64 │   173361  -0.000891724
  65 │   173406   0.00118433
  66 │   173481  -0.000851025
  67 │   173640  -0.00104521
  68 │   173642  -0.0007967
  69 │   173656  -0.000898038
  70 │   173657  -0.000754452
  71 │   173658  -0.000763875
  72 │   174250  -0.000703108
  73 │   174672   0.000545139
  74 │   174865   0.000406888
  75 │   174867   0.000407913
  76 │   174880   0.000542524
  77 │   174887   0.000855148
  78 │   174908   0.000900693
  79 │   174987   0.000830898
  80 │   175062   0.000782011
  81 │   175111   0.00068393
  82 │   208920   0.000874202
  83 │   208924  -0.00144892
  84 │   208925  -0.00177112
  85 │   208926  -0.00180489
  86 │   208927  -0.0017741
  87 │   208928  -0.00176644
  88 │   208934  -0.00184676
  89 │   208939  -0.00193136
  90 │   208941  -0.00195507
  91 │   208944  -0.00223217
  92 │   208947  -0.00201465
  93 │   208948  -0.0020246
  94 │   208949  -0.00196101
  95 │   208951  -0.00208245
  96 │   208952  -0.00190656
  97 │   208954  -0.00181855
  98 │   208956  -0.00161938
  99 │   225261  -0.000861838
 100 │   225262  -0.000876372
 101 │   225334  -0.00101061
 102 │   225486   0.00378813
 103 │   225487   0.00377529
 104 │   225488   0.00428447
 105 │   225489   0.00425327
 106 │   225490   0.00429034
 107 │   225491   0.00435675
 108 │   225497  -0.00372383
 109 │   225506  -0.00251809
 110 │   225848   0.00116828
 111 │   226061  -0.0010454
 112 │   226074  -0.000713494
 113 │   226078   0.000423373
 114 │   226079  -0.00068984
 115 │   226082  -0.000609671
 116 │   226119  -0.00114876
 117 │   242601  -0.00251535
 118 │   242602  -0.00240312
 119 │   242603  -0.00253696
 120 │   242605  -0.00111269
 121 │   242606  -0.00113139
 122 │   242607  -0.00241078
 123 │   242609  -0.00108831
 124 │   242612  -0.00171067
 125 │   266007   0.00333721
 126 │   266011   0.00340431
 127 │   303688  -0.00243858
 128 │   303690  -0.00287803
 129 │   303691  -0.00307441
 130 │   303694  -0.00290294
 131 │   303697  -0.00285679
 132 │   309993  -0.00127324
 133 │   309996  -0.00217421
 134 │   309998   0.00126199
 135 │   310000   0.0014396
 136 │   310003   0.00143173
 137 │   310006   0.00148694
 138 │   310010  -0.00257725
 139 │   310012   0.00132763
 140 │   310013   0.00129523
 141 │   310014  -0.00214602
 142 │   310015  -0.00217713
 143 │   310016  -0.00117309
 144 │   310017   0.00139833
 145 │   310018  -0.00224092
 146 │   310019   0.00142824
 147 │   310020  -0.00223775
 148 │   310026  -0.00207044
 149 │   310027  -0.00228639
 150 │   310033  -0.00197155
 151 │   310035   0.00201085
 152 │   310037  -0.00246877
 153 │   310039   0.00374323
 154 │   310041  -0.0020294
 155 │   310042  -0.00420881
 156 │   310044  -0.00418886
 157 │   310047   0.00272568
 158 │   310056   0.0031391
 159 │   310059  -0.00154774
 160 │   310062   0.0031793
 161 │   310064   0.0019334
 162 │   310073  -0.00177606
 163 │   310081   0.00189967
 164 │   391795  -0.00366973
 165 │   401797  -0.0025129
 166 │   423234   0.00225981
 167 │   423244   0.00485092
 168 │   423245   0.00469713
 169 │   423246   0.00419742
 170 │   423247   0.00489023
 171 │   423250   0.00485627
 172 │   423255   0.00269892
 173 │   423259   0.00308066
 174 │   432795  -0.00367287
 175 │   432801  -0.00367049
 176 │   434532  -0.00231334
 177 │   434545  -0.00257319
 178 │   434553  -0.0017753
 179 │   434560  -0.00166037
 180 │   434561  -0.00170232
 181 │   434573  -0.0018765
 182 │   434574  -0.00176855
 183 │   438530   0.00200584
 184 │   438535   0.00293167
 185 │   450473  -0.000567839
 186 │   450479   0.00251237
 187 │   450486   0.000628615
 188 │   450489   0.00103483
 189 │   450491   0.00117538
 190 │   450496   0.000880414
 191 │   450506   0.00253961
 192 │   450513  -0.0018724
 193 │   450521  -0.00129555
 194 │   450523  -0.00132718
 195 │   450524  -0.00199759
 196 │   450525  -0.00130721
 197 │   450526  -0.00161418
 198 │   450528  -0.00128258
 199 │   450529   0.00193939
 200 │   450530  -0.00122133
 201 │   450531  -0.00147009
 202 │   450532  -0.00147885
 203 │   450535   0.00992632
 204 │   450536  -0.00291381
 205 │   450537  -0.0101146
 206 │   450538   0.0103635
 207 │   450539   0.00650847
 208 │   450540   0.0104008
 209 │   450541  -0.00351728
 210 │   450543  -0.00306109
 211 │   450545  -0.00400967
 212 │   450546  -0.00588474
 213 │   450550  -0.00544813
 214 │   450551  -0.00363136
 215 │   450553  -0.00269968
 216 │   450555   0.00220643
 217 │   450556   0.00254166
 218 │   450559   0.0022058
 219 │   450560   0.00219174
 220 │   450562  -0.0012762
 221 │   450577   0.00209968

Trait 18: IHT estimated 14 non-genetic predictors
14×2 DataFrame
 Row │ Position  Estimated_β
     │ Int64     Float64
─────┼────────────────────────
   1 │        1   1.37809e-5
   2 │        2   0.00909258
   3 │        3   0.00480434
   4 │        4   0.00419261
   5 │        5   0.000229313
   6 │        6   7.69338e-5
   7 │        7  -2.11145e-5
   8 │        8  -0.000300718
   9 │        9   0.00108274
  10 │       10   0.000699908
  11 │       11  -8.23161e-5
  12 │       12   0.000395485
  13 │       13   0.00401412
  14 │       14  -0.00196806
