| tags: [ Gaston Genomic Data GWAS Heritability ] categories: [Coding ]
Generating beta-values for significant SNPs
Introduction
The heritability values obtained from the previous GWAS using lmm and lrt appear to be artificially inflated. Therefore, beta values may be a better indication of SNP effect, which can be obtained by using the wald test, instead of lrt.
Methods and Results
Load packages
require(magicfor)
require(magrittr)
require(dplyr)
require(gaston)
require(qqman)Load data
nies_heritable_pheno240918 <- read.csv('C:/Users/Martha/Documents/Honours/Project/honours.project/Data/nies_heritable_pheno240918.csv', header = TRUE)
nies_covar <- read.csv('C:/Users/Martha/Documents/Honours/Project/honours.project/Data/nies_covar.csv', header = T)
head(nies_covar)## UUID Sex Age
## 1 219960 1 53
## 2 313180 1 55
## 3 320511 2 60
## 4 400011 1 23
## 5 400013 1 50
## 6 316131 2 77merged_nies_210818 <- read.bed.matrix("C:/Users/Martha/Documents/Honours/Project/honours.project/Data/merged_nies/merged_nies_geno_210818.bed")## Reading C:/Users/Martha/Documents/Honours/Project/honours.project/Data/merged_nies/merged_nies_geno_210818.fam
## Reading C:/Users/Martha/Documents/Honours/Project/honours.project/Data/merged_nies/merged_nies_geno_210818.bim
## Reading C:/Users/Martha/Documents/Honours/Project/honours.project/Data/merged_nies/merged_nies_geno_210818.bed
## ped stats and snps stats have been set.
## 'p' has been set.
## 'mu' and 'sigma' have been set.merged_nies_GRM <- GRM(merged_nies_210818)
merged_nies_eiK <- eigen(merged_nies_GRM)
merged_nies_eiK$values[ merged_nies_eiK$values < 0] <- 0
merged_nies_PC <- sweep(merged_nies_eiK$vectors, 2, sqrt(merged_nies_eiK$values), "*")1. L K-value H
lKvalH_wald_gwas <- association.test(merged_nies_210818, nies_heritable_pheno240918$L.K.value.H, X = nies_covar, method="lm", test = "wald", response = "quantitative", K = merged_nies_GRM, eigenK = merged_nies_eiK, p = 2)## Warning in trans.X(X, mean.y = mean(Y)): An intercept column was added to
## the covariate matrix XlKvalH_wald_gwas <- na.omit(lKvalH_wald_gwas)
l_kvalH_wfiltered <- lKvalH_wald_gwas %>% filter(-log10(p)>1) %>% filter(freqA2 < 0.99)
l_kvalH_wmeff <- l_kvalH_wfiltered %>% filter(p < 1.84e-7)
l_kvalH_wsig <- do.call(rbind, lapply(split(l_kvalH_wmeff,l_kvalH_wmeff$chr), function(x) {return(x[which.min(x$p),])}))
l_kvalH_wres <- NULL
for (i in l_kvalH_wsig$id) {
snpID <- i
snpCHR <- l_kvalH_wfiltered[l_kvalH_wfiltered$id == snpID,]$chr
snpPOS <- l_kvalH_wfiltered[l_kvalH_wfiltered$id ==snpID,]$pos
sig.peak <- l_kvalH_wfiltered %>%
filter(chr == snpCHR) %>%
filter(pos > snpPOS - 50000) %>%
filter(pos < snpPOS + 50000) %>%
filter(p < 1e-5)
l_kvalH_wres <- rbind(l_kvalH_wres, sig.peak)
}
write.csv(l_kvalH_wres, 'C:/Users/Martha/Documents/Honours/Project/honours.project/Data/gwas_filter_covar/l_kvalH_wald_res.csv')
l_kvalH_wres## chr pos id A1 A2 freqA2 beta sd
## 1 2 176830012 rs72940750 C T 0.9898551 3.750520 0.5949583
## 2 2 176831387 rs7576095 A G 0.9898551 3.750520 0.5949583
## 3 2 176832679 rs6758571 G A 0.9898551 3.750520 0.5949583
## 4 2 176833429 rs139727961 G A 0.9898551 3.750520 0.5949583
## 5 2 176839936 rs72940766 A T 0.9898551 3.750520 0.5949583
## 6 2 176840625 rs72940776 T C 0.9898551 3.750520 0.5949583
## 7 2 176840683 rs72940781 C G 0.9898551 3.750520 0.5949583
## 8 2 176841189 rs6715723 T A 0.9898551 3.750520 0.5949583
## 9 3 77739700 rs1163757 A G 0.9869565 3.208147 0.5285691
## 10 5 115982105 rs114096393 T A 0.9898551 3.273656 0.6035919
## 11 5 115982651 rs79849322 C G 0.9898551 3.273656 0.6035919
## 12 5 116005046 rs186488524 A T 0.9898551 3.273656 0.6035919
## 13 5 116019083 rs74459592 G A 0.9884058 2.923871 0.5672395
## 14 5 116019686 rs73783057 T C 0.9884058 2.923871 0.5672395
## 15 5 116021083 rs74809125 A G 0.9898551 3.273656 0.6035919
## 16 5 116021134 rs73783063 C T 0.9884058 2.923871 0.5672395
## 17 5 116021188 rs73783064 C T 0.9884058 2.923871 0.5672395
## 18 5 116021961 rs61626272 T G 0.9884058 2.923871 0.5672395
## 19 5 116022620 rs56745470 G A 0.9884058 2.923871 0.5672395
## 20 5 116022897 rs17138683 G A 0.9884058 2.923871 0.5672395
## 21 5 116023640 rs79219134 T C 0.9898551 3.273656 0.6035919
## 22 5 116023793 rs77288792 T G 0.9884058 2.923871 0.5672395
## 23 5 116025142 rs77471527 G C 0.9898551 3.273656 0.6035919
## 24 5 116025217 rs142277837 G T 0.9898551 3.273656 0.6035919
## 25 5 116025822 rs139742429 G C 0.9898551 3.273656 0.6035919
## 26 6 82425908 rs73481987 C T 0.9753623 1.922015 0.4001026
## 27 6 82442490 rs114928787 T C 0.9855072 3.192738 0.4508034
## 28 6 82442833 rs116172930 C A 0.9855072 3.192738 0.4508034
## 29 6 82443802 rs74436554 C T 0.9855072 3.192738 0.4508034
## 30 6 82444791 rs78056249 C G 0.9855072 3.192738 0.4508034
## 31 6 82445716 rs77941466 C T 0.9855072 3.192738 0.4508034
## 32 6 82447004 rs116461493 T C 0.9855072 3.192738 0.4508034
## 33 6 82447732 rs77666578 G A 0.9855072 3.192738 0.4508034
## 34 6 82451563 rs75189229 A G 0.9855072 3.192738 0.4508034
## 35 6 82453938 rs117178778 A G 0.9855072 3.192738 0.4508034
## 36 6 82454058 rs116246536 T G 0.9855072 3.192738 0.4508034
## 37 6 82454140 rs78427866 A G 0.9855072 3.192738 0.4508034
## 38 6 82454380 rs147257041 A G 0.9855072 3.192738 0.4508034
## 39 6 82454449 rs140711073 T C 0.9855072 3.192738 0.4508034
## 40 6 82454505 rs142248448 T C 0.9855072 3.192738 0.4508034
## 41 6 82454620 rs114442506 A G 0.9855072 3.192738 0.4508034
## 42 6 82456537 rs145558293 A G 0.9855072 3.192738 0.4508034
## 43 6 82458393 rs77391407 C T 0.9855072 3.192738 0.4508034
## 44 6 82458546 rs77103853 G C 0.9855072 3.192738 0.4508034
## 45 6 82459011 rs115096710 T C 0.9855072 3.192738 0.4508034
## 46 6 82459713 rs77245672 G C 0.9855072 3.192738 0.4508034
## 47 6 82459810 rs77599496 T A 0.9855072 3.192738 0.4508034
## 48 6 82459890 rs77598967 G A 0.9855072 3.192738 0.4508034
## 49 6 82460167 rs115847999 C G 0.9855072 3.192738 0.4508034
## 50 6 82460379 rs116730626 G A 0.9855072 3.192738 0.4508034
## 51 6 82460650 rs149355051 G T 0.9855072 3.192738 0.4508034
## 52 6 82462126 rs76856243 T C 0.9855072 3.192738 0.4508034
## 53 6 82462603 rs6933239 C T 0.9855072 3.192738 0.4508034
## 54 6 82462992 rs6911216 A C 0.9855072 3.192738 0.4508034
## 55 6 82465617 rs6928806 A C 0.9855072 3.192738 0.4508034
## 56 6 82466574 rs74404091 C T 0.9855072 3.192738 0.4508034
## 57 6 82466715 rs79358384 G A 0.9855072 3.192738 0.4508034
## 58 6 82467200 rs77721025 A C 0.9855072 3.192738 0.4508034
## 59 6 82467706 rs116423281 A G 0.9855072 3.192738 0.4508034
## 60 6 82467953 rs142216660 T C 0.9855072 3.192738 0.4508034
## 61 6 82467988 rs140099919 A G 0.9855072 3.192738 0.4508034
## 62 6 82468668 rs78941585 G A 0.9855072 3.192738 0.4508034
## 63 6 82468774 rs75228268 A T 0.9855072 3.192738 0.4508034
## 64 6 82469116 rs77552654 T A 0.9855072 3.192738 0.4508034
## 65 6 82470649 rs149706908 G T 0.9855072 3.192738 0.4508034
## 66 6 82470651 rs144623191 T C 0.9855072 3.192738 0.4508034
## 67 6 82470859 rs192614396 C A 0.9855072 3.192738 0.4508034
## 68 6 82471119 rs151156468 C T 0.9855072 3.192738 0.4508034
## 69 6 82471338 rs140554533 A G 0.9855072 3.192738 0.4508034
## 70 6 82471381 rs150446760 C G 0.9855072 3.192738 0.4508034
## 71 6 82471679 rs138339145 T C 0.9855072 3.192738 0.4508034
## 72 6 82472140 rs142089466 T C 0.9855072 3.192738 0.4508034
## 73 6 82473676 rs147151928 G C 0.9855072 3.192738 0.4508034
## 74 6 82473679 rs140298049 C T 0.9855072 3.192738 0.4508034
## 75 6 82473688 rs149655171 A G 0.9855072 3.192738 0.4508034
## 76 6 82474468 rs146864360 T C 0.9855072 3.192738 0.4508034
## 77 6 82474648 rs140520501 C T 0.9855072 3.192738 0.4508034
## 78 6 82474867 rs150394443 T C 0.9855072 3.192738 0.4508034
## 79 6 82475320 rs143579868 A T 0.9855072 3.192738 0.4508034
## 80 6 82475696 rs115741750 C T 0.9855072 3.192738 0.4508034
## 81 6 82477810 rs77406497 T C 0.9855072 3.192738 0.4508034
## 82 6 82478378 rs115813741 T G 0.9855072 3.192738 0.4508034
## 83 6 82478650 rs78900243 G A 0.9855072 3.192738 0.4508034
## 84 6 82478870 rs76557363 T G 0.9855072 3.192738 0.4508034
## 85 6 82479264 rs77943130 T G 0.9855072 3.192738 0.4508034
## 86 6 82479546 rs115245280 A G 0.9855072 3.192738 0.4508034
## 87 6 82479664 rs75910615 A G 0.9855072 3.192738 0.4508034
## 88 6 82480370 rs76438934 A G 0.9855072 3.192738 0.4508034
## 89 6 82481986 rs115034961 A C 0.9855072 3.192738 0.4508034
## 90 6 82482183 rs79967481 G A 0.9855072 3.192738 0.4508034
## 91 6 82482254 rs116699765 T C 0.9855072 3.192738 0.4508034
## 92 6 82483125 rs78639250 T C 0.9855072 3.192738 0.4508034
## 93 6 82483522 rs75763492 A G 0.9855072 3.192738 0.4508034
## 94 6 82483898 rs76617768 T C 0.9855072 3.192738 0.4508034
## 95 6 82484287 rs76652063 C A 0.9855072 3.192738 0.4508034
## 96 6 82484758 rs114024754 A G 0.9855072 3.192738 0.4508034
## 97 6 82485370 rs79031996 C G 0.9855072 3.192738 0.4508034
## 98 6 82485916 rs77517398 C T 0.9855072 3.192738 0.4508034
## 99 6 82486863 rs80252551 A T 0.9855072 3.192738 0.4508034
## 100 6 82488997 rs114963095 G T 0.9855072 3.192738 0.4508034
## 101 6 82489053 rs77561386 C T 0.9855072 3.192738 0.4508034
## 102 6 82489164 rs76602861 A G 0.9855072 3.192738 0.4508034
## 103 6 82490178 rs79435750 A G 0.9855072 3.192738 0.4508034
## 104 6 82490367 rs80347071 C G 0.9855072 3.192738 0.4508034
## 105 6 82492170 rs74785531 C T 0.9855072 3.192738 0.4508034
## 106 6 82492233 rs74361967 C T 0.9855072 3.192738 0.4508034
## 107 6 82492321 rs75373608 A T 0.9855072 3.192738 0.4508034
## 108 10 64099069 rs74804993 G A 0.9826087 2.596578 0.4600200
## 109 16 13935176 rs1800067 A G 0.9550725 1.618276 0.2812503
## p
## 1 9.068185e-10
## 2 9.068185e-10
## 3 9.068185e-10
## 4 9.068185e-10
## 5 9.068185e-10
## 6 9.068185e-10
## 7 9.068185e-10
## 8 9.068185e-10
## 9 3.444386e-09
## 10 1.114565e-07
## 11 1.114565e-07
## 12 1.114565e-07
## 13 4.334528e-07
## 14 4.334528e-07
## 15 1.114565e-07
## 16 4.334528e-07
## 17 4.334528e-07
## 18 4.334528e-07
## 19 4.334528e-07
## 20 4.334528e-07
## 21 1.114565e-07
## 22 4.334528e-07
## 23 1.114565e-07
## 24 1.114565e-07
## 25 1.114565e-07
## 26 2.344151e-06
## 27 8.269693e-12
## 28 8.269693e-12
## 29 8.269693e-12
## 30 8.269693e-12
## 31 8.269693e-12
## 32 8.269693e-12
## 33 8.269693e-12
## 34 8.269693e-12
## 35 8.269693e-12
## 36 8.269693e-12
## 37 8.269693e-12
## 38 8.269693e-12
## 39 8.269693e-12
## 40 8.269693e-12
## 41 8.269693e-12
## 42 8.269693e-12
## 43 8.269693e-12
## 44 8.269693e-12
## 45 8.269693e-12
## 46 8.269693e-12
## 47 8.269693e-12
## 48 8.269693e-12
## 49 8.269693e-12
## 50 8.269693e-12
## 51 8.269693e-12
## 52 8.269693e-12
## 53 8.269693e-12
## 54 8.269693e-12
## 55 8.269693e-12
## 56 8.269693e-12
## 57 8.269693e-12
## 58 8.269693e-12
## 59 8.269693e-12
## 60 8.269693e-12
## 61 8.269693e-12
## 62 8.269693e-12
## 63 8.269693e-12
## 64 8.269693e-12
## 65 8.269693e-12
## 66 8.269693e-12
## 67 8.269693e-12
## 68 8.269693e-12
## 69 8.269693e-12
## 70 8.269693e-12
## 71 8.269693e-12
## 72 8.269693e-12
## 73 8.269693e-12
## 74 8.269693e-12
## 75 8.269693e-12
## 76 8.269693e-12
## 77 8.269693e-12
## 78 8.269693e-12
## 79 8.269693e-12
## 80 8.269693e-12
## 81 8.269693e-12
## 82 8.269693e-12
## 83 8.269693e-12
## 84 8.269693e-12
## 85 8.269693e-12
## 86 8.269693e-12
## 87 8.269693e-12
## 88 8.269693e-12
## 89 8.269693e-12
## 90 8.269693e-12
## 91 8.269693e-12
## 92 8.269693e-12
## 93 8.269693e-12
## 94 8.269693e-12
## 95 8.269693e-12
## 96 8.269693e-12
## 97 8.269693e-12
## 98 8.269693e-12
## 99 8.269693e-12
## 100 8.269693e-12
## 101 8.269693e-12
## 102 8.269693e-12
## 103 8.269693e-12
## 104 8.269693e-12
## 105 8.269693e-12
## 106 8.269693e-12
## 107 8.269693e-12
## 108 3.511379e-08
## 109 1.955875e-082. R Cyl Pre-dilate
rcyl_wald_gwas <- association.test(merged_nies_210818, nies_heritable_pheno240918$R.Cyl..pre.dilate, X = nies_covar, method="lm", test = "wald", response = "quantitative", K = merged_nies_GRM, eigenK = merged_nies_eiK, p = 2)
rcyl_wald_gwas <- na.omit(rcyl_wald_gwas)
r_cyl_wfiltered <- rcyl_wald_gwas %>% filter(-log10(p)>1) %>% filter(freqA2 < 0.99)
r_cyl_wmeff <- r_cyl_wfiltered %>% filter(p < 1.84e-7)
r_cyl_wsig <- do.call(rbind, lapply(split(r_cyl_wmeff,r_cyl_wmeff$chr), function(x) {return(x[which.min(x$p),])}))
r_cyl_wres <- NULL
for (i in r_cyl_wsig$id) {
snpID <- i
snpCHR <- r_cyl_wfiltered[r_cyl_wfiltered$id == snpID,]$chr
snpPOS <- r_cyl_wfiltered[r_cyl_wfiltered$id ==snpID,]$pos
sig.peak <- r_cyl_wfiltered %>%
filter(chr == snpCHR) %>%
filter(pos > snpPOS - 50000) %>%
filter(pos < snpPOS + 50000) %>%
filter(p < 1e-5)
r_cyl_wres <- rbind(r_cyl_wres, sig.peak)
}
write.csv(r_cyl_wres, 'C:/Users/Martha/Documents/Honours/Project/honours.project/Data/gwas_filter_covar/r_cyl_wald_res.csv')
r_cyl_wres## chr pos id A1 A2 freqA2 beta sd
## 1 1 205916566 rs72752923 C A 0.9782609 0.6646789 0.12172209
## 2 1 205916729 rs16830364 G A 0.9782609 0.6646789 0.12172209
## 3 1 205916931 rs60255052 C T 0.9811594 0.7038140 0.12413749
## 4 1 205917041 rs60716530 C T 0.9782609 0.6646789 0.12172209
## 5 1 205917115 rs60644810 G A 0.9782609 0.6646789 0.12172209
## 6 1 205917248 rs35694044 A T 0.9782609 0.6646789 0.12172209
## 7 1 205917652 rs16830370 T C 0.9782609 0.6646789 0.12172209
## 8 1 205918853 rs16856462 C T 0.9782609 0.6646789 0.12172209
## 9 1 205919195 rs16856468 G A 0.9782609 0.6646789 0.12172209
## 10 1 205919303 rs60001177 T C 0.9782609 0.6646789 0.12172209
## 11 1 205919401 rs12723666 A G 0.9782609 0.6646789 0.12172209
## 12 1 205920201 rs16856470 T C 0.9811594 0.7038140 0.12413749
## 13 1 205920404 rs16856473 A G 0.9811594 0.7038140 0.12413749
## 14 1 205922403 rs68189466 G A 0.9797101 0.6984206 0.12410411
## 15 1 205922720 rs35648260 G T 0.9797101 0.6984206 0.12410411
## 16 1 205922775 rs35360452 G T 0.9797101 0.6984206 0.12410411
## 17 1 205925474 rs12727528 A G 0.9797101 0.6984206 0.12410411
## 18 1 205935183 rs1891309 G A 0.9782609 0.6885981 0.12388621
## 19 1 205935330 rs1891310 T G 0.9782609 0.6885981 0.12388621
## 20 1 205936240 rs1473537 T C 0.9739130 0.6453227 0.12092480
## 21 1 205942026 rs72752928 T C 0.9782609 0.6885981 0.12388621
## 22 1 205943691 rs66593238 T C 0.9782609 0.6885981 0.12388621
## 23 1 205944627 rs9438407 T G 0.9782609 0.6885981 0.12388621
## 24 1 205945388 rs12741299 T C 0.9782609 0.6885981 0.12388621
## 25 1 205946647 rs34265780 T C 0.9782609 0.6885981 0.12388621
## 26 2 22752117 rs72793052 C T 0.9768116 0.6739011 0.12214930
## 27 2 22759734 rs72793060 C G 0.9579710 0.6091818 0.11124690
## 28 2 22763823 rs72793066 T C 0.9579710 0.6091818 0.11124690
## 29 2 22764837 rs72793070 C G 0.9579710 0.6091818 0.11124690
## 30 2 22770868 rs4353679 C T 0.9579710 0.6091818 0.11124690
## 31 2 22771019 rs4343495 T C 0.9579710 0.6091818 0.11124690
## 32 2 22778013 rs72793089 A T 0.9579710 0.6091818 0.11124690
## 33 2 22780281 rs10187240 C T 0.9579710 0.6091818 0.11124690
## 34 2 22786683 rs72794813 C T 0.9579710 0.6091818 0.11124690
## 35 2 22792883 rs6719784 T A 0.9579710 0.6091818 0.11124690
## 36 4 21642565 rs1604803 G A 0.9724638 0.7175966 0.12075011
## 37 4 21644129 rs35792460 C T 0.9724638 0.7175966 0.12075011
## 38 4 21644652 rs35038373 A G 0.9724638 0.7175966 0.12075011
## 39 4 21648827 rs35325665 T C 0.9724638 0.7175966 0.12075011
## 40 5 111517937 rs72792073 T C 0.9434783 0.5500178 0.10272813
## 41 5 111519388 rs149693214 G T 0.9434783 0.5500178 0.10272813
## 42 5 111519507 rs112881034 T C 0.9434783 0.5500178 0.10272813
## 43 5 111520228 rs17133359 G A 0.9434783 0.5500178 0.10272813
## 44 5 111522182 rs72792075 A T 0.9434783 0.5500178 0.10272813
## 45 5 111522894 rs60878703 C T 0.9434783 0.5500178 0.10272813
## 46 5 111525865 rs56273704 T C 0.9434783 0.5500178 0.10272813
## 47 5 111527313 rs72792083 C A 0.9434783 0.5500178 0.10272813
## 48 8 124203587 rs116856476 T C 0.9840580 0.7052181 0.12982609
## 49 9 78643317 rs12377322 T A 0.8942029 0.5291633 0.08715593
## 50 9 78643821 rs11137782 T C 0.8942029 0.5291633 0.08715593
## 51 9 78644279 rs10867228 C T 0.8942029 0.5291633 0.08715593
## 52 9 78645867 rs9644983 A T 0.8942029 0.5291633 0.08715593
## 53 9 78650464 rs7870042 G T 0.8869565 0.5196043 0.08617023
## 54 10 25947431 rs144363867 G A 0.9565217 0.6297366 0.11062451
## 55 11 100721739 rs148096302 A G 0.9840580 0.6452475 0.13469060
## 56 11 100769446 rs78598508 G A 0.9753623 0.7344718 0.12088242
## 57 18 50137976 rs73430360 G T 0.9855072 0.7093028 0.12336747
## p
## 1 9.190772e-08
## 2 9.190772e-08
## 3 3.065254e-08
## 4 9.190772e-08
## 5 9.190772e-08
## 6 9.190772e-08
## 7 9.190772e-08
## 8 9.190772e-08
## 9 9.190772e-08
## 10 9.190772e-08
## 11 9.190772e-08
## 12 3.065254e-08
## 13 3.065254e-08
## 14 3.830535e-08
## 15 3.830535e-08
## 16 3.830535e-08
## 17 3.830535e-08
## 18 5.523311e-08
## 19 5.523311e-08
## 20 1.737014e-07
## 21 5.523311e-08
## 22 5.523311e-08
## 23 5.523311e-08
## 24 5.523311e-08
## 25 5.523311e-08
## 26 6.855414e-08
## 27 8.489388e-08
## 28 8.489388e-08
## 29 8.489388e-08
## 30 8.489388e-08
## 31 8.489388e-08
## 32 8.489388e-08
## 33 8.489388e-08
## 34 8.489388e-08
## 35 8.489388e-08
## 36 6.956532e-09
## 37 6.956532e-09
## 38 6.956532e-09
## 39 6.956532e-09
## 40 1.588553e-07
## 41 1.588553e-07
## 42 1.588553e-07
## 43 1.588553e-07
## 44 1.588553e-07
## 45 1.588553e-07
## 46 1.588553e-07
## 47 1.588553e-07
## 48 1.065448e-07
## 49 3.397391e-09
## 50 3.397391e-09
## 51 3.397391e-09
## 52 3.397391e-09
## 53 4.286167e-09
## 54 2.712142e-08
## 55 2.490562e-06
## 56 3.313262e-09
## 57 1.997800e-083. R K-value V
rkvalV_wald_gwas <- association.test(merged_nies_210818, nies_heritable_pheno240918$R.K.value.V, X = nies_covar, method="lm", test = "wald", response = "quantitative", K = merged_nies_GRM, eigenK = merged_nies_eiK, p = 2)## Warning in trans.X(X, mean.y = mean(Y)): An intercept column was added to
## the covariate matrix XrkvalV_wald_gwas <- na.omit(rkvalV_wald_gwas)
r_kvalV_wfiltered <- rkvalV_wald_gwas %>% filter(-log10(p)>1) %>% filter(freqA2 < 0.99)
r_kvalV_wmeff <- r_kvalV_wfiltered %>% filter(p < 1.84e-7)
r_kvalV_wsig <- do.call(rbind, lapply(split(r_kvalV_wmeff,r_kvalV_wmeff$chr), function(x) {return(x[which.min(x$p),])}))
r_kvalV_wres <- NULL
for (i in r_kvalV_wsig$id) {
snpID <- i
snpCHR <- r_kvalV_wfiltered[r_kvalV_wfiltered$id == snpID,]$chr
snpPOS <- r_kvalV_wfiltered[r_kvalV_wfiltered$id ==snpID,]$pos
sig.peak <- r_kvalV_wfiltered %>%
filter(chr == snpCHR) %>%
filter(pos > snpPOS - 50000) %>%
filter(pos < snpPOS + 50000) %>%
filter(p < 1e-5)
r_kvalV_wres <- rbind(r_kvalV_wres, sig.peak)
}
write.csv(r_kvalV_wres, 'C:/Users/Martha/Documents/Honours/Project/honours.project/Data/gwas_filter_covar/r_kvalV_wald_res.csv')
r_kvalV_wres## chr pos id A1 A2 freqA2 beta sd
## 1 1 205916566 rs72752923 C A 0.9782609 -2.038243 0.3752191
## 2 1 205916729 rs16830364 G A 0.9782609 -2.038243 0.3752191
## 3 1 205916931 rs60255052 C T 0.9811594 -2.677836 0.3892119
## 4 1 205917041 rs60716530 C T 0.9782609 -2.038243 0.3752191
## 5 1 205917115 rs60644810 G A 0.9782609 -2.038243 0.3752191
## 6 1 205917248 rs35694044 A T 0.9782609 -2.038243 0.3752191
## 7 1 205917652 rs16830370 T C 0.9782609 -2.038243 0.3752191
## 8 1 205918853 rs16856462 C T 0.9782609 -2.038243 0.3752191
## 9 1 205919195 rs16856468 G A 0.9782609 -2.038243 0.3752191
## 10 1 205919303 rs60001177 T C 0.9782609 -2.038243 0.3752191
## 11 1 205919401 rs12723666 A G 0.9782609 -2.038243 0.3752191
## 12 1 205920201 rs16856470 T C 0.9811594 -2.677836 0.3892119
## 13 1 205920404 rs16856473 A G 0.9811594 -2.677836 0.3892119
## 14 1 205922403 rs68189466 G A 0.9797101 -2.351687 0.3832183
## 15 1 205922720 rs35648260 G T 0.9797101 -2.351687 0.3832183
## 16 1 205922775 rs35360452 G T 0.9797101 -2.351687 0.3832183
## 17 1 205925474 rs12727528 A G 0.9797101 -2.351687 0.3832183
## 18 1 205935183 rs1891309 G A 0.9782609 -2.246581 0.3729493
## 19 1 205935330 rs1891310 T G 0.9782609 -2.246581 0.3729493
## 20 1 205936240 rs1473537 T C 0.9739130 -2.170629 0.3425381
## 21 1 205937685 rs34190121 T C 0.9797101 -1.936564 0.4197622
## 22 1 205942026 rs72752928 T C 0.9782609 -2.246581 0.3729493
## 23 1 205943691 rs66593238 T C 0.9782609 -2.246581 0.3729493
## 24 1 205944627 rs9438407 T G 0.9782609 -2.246581 0.3729493
## 25 1 205945388 rs12741299 T C 0.9782609 -2.246581 0.3729493
## 26 1 205946647 rs34265780 T C 0.9782609 -2.246581 0.3729493
## 27 4 119321195 rs77203710 A G 0.9855072 -2.625926 0.4405142
## 28 4 119322197 rs1397614 T C 0.9855072 -2.625926 0.4405142
## 29 4 119362510 rs112314510 A G 0.9855072 -2.625926 0.4405142
## 30 4 119362552 rs111968273 T A 0.9855072 -2.625926 0.4405142
## 31 4 119367677 rs113059419 A G 0.9869565 -2.851907 0.4562266
## 32 4 119372303 rs112760591 G A 0.9855072 -2.625926 0.4405142
## 33 4 119372480 rs111609258 C G 0.9855072 -2.625926 0.4405142
## 34 4 119378224 rs147602981 G A 0.9855072 -2.625926 0.4405142
## 35 4 119381167 rs143847948 A C 0.9855072 -2.625926 0.4405142
## 36 4 119390257 rs113224532 T C 0.9855072 -2.625926 0.4405142
## 37 4 119392279 rs117856633 C A 0.9855072 -2.625926 0.4405142
## 38 4 119398681 rs113825627 C G 0.9855072 -2.625926 0.4405142
## 39 4 119403429 rs112414671 A G 0.9869565 -2.851907 0.4562266
## 40 4 119403485 rs185357281 A G 0.9869565 -2.144971 0.4693895
## 41 4 119404439 rs183181597 A G 0.9855072 -2.625926 0.4405142
## 42 4 119404927 rs113317707 C A 0.9855072 -2.625926 0.4405142
## 43 4 119408454 rs184703141 T C 0.9855072 -2.625926 0.4405142
## 44 5 33168945 rs113442983 T C 0.9898551 -3.297808 0.6011238
## p
## 1 1.066727e-07
## 2 1.066727e-07
## 3 2.908984e-11
## 4 1.066727e-07
## 5 1.066727e-07
## 6 1.066727e-07
## 7 1.066727e-07
## 8 1.066727e-07
## 9 1.066727e-07
## 10 1.066727e-07
## 11 1.066727e-07
## 12 2.908984e-11
## 13 2.908984e-11
## 14 2.358515e-09
## 15 2.358515e-09
## 16 2.358515e-09
## 17 2.358515e-09
## 18 4.447739e-09
## 19 4.447739e-09
## 20 7.489119e-10
## 21 5.628478e-06
## 22 4.447739e-09
## 23 4.447739e-09
## 24 4.447739e-09
## 25 4.447739e-09
## 26 4.447739e-09
## 27 6.305362e-09
## 28 6.305362e-09
## 29 6.305362e-09
## 30 6.305362e-09
## 31 1.228698e-09
## 32 6.305362e-09
## 33 6.305362e-09
## 34 6.305362e-09
## 35 6.305362e-09
## 36 6.305362e-09
## 37 6.305362e-09
## 38 6.305362e-09
## 39 1.228698e-09
## 40 6.856998e-06
## 41 6.305362e-09
## 42 6.305362e-09
## 43 6.305362e-09
## 44 8.069754e-084. UVAF
uvaf_wald_gwas <- association.test(merged_nies_210818, nies_heritable_pheno240918$totaluvafmm, X = nies_covar, method="lm", test = "wald", response = "quantitative", K = merged_nies_GRM, eigenK = merged_nies_eiK, p = 2)## Warning in trans.X(X, mean.y = mean(Y)): An intercept column was added to
## the covariate matrix Xuvaf_wald_gwas <- na.omit(uvaf_wald_gwas)
uvaf_wfiltered <- uvaf_wald_gwas %>% filter(-log10(p)>1) %>% filter(freqA2 < 0.99)
uvaf_wmeff <- uvaf_wfiltered %>% filter(p < 1.84e-7)
uvaf_wsig <- do.call(rbind, lapply(split(uvaf_wmeff,uvaf_wmeff$chr), function(x) {return(x[which.min(x$p),])}))
uvaf_wres <- NULL
for (i in uvaf_wsig$id) {
snpID <- i
snpCHR <- uvaf_wfiltered[uvaf_wfiltered$id == snpID,]$chr
snpPOS <- uvaf_wfiltered[uvaf_wfiltered$id ==snpID,]$pos
sig.peak <- uvaf_wfiltered %>%
filter(chr == snpCHR) %>%
filter(pos > snpPOS - 50000) %>%
filter(pos < snpPOS + 50000) %>%
filter(p < 1e-5)
uvaf_wres <- rbind(uvaf_wres, sig.peak)
}
write.csv(uvaf_wres, 'C:/Users/Martha/Documents/Honours/Project/honours.project/Data/gwas_filter_covar/uvaf_wald_res.csv')
uvaf_wres## chr pos id A1 A2 freqA2 beta sd
## 1 1 158362100 rs112697372 T G 0.9898551 -51.08282 9.320546
## 2 4 22963447 rs75555621 T C 0.9753623 -36.07684 6.065289
## 3 4 22968049 rs961611 G C 0.9753623 -36.07684 6.065289
## 4 4 22994702 rs77135796 C A 0.9768116 -36.31808 6.250112
## 5 5 159560389 rs76476973 G T 0.9594203 -25.45470 4.482965
## 6 5 159560514 rs10515800 T C 0.9594203 -25.45470 4.482965
## 7 5 159560700 rs17056804 T C 0.9594203 -25.45470 4.482965
## 8 7 107578936 rs191522213 G C 0.9884058 -53.10171 8.662913
## 9 8 34731289 rs116937259 C T 0.9884058 -44.01351 7.764533
## 10 8 34738629 rs141115618 C G 0.9898551 -40.73365 8.262096
## 11 8 34743083 rs192922472 T C 0.9884058 -44.01351 7.764533
## 12 9 68575580 rs34054758 A G 0.9753623 -32.65221 5.670032
## 13 9 68576337 rs35666199 G C 0.9753623 -32.65221 5.670032
## 14 9 68580538 rs6560237 C T 0.9753623 -32.65221 5.670032
## 15 9 68581265 rs7048633 T C 0.9753623 -32.65221 5.670032
## 16 9 68583308 rs71501771 T A 0.9753623 -32.65221 5.670032
## 17 9 68586048 rs35551873 T C 0.9753623 -32.65221 5.670032
## 18 9 68586254 rs7045561 G A 0.9753623 -32.65221 5.670032
## 19 9 68587181 rs13288798 G T 0.9753623 -32.65221 5.670032
## 20 9 68587313 rs13284137 G A 0.9753623 -32.65221 5.670032
## 21 9 68588522 rs139047286 C T 0.9753623 -32.65221 5.670032
## 22 9 68588999 rs7859065 C T 0.9753623 -32.65221 5.670032
## 23 9 68594362 rs13290124 A G 0.9753623 -32.65221 5.670032
## 24 9 68595978 rs10511959 A G 0.9753623 -32.65221 5.670032
## 25 9 68597806 rs34412731 T C 0.9753623 -32.65221 5.670032
## 26 9 68599834 rs12004993 G A 0.9753623 -32.65221 5.670032
## 27 9 68605388 rs76930250 G C 0.9753623 -32.65221 5.670032
## 28 9 68605806 rs13287094 A G 0.9753623 -32.65221 5.670032
## 29 9 68608085 rs34921768 G A 0.9753623 -32.65221 5.670032
## 30 9 68608420 rs13299492 A G 0.9753623 -32.65221 5.670032
## 31 9 68612655 rs34344868 A G 0.9753623 -32.65221 5.670032
## 32 9 68615281 rs34805084 A G 0.9739130 -30.53099 5.558659
## 33 9 68618011 rs71501772 G C 0.9739130 -30.53099 5.558659
## 34 9 68618330 rs34763246 T C 0.9739130 -30.53099 5.558659
## 35 9 68619315 rs34436601 T C 0.9739130 -30.53099 5.558659
## 36 9 68621728 rs13289515 C G 0.9739130 -30.53099 5.558659
## 37 9 68621879 rs13289852 A G 0.9753623 -29.48118 5.714665
## 38 9 68624185 rs117741244 T C 0.9811594 -40.42978 6.284847
## 39 9 68629924 rs117987088 T C 0.9811594 -40.42978 6.284847
## 40 9 68652928 rs77058957 C T 0.9695652 -25.51528 5.255250
## 41 9 68654569 rs76760268 T C 0.9695652 -25.51528 5.255250
## 42 9 68655326 rs186268857 C G 0.9695652 -25.51528 5.255250
## 43 9 68655444 rs118049065 G T 0.9695652 -25.51528 5.255250
## 44 9 68657621 rs75835902 G A 0.9695652 -25.51528 5.255250
## 45 9 68658645 rs180877078 A T 0.9695652 -25.51528 5.255250
## 46 9 68658661 rs78742689 G C 0.9695652 -25.51528 5.255250
## 47 9 68659669 rs111504512 G A 0.9695652 -25.51528 5.255250
## 48 9 68659832 rs150742857 G C 0.9695652 -25.51528 5.255250
## 49 9 68659936 rs145005200 C G 0.9695652 -25.51528 5.255250
## 50 9 68660811 rs76726918 A G 0.9695652 -25.51528 5.255250
## 51 9 68660882 rs77616759 G A 0.9695652 -25.51528 5.255250
## 52 9 68664724 rs78104260 C T 0.9695652 -25.51528 5.255250
## 53 9 68668603 rs74341285 T C 0.9695652 -25.51528 5.255250
## 54 9 68669378 rs75245907 T C 0.9695652 -25.51528 5.255250
## 55 9 68669933 rs116959126 G T 0.9695652 -25.51528 5.255250
## 56 9 68671411 rs79224950 G A 0.9695652 -25.51528 5.255250
## 57 9 68672520 rs78935265 A G 0.9695652 -25.51528 5.255250
## 58 9 68673301 rs80225323 G A 0.9695652 -25.51528 5.255250
## 59 18 22734233 rs1357201 A G 0.9637681 -25.09240 4.661405
## 60 18 22782053 rs10153383 C T 0.9681159 -23.54607 4.943863
## p
## 1 8.299304e-08
## 2 6.774313e-09
## 3 6.774313e-09
## 4 1.437436e-08
## 5 2.936260e-08
## 6 2.936260e-08
## 7 2.936260e-08
## 8 2.452435e-09
## 9 3.089838e-08
## 10 1.290054e-06
## 11 3.089838e-08
## 12 1.905184e-08
## 13 1.905184e-08
## 14 1.905184e-08
## 15 1.905184e-08
## 16 1.905184e-08
## 17 1.905184e-08
## 18 1.905184e-08
## 19 1.905184e-08
## 20 1.905184e-08
## 21 1.905184e-08
## 22 1.905184e-08
## 23 1.905184e-08
## 24 1.905184e-08
## 25 1.905184e-08
## 26 1.905184e-08
## 27 1.905184e-08
## 28 1.905184e-08
## 29 1.905184e-08
## 30 1.905184e-08
## 31 1.905184e-08
## 32 7.804189e-08
## 33 7.804189e-08
## 34 7.804189e-08
## 35 7.804189e-08
## 36 7.804189e-08
## 37 4.243244e-07
## 38 4.279007e-10
## 39 4.279007e-10
## 40 1.841426e-06
## 41 1.841426e-06
## 42 1.841426e-06
## 43 1.841426e-06
## 44 1.841426e-06
## 45 1.841426e-06
## 46 1.841426e-06
## 47 1.841426e-06
## 48 1.841426e-06
## 49 1.841426e-06
## 50 1.841426e-06
## 51 1.841426e-06
## 52 1.841426e-06
## 53 1.841426e-06
## 54 1.841426e-06
## 55 1.841426e-06
## 56 1.841426e-06
## 57 1.841426e-06
## 58 1.841426e-06
## 59 1.372926e-07
## 60 2.839311e-065. PC1
pc1_wald_gwas <- association.test(merged_nies_210818, nies_heritable_pheno240918$coord.Dim.1, X = nies_covar, method="lm", test = "wald", response = "quantitative", K = merged_nies_GRM, eigenK = merged_nies_eiK, p = 2)
pc1_wald_gwas <- na.omit(pc1_wald_gwas)
pc1_wfiltered <- pc1_wald_gwas %>% filter(-log10(p)>1) %>% filter(freqA2 < 0.99)
pc1_wmeff <- pc1_wfiltered %>% filter(p < 1.84e-7)
pc1_wsig <- do.call(rbind, lapply(split(pc1_wmeff,pc1_wmeff$chr), function(x) {return(x[which.min(x$p),])}))
pc1_wres <- NULL
for (i in pc1_wsig$id) {
snpID <- i
snpCHR <- pc1_wfiltered[pc1_wfiltered$id == snpID,]$chr
snpPOS <- pc1_wfiltered[pc1_wfiltered$id ==snpID,]$pos
sig.peak <- pc1_wfiltered %>%
filter(chr == snpCHR) %>%
filter(pos > snpPOS - 50000) %>%
filter(pos < snpPOS + 50000) %>%
filter(p < 1e-5)
pc1_wres <- rbind(pc1_wres, sig.peak)
}
write.csv(pc1_wres, 'C:/Users/Martha/Documents/Honours/Project/honours.project/Data/gwas_filter_covar/pc1_wald_res.csv')
pc1_wres## chr pos id A1 A2 freqA2 beta sd
## 1 1 197538281 rs10494757 T C 0.9594203 -1.4256297 0.2477083
## 2 2 211334210 rs1821662 G A 0.6898551 -0.7831531 0.1459409
## 3 2 211334911 rs10804194 T C 0.7637681 -0.7882912 0.1550308
## 4 2 211335269 rs1595068 C T 0.6927536 -0.7840114 0.1475340
## 5 3 160102701 rs6778335 T C 0.9028986 -1.1737527 0.2178986
## 6 3 160102966 rs11922988 A C 0.8637681 -1.0767482 0.1913661
## 7 3 160122371 rs66566032 G A 0.9202899 -1.0901215 0.2281417
## 8 3 160123754 rs73171924 A G 0.9159420 -1.0427722 0.2266812
## 9 3 160124095 rs113621516 T C 0.9159420 -1.0427722 0.2266812
## 10 3 160125646 rs4541448 T G 0.8884058 -1.0770006 0.2076571
## 11 3 160126934 rs11926233 C T 0.8884058 -1.0770006 0.2076571
## 12 3 160126964 rs116472907 A G 0.9217391 -1.1014880 0.2271433
## 13 3 160126966 rs115317177 C A 0.9217391 -1.1014880 0.2271433
## 14 3 160126968 rs114050713 G C 0.9217391 -1.1014880 0.2271433
## 15 3 160127332 rs67955459 C T 0.9202899 -1.0901215 0.2281417
## 16 3 160130412 rs59287878 A C 0.9202899 -1.0901215 0.2281417
## 17 4 161298219 rs75219943 A T 0.9014493 -1.0068320 0.2018008
## 18 4 161298374 rs78397069 T A 0.9086957 -1.1249478 0.2066917
## 19 4 161298417 rs7667597 G A 0.9086957 -1.1249478 0.2066917
## 20 4 161299003 rs78982571 G A 0.9086957 -1.1249478 0.2066917
## 21 4 161301597 rs11930861 A C 0.9086957 -1.1249478 0.2066917
## 22 4 161302329 rs7658820 G A 0.9086957 -1.1249478 0.2066917
## 23 4 161302835 rs113228726 G T 0.9086957 -1.1249478 0.2066917
## 24 4 161308227 rs9308027 T C 0.7579710 -0.6956557 0.1503054
## 25 4 161308302 rs9308028 T G 0.7579710 -0.6956557 0.1503054
## 26 4 161308359 rs10027110 G T 0.7579710 -0.6956557 0.1503054
## 27 4 161308518 rs9992864 G A 0.7579710 -0.6956557 0.1503054
## 28 4 161308604 rs10015574 T C 0.7579710 -0.6956557 0.1503054
## 29 4 161308878 rs10017957 G C 0.7579710 -0.6956557 0.1503054
## 30 4 161308882 rs10018124 T G 0.7579710 -0.6956557 0.1503054
## 31 4 161308926 rs10018045 T C 0.7579710 -0.6956557 0.1503054
## 32 4 161308939 rs10029764 C T 0.7579710 -0.6956557 0.1503054
## 33 4 161309025 rs10018146 T C 0.7579710 -0.6956557 0.1503054
## 34 4 161309066 rs10029866 G T 0.7579710 -0.6956557 0.1503054
## 35 4 161309184 rs6827362 A G 0.7579710 -0.6956557 0.1503054
## 36 4 161309223 rs6826847 C A 0.7579710 -0.6956557 0.1503054
## 37 4 161309666 rs6827877 G C 0.7579710 -0.6956557 0.1503054
## 38 4 161309721 rs10018817 T C 0.7579710 -0.6956557 0.1503054
## 39 4 161309899 rs10021326 A G 0.7579710 -0.6956557 0.1503054
## 40 4 161309993 rs6854527 C T 0.7579710 -0.6956557 0.1503054
## 41 4 161310377 rs6834175 T C 0.7579710 -0.6956557 0.1503054
## 42 4 161310657 rs6536585 G A 0.7579710 -0.6956557 0.1503054
## 43 4 161310853 rs7677663 T A 0.7579710 -0.6956557 0.1503054
## 44 4 161311072 rs7678039 G A 0.7579710 -0.6956557 0.1503054
## 45 4 161311138 rs7678417 T C 0.7579710 -0.6956557 0.1503054
## 46 4 161311208 rs10007857 A C 0.7579710 -0.6956557 0.1503054
## 47 4 161314841 rs5010468 A G 0.7376812 -0.6786950 0.1431825
## 48 5 110018330 rs1563324 G A 0.9637681 -1.2424987 0.2657114
## 49 5 110027474 rs1455554 G A 0.8782609 -1.0517960 0.1865073
## 50 5 110034646 rs1869723 T C 0.9550725 -1.1489939 0.2529790
## 51 5 110063032 rs72816853 T C 0.9188406 -1.0011724 0.2186121
## 52 5 110063197 rs7710972 A G 0.9188406 -1.0011724 0.2186121
## 53 5 110063858 rs10515409 G C 0.9188406 -1.0011724 0.2186121
## 54 5 110063929 rs11959815 A G 0.9188406 -1.0011724 0.2186121
## 55 5 110064678 rs72816864 G C 0.9188406 -1.0011724 0.2186121
## 56 5 110065253 rs72816865 A G 0.9188406 -1.0011724 0.2186121
## 57 5 110065473 rs17162644 C T 0.9188406 -1.0011724 0.2186121
## 58 5 110065710 rs17162650 A G 0.9188406 -1.0011724 0.2186121
## 59 5 110066417 rs72816868 C T 0.9188406 -1.0011724 0.2186121
## 60 5 110068774 rs72816871 T G 0.9188406 -1.0011724 0.2186121
## 61 5 110073037 rs72816880 T C 0.9188406 -1.0011724 0.2186121
## 62 6 19696595 rs6921521 T C 0.9811594 -1.2688520 0.2757097
## 63 6 19742012 rs1209816 T C 0.9652174 -1.3539351 0.2428034
## 64 7 7976971 rs73049252 A G 0.9376812 -1.2573307 0.2192251
## 65 7 7978549 rs7804306 A G 0.9304348 -1.2755321 0.2192226
## 66 7 7978858 rs73049256 T A 0.9376812 -1.2573307 0.2192251
## 67 7 7979532 rs67343471 T G 0.9275362 -1.2107762 0.2172348
## 68 7 7981025 rs56073406 G A 0.9304348 -1.2755321 0.2192226
## 69 7 7981281 rs112270482 C T 0.9376812 -1.2573307 0.2192251
## 70 7 7981982 rs6975218 G A 0.9304348 -1.2755321 0.2192226
## 71 7 7982015 rs73049270 T C 0.9376812 -1.2573307 0.2192251
## 72 7 7982385 rs73049276 A G 0.9376812 -1.2573307 0.2192251
## 73 7 7985192 rs113537684 T G 0.9376812 -1.2573307 0.2192251
## 74 7 7985209 rs60466842 A C 0.9188406 -1.0858589 0.2095709
## 75 7 7992584 rs73049290 C T 0.9376812 -1.2573307 0.2192251
## 76 7 7993887 rs17566854 C A 0.9376812 -1.2573307 0.2192251
## 77 7 7995282 rs56017154 A G 0.9376812 -1.2573307 0.2192251
## 78 7 7997876 rs142269087 A G 0.9376812 -1.2573307 0.2192251
## 79 7 7999017 rs73049293 C T 0.9376812 -1.2573307 0.2192251
## 80 7 7999429 rs73049297 A G 0.9376812 -1.2573307 0.2192251
## 81 7 8001135 rs138912252 A G 0.9376812 -1.2573307 0.2192251
## 82 7 8001658 rs147420655 A G 0.9376812 -1.2573307 0.2192251
## 83 7 8002315 rs73049300 G C 0.9376812 -1.2573307 0.2192251
## 84 7 8010614 rs73050915 T G 0.9376812 -1.2573307 0.2192251
## 85 7 8012093 rs149303885 T G 0.9376812 -1.2573307 0.2192251
## 86 7 8016462 rs145954895 A C 0.9376812 -1.2573307 0.2192251
## 87 7 8019638 rs73050929 A C 0.9376812 -1.2573307 0.2192251
## 88 7 8027882 rs73050940 G A 0.9376812 -1.2573307 0.2192251
## 89 9 2121302 rs58152462 C G 0.9884058 -1.3502053 0.2960458
## 90 9 2124140 rs10811481 T C 0.8739130 -1.0141919 0.1945314
## 91 9 2124569 rs4373572 G A 0.8724638 -1.0248984 0.1951010
## 92 9 2124583 rs3829071 G C 0.8724638 -1.0248984 0.1951010
## 93 9 2125231 rs7048496 A C 0.8971014 -1.1498926 0.2086025
## 94 9 2126238 rs6475506 A G 0.8971014 -1.1532723 0.2072771
## 95 9 2127469 rs6475507 T A 0.8971014 -1.1498926 0.2086025
## 96 9 2127677 rs6475508 A G 0.8971014 -1.1498926 0.2086025
## 97 9 2127796 rs3829072 A G 0.8971014 -1.1498926 0.2086025
## 98 9 2129360 rs6475519 G T 0.9014493 -1.1293905 0.2157940
## 99 9 2129744 rs10811504 C T 0.8956522 -1.1683446 0.2082453
## 100 9 2129798 rs10964907 G T 0.9014493 -1.1293905 0.2157940
## 101 9 2129832 rs10964908 C T 0.8942029 -1.1598299 0.2067817
## 102 9 2129949 rs10964909 G A 0.9028986 -1.1115208 0.2164786
## 103 9 2130029 rs10811507 T C 0.8956522 -1.1432338 0.2074131
## 104 9 2130828 rs6475520 G A 0.9028986 -1.1115208 0.2164786
## 105 9 2130861 rs6475521 G C 0.8956522 -1.1432338 0.2074131
## 106 9 2131534 rs6475524 G A 0.9362319 -1.1867207 0.2377471
## 107 10 58350923 rs117937758 T C 0.9579710 -1.2816181 0.2401111
## 108 10 58363234 rs2306605 G T 0.9507246 -1.2567480 0.2326473
## 109 10 58363726 rs73288305 G A 0.9231884 -0.9798906 0.2065222
## 110 10 58367879 rs74377516 T G 0.9507246 -1.2567480 0.2326473
## 111 10 58368078 rs75362994 A G 0.9507246 -1.2567480 0.2326473
## 112 10 58371631 rs56713413 T C 0.9333333 -1.0758271 0.2186407
## 113 10 58388991 rs16912188 G A 0.9362319 -1.0500796 0.2174013
## 114 10 58391107 rs191321905 A G 0.9623188 -1.2854714 0.2435308
## 115 10 58391386 rs16912196 G A 0.9536232 -1.1571822 0.2335622
## 116 10 58391482 rs16912197 G A 0.9521739 -1.1079482 0.2299337
## 117 10 58392399 rs79356971 C T 0.9362319 -1.0500796 0.2174013
## 118 10 58392785 rs77124850 T C 0.9362319 -1.0500796 0.2174013
## 119 10 58393772 rs112938146 C G 0.9362319 -1.0500796 0.2174013
## 120 10 58396221 rs17847532 C T 0.9536232 -1.1571822 0.2335622
## 121 10 58396842 rs74827573 C T 0.9536232 -1.1571822 0.2335622
## 122 10 58396926 rs16912201 G A 0.9536232 -1.1571822 0.2335622
## 123 10 58397881 rs77032090 A G 0.9536232 -1.1571822 0.2335622
## 124 10 58398310 rs16912202 G T 0.9536232 -1.1571822 0.2335622
## 125 10 58400877 rs79696318 T C 0.9536232 -1.1571822 0.2335622
## 126 11 69654262 rs7178 G A 0.9217391 -1.2094747 0.2089804
## 127 12 131726697 rs71470343 T C 0.7565217 -0.8689439 0.1702817
## 128 12 131727978 rs11612305 G A 0.7565217 -0.8689439 0.1702817
## 129 12 131732148 rs34459128 A G 0.7565217 -0.8689439 0.1702817
## 130 12 131733497 rs11246782 C A 0.7565217 -0.8689439 0.1702817
## 131 12 131735840 rs12426142 G T 0.7565217 -0.8689439 0.1702817
## 132 12 131740230 rs35811529 A T 0.7565217 -0.8689439 0.1702817
## 133 12 131741218 rs77720672 A G 0.7565217 -0.8689439 0.1702817
## 134 12 131750373 rs11613616 A G 0.7565217 -0.8689439 0.1702817
## 135 12 131751961 rs12814215 A G 0.7565217 -0.8689439 0.1702817
## 136 12 131753205 rs1051219 T C 0.7550725 -0.9111014 0.1703480
## 137 12 131755796 rs3741526 T C 0.5246377 -0.8142617 0.1434219
## 138 12 131757714 rs10902445 A G 0.5246377 -0.8142617 0.1434219
## 139 12 131759383 rs10751692 C T 0.5231884 -0.8140192 0.1429634
## 140 12 131780621 rs35769880 A G 0.7565217 -0.8488046 0.1691329
## 141 12 131782218 rs12824836 C T 0.7579710 -0.8608964 0.1705522
## 142 12 131788771 rs10751693 A G 0.5260870 -0.8135621 0.1440277
## 143 12 131789723 rs78792048 C A 0.7579710 -0.8608964 0.1705522
## 144 12 131790985 rs7302570 A C 0.7579710 -0.8608964 0.1705522
## 145 12 131792417 rs7972213 C T 0.5362319 -0.8117677 0.1437640
## 146 12 131793860 rs35198651 A G 0.7579710 -0.8608964 0.1705522
## 147 12 131794164 rs34705844 G A 0.7579710 -0.8608964 0.1705522
## 148 12 131805033 rs11615253 T C 0.7550725 -0.8682945 0.1705908
## 149 12 131805444 rs12319878 C T 0.5188406 -0.8165264 0.1461678
## 150 12 131805478 rs7963727 C G 0.7550725 -0.8682945 0.1705908
## 151 13 98207311 rs285107 G A 0.5217391 -0.7591165 0.1420521
## 152 13 98240001 rs944095 C T 0.6695652 -0.7384079 0.1436502
## 153 14 78416873 rs17829009 A G 0.9463768 -1.2557271 0.2317082
## 154 15 45161524 rs1648315 G A 0.9739130 -1.3000975 0.2737862
## 155 15 45163058 rs938130 G A 0.9739130 -1.3000975 0.2737862
## 156 15 45163996 rs1648314 G A 0.9739130 -1.3000975 0.2737862
## 157 15 45172570 rs1648290 A G 0.9739130 -1.3000975 0.2737862
## 158 15 45173053 rs1706819 G A 0.9739130 -1.3000975 0.2737862
## 159 15 45175342 rs1632144 C G 0.9739130 -1.3000975 0.2737862
## 160 15 45181145 rs1625404 G C 0.9739130 -1.3000975 0.2737862
## 161 15 45196676 rs2467839 A T 0.9739130 -1.3000975 0.2737862
## 162 15 45199537 rs1648300 T C 0.9739130 -1.3000975 0.2737862
## 163 15 45201250 rs2458239 C G 0.9739130 -1.3000975 0.2737862
## 164 15 45201819 rs1648301 T C 0.9637681 -1.3678326 0.2567521
## 165 15 45203931 rs2668750 A G 0.9724638 -1.2762335 0.2714550
## 166 15 45206013 rs1648292 A C 0.9724638 -1.2762335 0.2714550
## 167 15 45207831 rs2458240 G A 0.9724638 -1.2762335 0.2714550
## 168 15 45208189 rs1628717 G A 0.9724638 -1.2762335 0.2714550
## 169 15 45212788 rs1648291 T C 0.9724638 -1.2762335 0.2714550
## 170 15 45213976 rs1648288 C G 0.9724638 -1.2762335 0.2714550
## 171 15 45217126 rs1706828 C T 0.9724638 -1.2762335 0.2714550
## 172 15 45218630 rs1648280 G T 0.9724638 -1.2762335 0.2714550
## 173 15 45223046 rs2458241 C T 0.9724638 -1.2762335 0.2714550
## 174 15 45225440 rs1706833 T C 0.9724638 -1.2762335 0.2714550
## 175 15 45225994 rs1706836 A G 0.9724638 -1.2762335 0.2714550
## 176 16 52630885 rs8050739 C T 0.7362319 -0.8198966 0.1468328
## 177 16 52632690 rs7188201 G A 0.7362319 -0.8198966 0.1468328
## 178 16 52632695 rs7188202 G A 0.7362319 -0.8198966 0.1468328
## 179 16 52632827 rs7187724 A C 0.7362319 -0.8198966 0.1468328
## 180 16 52635058 rs4536472 A G 0.7362319 -0.8198966 0.1468328
## 181 16 52635377 rs58472864 C A 0.7362319 -0.8198966 0.1468328
## 182 16 52635542 rs28542820 A G 0.7362319 -0.8198966 0.1468328
## 183 16 52641501 rs3104819 G A 0.7985507 -0.8674585 0.1586238
## 184 16 52642525 rs3112592 T C 0.7985507 -0.8674585 0.1586238
## 185 16 52642931 rs3104822 A G 0.7985507 -0.8674585 0.1586238
## 186 16 52647924 rs3112587 T C 0.7869565 -0.8165291 0.1598739
## 187 18 36626107 rs75895411 C A 0.8942029 -0.9276155 0.1934680
## 188 18 36626477 rs2644254 A G 0.7927536 -0.8692300 0.1614081
## 189 18 36626486 rs79026601 G A 0.8942029 -0.9276155 0.1934680
## 190 18 36627754 rs11661986 A G 0.8985507 -0.8944593 0.1964448
## 191 18 36627944 rs11662615 T C 0.8985507 -0.8944593 0.1964448
## 192 18 36629087 rs78120969 C G 0.8942029 -0.9276155 0.1934680
## 193 18 36630706 rs11664734 T G 0.8985507 -0.8944593 0.1964448
## 194 18 36631401 rs8083846 T C 0.8985507 -0.8944593 0.1964448
## 195 18 36631850 rs8084815 C G 0.8942029 -0.9276155 0.1934680
## 196 18 36631892 rs8084477 G A 0.8942029 -0.9276155 0.1934680
## 197 18 36632135 rs74818539 G T 0.8942029 -0.9276155 0.1934680
## 198 18 36632302 rs75323193 G T 0.8942029 -0.9276155 0.1934680
## 199 18 36633245 rs79091544 G C 0.8942029 -0.9276155 0.1934680
## 200 18 36633326 rs79603670 G A 0.8942029 -0.9276155 0.1934680
## 201 18 36633458 rs16968087 G A 0.8942029 -0.9276155 0.1934680
## 202 18 36633546 rs74583186 A G 0.8942029 -0.9276155 0.1934680
## 203 18 36635242 rs8085903 T C 0.8942029 -0.9276155 0.1934680
## 204 18 36635439 rs8086052 G A 0.8942029 -0.9276155 0.1934680
## 205 18 36636441 rs1565976 G A 0.8985507 -0.8944593 0.1964448
## 206 18 36636541 rs11660710 G A 0.8985507 -0.8944593 0.1964448
## 207 18 36637747 rs2848921 T C 0.8985507 -0.8944593 0.1964448
## 208 18 36637790 rs2644258 T C 0.8985507 -0.8944593 0.1964448
## 209 18 36638574 rs990462 A G 0.8985507 -0.8944593 0.1964448
## 210 19 50403272 rs1673043 A G 0.9463768 -1.2671199 0.2337885
## 211 19 50410704 rs1673037 G T 0.9463768 -1.2671199 0.2337885
## 212 19 50411356 rs2445830 C T 0.9463768 -1.2671199 0.2337885
## 213 19 50416571 rs3218760 G A 0.9463768 -1.2671199 0.2337885
## 214 19 50418015 rs2445837 C T 0.9463768 -1.2671199 0.2337885
## 215 20 8549239 rs6039190 C T 0.6072464 -0.6575422 0.1459235
## 216 20 8582435 rs12624339 G A 0.8550725 -0.9444111 0.1745442
## 217 20 8582919 rs57379040 A G 0.8550725 -0.9444111 0.1745442
## 218 20 8584320 rs6055922 G A 0.7695652 -0.6873243 0.1498391
## 219 20 8586504 rs6055928 A G 0.7000000 -0.7705549 0.1424458
## 220 20 8586872 rs6086518 G A 0.6753623 -0.7003448 0.1445490
## 221 20 8608924 rs6055944 G A 0.8594203 -0.8320014 0.1758258
## 222 21 26973633 rs2830592 A G 0.7869565 -0.8156619 0.1719187
## 223 21 27012210 rs9983987 A G 0.8347826 -0.9531290 0.1774854
## 224 21 27013043 rs977152 A G 0.8333333 -0.9779213 0.1770009
## p
## 1 1.936695e-08
## 2 1.493256e-07
## 3 6.102537e-07
## 4 1.946743e-07
## 5 1.344928e-07
## 6 3.852095e-08
## 7 2.637867e-06
## 8 5.971731e-06
## 9 5.971731e-06
## 10 3.695170e-07
## 11 3.695170e-07
## 12 1.891003e-06
## 13 1.891003e-06
## 14 1.891003e-06
## 15 2.637867e-06
## 16 2.637867e-06
## 17 9.704918e-07
## 18 1.008665e-07
## 19 1.008665e-07
## 20 1.008665e-07
## 21 1.008665e-07
## 22 1.008665e-07
## 23 1.008665e-07
## 24 5.257910e-06
## 25 5.257910e-06
## 26 5.257910e-06
## 27 5.257910e-06
## 28 5.257910e-06
## 29 5.257910e-06
## 30 5.257910e-06
## 31 5.257910e-06
## 32 5.257910e-06
## 33 5.257910e-06
## 34 5.257910e-06
## 35 5.257910e-06
## 36 5.257910e-06
## 37 5.257910e-06
## 38 5.257910e-06
## 39 5.257910e-06
## 40 5.257910e-06
## 41 5.257910e-06
## 42 5.257910e-06
## 43 5.257910e-06
## 44 5.257910e-06
## 45 5.257910e-06
## 46 5.257910e-06
## 47 3.149705e-06
## 48 4.227633e-06
## 49 3.599351e-08
## 50 7.761227e-06
## 51 6.549984e-06
## 52 6.549984e-06
## 53 6.549984e-06
## 54 6.549984e-06
## 55 6.549984e-06
## 56 6.549984e-06
## 57 6.549984e-06
## 58 6.549984e-06
## 59 6.549984e-06
## 60 6.549984e-06
## 61 6.549984e-06
## 62 5.919095e-06
## 63 5.026116e-08
## 64 2.156164e-08
## 65 1.375737e-08
## 66 2.156164e-08
## 67 5.097389e-08
## 68 1.375737e-08
## 69 2.156164e-08
## 70 1.375737e-08
## 71 2.156164e-08
## 72 2.156164e-08
## 73 2.156164e-08
## 74 3.789911e-07
## 75 2.156164e-08
## 76 2.156164e-08
## 77 2.156164e-08
## 78 2.156164e-08
## 79 2.156164e-08
## 80 2.156164e-08
## 81 2.156164e-08
## 82 2.156164e-08
## 83 2.156164e-08
## 84 2.156164e-08
## 85 2.156164e-08
## 86 2.156164e-08
## 87 2.156164e-08
## 88 2.156164e-08
## 89 7.129872e-06
## 90 3.228912e-07
## 91 2.647433e-07
## 92 2.647433e-07
## 93 7.024329e-08
## 94 5.363131e-08
## 95 7.024329e-08
## 96 7.024329e-08
## 97 7.024329e-08
## 98 2.919620e-07
## 99 4.197314e-08
## 100 2.919620e-07
## 101 4.229997e-08
## 102 4.777709e-07
## 103 7.042405e-08
## 104 4.777709e-07
## 105 7.042405e-08
## 106 9.598444e-07
## 107 1.727827e-07
## 108 1.243749e-07
## 109 3.082558e-06
## 110 1.243749e-07
## 111 1.243749e-07
## 112 1.349188e-06
## 113 2.069471e-06
## 114 2.330892e-07
## 115 1.146932e-06
## 116 2.185141e-06
## 117 2.069471e-06
## 118 2.069471e-06
## 119 2.069471e-06
## 120 1.146932e-06
## 121 1.146932e-06
## 122 1.146932e-06
## 123 1.146932e-06
## 124 1.146932e-06
## 125 1.146932e-06
## 126 1.627147e-08
## 127 5.580659e-07
## 128 5.580659e-07
## 129 5.580659e-07
## 130 5.580659e-07
## 131 5.580659e-07
## 132 5.580659e-07
## 133 5.580659e-07
## 134 5.580659e-07
## 135 5.580659e-07
## 136 1.634876e-07
## 137 2.941044e-08
## 138 2.941044e-08
## 139 2.692761e-08
## 140 8.422516e-07
## 141 7.311630e-07
## 142 3.427418e-08
## 143 7.311630e-07
## 144 7.311630e-07
## 145 3.466265e-08
## 146 7.311630e-07
## 147 7.311630e-07
## 148 5.949563e-07
## 149 4.769174e-08
## 150 5.949563e-07
## 151 1.673115e-07
## 152 4.643702e-07
## 153 1.136822e-07
## 154 3.027878e-06
## 155 3.027878e-06
## 156 3.027878e-06
## 157 3.027878e-06
## 158 3.027878e-06
## 159 3.027878e-06
## 160 3.027878e-06
## 161 3.027878e-06
## 162 3.027878e-06
## 163 3.027878e-06
## 164 1.819387e-07
## 165 3.763762e-06
## 166 3.763762e-06
## 167 3.763762e-06
## 168 3.763762e-06
## 169 3.763762e-06
## 170 3.763762e-06
## 171 3.763762e-06
## 172 3.763762e-06
## 173 3.763762e-06
## 174 3.763762e-06
## 175 3.763762e-06
## 176 4.828536e-08
## 177 4.828536e-08
## 178 4.828536e-08
## 179 4.828536e-08
## 180 4.828536e-08
## 181 4.828536e-08
## 182 4.828536e-08
## 183 8.816423e-08
## 184 8.816423e-08
## 185 8.816423e-08
## 186 5.462697e-07
## 187 2.443567e-06
## 188 1.354600e-07
## 189 2.443567e-06
## 190 7.375822e-06
## 191 7.375822e-06
## 192 2.443567e-06
## 193 7.375822e-06
## 194 7.375822e-06
## 195 2.443567e-06
## 196 2.443567e-06
## 197 2.443567e-06
## 198 2.443567e-06
## 199 2.443567e-06
## 200 2.443567e-06
## 201 2.443567e-06
## 202 2.443567e-06
## 203 2.443567e-06
## 204 2.443567e-06
## 205 7.375822e-06
## 206 7.375822e-06
## 207 7.375822e-06
## 208 7.375822e-06
## 209 7.375822e-06
## 210 1.133853e-07
## 211 1.133853e-07
## 212 1.133853e-07
## 213 1.133853e-07
## 214 1.133853e-07
## 215 9.103186e-06
## 216 1.188889e-07
## 217 1.188889e-07
## 218 6.335011e-06
## 219 1.196643e-07
## 220 1.929486e-06
## 221 3.269982e-06
## 222 3.086274e-06
## 223 1.463444e-07
## 224 6.577593e-086. PC3
pc3_wald_gwas <- association.test(merged_nies_210818, nies_heritable_pheno240918$coord.Dim.3, X = nies_covar, method="lm", test = "wald", response = "quantitative", K = merged_nies_GRM, eigenK = merged_nies_eiK, p = 2)## Warning in trans.X(X, mean.y = mean(Y)): An intercept column was added to
## the covariate matrix Xpc3_wald_gwas <- na.omit(pc3_wald_gwas)
pc3_wfiltered <- pc3_wald_gwas %>% filter(-log10(p)>1) %>% filter(freqA2 < 0.99)
pc3_wmeff <- pc3_wfiltered %>% filter(p < 1.84e-7)
pc3_wsig <- do.call(rbind, lapply(split(pc3_wmeff,pc3_wmeff$chr), function(x) {return(x[which.min(x$p),])}))
pc3_wres <- NULL
for (i in pc3_wsig$id) {
snpID <- i
snpCHR <- pc3_wfiltered[pc3_wfiltered$id == snpID,]$chr
snpPOS <- pc3_wfiltered[pc3_wfiltered$id ==snpID,]$pos
sig.peak <- pc3_wfiltered %>%
filter(chr == snpCHR) %>%
filter(pos > snpPOS - 50000) %>%
filter(pos < snpPOS + 50000) %>%
filter(p < 1e-5)
pc3_wres <- rbind(pc3_wres, sig.peak)
}
write.csv(pc3_wres, 'C:/Users/Martha/Documents/Honours/Project/honours.project/Data/gwas_filter_covar/pc3_wald_res.csv')
pc3_wres## chr pos id A1 A2 freqA2 beta sd
## 1 1 205916566 rs72752923 C A 0.9782609 -2.555298 0.4025047
## 2 1 205916729 rs16830364 G A 0.9782609 -2.555298 0.4025047
## 3 1 205916931 rs60255052 C T 0.9811594 -2.959985 0.4226675
## 4 1 205917041 rs60716530 C T 0.9782609 -2.555298 0.4025047
## 5 1 205917115 rs60644810 G A 0.9782609 -2.555298 0.4025047
## 6 1 205917248 rs35694044 A T 0.9782609 -2.555298 0.4025047
## 7 1 205917652 rs16830370 T C 0.9782609 -2.555298 0.4025047
## 8 1 205918853 rs16856462 C T 0.9782609 -2.555298 0.4025047
## 9 1 205919195 rs16856468 G A 0.9782609 -2.555298 0.4025047
## 10 1 205919303 rs60001177 T C 0.9782609 -2.555298 0.4025047
## 11 1 205919401 rs12723666 A G 0.9782609 -2.555298 0.4025047
## 12 1 205920201 rs16856470 T C 0.9811594 -2.959985 0.4226675
## 13 1 205920404 rs16856473 A G 0.9811594 -2.959985 0.4226675
## 14 1 205922403 rs68189466 G A 0.9797101 -2.827531 0.4119262
## 15 1 205922720 rs35648260 G T 0.9797101 -2.827531 0.4119262
## 16 1 205922775 rs35360452 G T 0.9797101 -2.827531 0.4119262
## 17 1 205925474 rs12727528 A G 0.9797101 -2.827531 0.4119262
## 18 1 205935183 rs1891309 G A 0.9782609 -2.619719 0.4026668
## 19 1 205935330 rs1891310 T G 0.9782609 -2.619719 0.4026668
## 20 1 205936240 rs1473537 T C 0.9739130 -2.169598 0.3762565
## 21 1 205942026 rs72752928 T C 0.9782609 -2.619719 0.4026668
## 22 1 205943691 rs66593238 T C 0.9782609 -2.619719 0.4026668
## 23 1 205944627 rs9438407 T G 0.9782609 -2.619719 0.4026668
## 24 1 205945388 rs12741299 T C 0.9782609 -2.619719 0.4026668
## 25 1 205946647 rs34265780 T C 0.9782609 -2.619719 0.4026668
## 26 2 131577086 rs151117086 T C 0.9884058 -3.217951 0.5186455
## 27 3 42006157 rs71315517 G C 0.9869565 -3.041892 0.5038856
## 28 4 119321195 rs77203710 A G 0.9855072 -3.372387 0.4694447
## 29 4 119322197 rs1397614 T C 0.9855072 -3.372387 0.4694447
## 30 4 119362510 rs112314510 A G 0.9855072 -3.372387 0.4694447
## 31 4 119362552 rs111968273 T A 0.9855072 -3.372387 0.4694447
## 32 4 119367677 rs113059419 A G 0.9869565 -3.747963 0.4832128
## 33 4 119372303 rs112760591 G A 0.9855072 -3.372387 0.4694447
## 34 4 119372480 rs111609258 C G 0.9855072 -3.372387 0.4694447
## 35 4 119378224 rs147602981 G A 0.9855072 -3.372387 0.4694447
## 36 4 119381167 rs143847948 A C 0.9855072 -3.372387 0.4694447
## 37 4 119390257 rs113224532 T C 0.9855072 -3.372387 0.4694447
## 38 4 119392279 rs117856633 C A 0.9855072 -3.372387 0.4694447
## 39 4 119398681 rs113825627 C G 0.9855072 -3.372387 0.4694447
## 40 4 119403429 rs112414671 A G 0.9869565 -3.747963 0.4832128
## 41 4 119403485 rs185357281 A G 0.9869565 -3.021618 0.5000945
## 42 4 119404439 rs183181597 A G 0.9855072 -3.372387 0.4694447
## 43 4 119404927 rs113317707 C A 0.9855072 -3.372387 0.4694447
## 44 4 119408454 rs184703141 T C 0.9855072 -3.372387 0.4694447
## 45 5 25293191 rs138955515 A G 0.9855072 -3.035716 0.4768751
## 46 5 25300269 rs140158697 C T 0.9855072 -3.035716 0.4768751
## 47 5 25331088 rs114133913 T A 0.9855072 -3.035716 0.4768751
## 48 6 121261079 rs116936384 G C 0.9898551 -3.678807 0.6195338
## 49 7 65064421 rs187018641 T A 0.9884058 -3.166156 0.5930444
## 50 8 80306741 rs111864836 G T 0.9884058 -4.199841 0.5725396
## 51 8 80306859 rs113627660 G C 0.9884058 -4.199841 0.5725396
## 52 8 80306990 rs7825643 G T 0.9724638 -1.805367 0.3954829
## 53 8 80307293 rs7845792 A G 0.9884058 -4.199841 0.5725396
## 54 8 80307388 rs7845575 G A 0.9869565 -3.536816 0.5481756
## 55 8 80307700 rs114654811 C T 0.9884058 -4.199841 0.5725396
## 56 8 80307701 rs115278078 A T 0.9884058 -4.199841 0.5725396
## 57 8 80307837 rs79018076 T C 0.9884058 -4.199841 0.5725396
## 58 8 80308098 rs112501384 G C 0.9884058 -4.199841 0.5725396
## 59 8 80309142 rs60539023 G A 0.9724638 -1.805367 0.3954829
## 60 8 80309305 rs11996376 A G 0.9884058 -4.199841 0.5725396
## 61 8 80309598 rs79431653 C G 0.9884058 -4.199841 0.5725396
## 62 8 80309626 rs11996450 T C 0.9884058 -4.199841 0.5725396
## 63 8 80310193 rs60741023 C G 0.9884058 -4.199841 0.5725396
## 64 8 80310485 rs7844286 C T 0.9884058 -4.199841 0.5725396
## 65 8 80310716 rs7844696 A T 0.9884058 -4.199841 0.5725396
## 66 8 80310720 rs7826434 G A 0.9884058 -4.199841 0.5725396
## 67 8 80311242 rs80031189 C T 0.9884058 -4.199841 0.5725396
## 68 8 80311252 rs113823684 A G 0.9884058 -4.199841 0.5725396
## 69 8 80311311 rs61300312 A C 0.9724638 -1.805367 0.3954829
## 70 8 80311329 rs142907856 A G 0.9884058 -4.199841 0.5725396
## 71 8 80311457 rs112582272 A G 0.9884058 -4.199841 0.5725396
## 72 8 80311580 rs116773209 G A 0.9884058 -4.199841 0.5725396
## 73 8 80311736 rs113314270 G T 0.9884058 -4.199841 0.5725396
## 74 8 80311746 rs73261635 G A 0.9724638 -1.805367 0.3954829
## 75 8 80311838 rs117693425 A G 0.9884058 -4.199841 0.5725396
## 76 8 80312291 rs11988873 C T 0.9884058 -4.199841 0.5725396
## 77 8 80312345 rs11988904 A T 0.9884058 -4.199841 0.5725396
## 78 8 80312623 rs36051398 A C 0.9884058 -4.199841 0.5725396
## 79 8 80313237 rs73261640 G A 0.9724638 -1.805367 0.3954829
## 80 8 80313751 rs114426401 T C 0.9884058 -4.199841 0.5725396
## 81 8 80314228 rs74981396 G A 0.9884058 -4.199841 0.5725396
## 82 8 80317028 rs11998344 T G 0.9884058 -4.199841 0.5725396
## 83 8 80317208 rs113244900 C T 0.9884058 -4.199841 0.5725396
## 84 8 80318583 rs57246091 A G 0.9884058 -4.199841 0.5725396
## 85 8 80318643 rs113901603 G A 0.9884058 -4.199841 0.5725396
## 86 8 80319691 rs113718590 A G 0.9884058 -4.199841 0.5725396
## 87 8 80319794 rs111833373 C T 0.9724638 -1.805367 0.3954829
## 88 8 80320713 rs11987997 A G 0.9884058 -4.199841 0.5725396
## 89 8 80321002 rs111527437 T A 0.9884058 -4.199841 0.5725396
## 90 8 80321694 rs112815920 G C 0.9884058 -4.199841 0.5725396
## 91 8 80323890 rs11998156 C A 0.9884058 -4.199841 0.5725396
## 92 8 80323964 rs16907573 G A 0.9884058 -4.199841 0.5725396
## 93 8 80324156 rs111257240 C T 0.9884058 -4.199841 0.5725396
## 94 8 80325047 rs113437388 T C 0.9884058 -4.199841 0.5725396
## 95 8 80325311 rs73261674 G C 0.9724638 -1.805367 0.3954829
## 96 8 80326033 rs111370206 G A 0.9884058 -4.199841 0.5725396
## 97 8 80326181 rs73261679 A C 0.9724638 -1.805367 0.3954829
## 98 8 80326935 rs147955676 A G 0.9884058 -4.199841 0.5725396
## 99 8 80326985 rs61039050 A C 0.9724638 -1.805367 0.3954829
## 100 8 80327347 rs7840954 C T 0.9724638 -1.805367 0.3954829
## 101 8 80327348 rs7822886 A G 0.9724638 -1.805367 0.3954829
## 102 8 80327442 rs7841095 C T 0.9884058 -4.199841 0.5725396
## 103 8 80327549 rs7822828 C A 0.9884058 -4.199841 0.5725396
## 104 8 80327674 rs7841418 C T 0.9724638 -1.805367 0.3954829
## 105 8 80327732 rs7823481 C G 0.9884058 -4.199841 0.5725396
## 106 8 80328450 rs11990649 A G 0.9884058 -4.199841 0.5725396
## 107 8 80329801 rs56960849 A G 0.9884058 -4.199841 0.5725396
## 108 8 80330197 rs11995624 C T 0.9884058 -4.199841 0.5725396
## 109 8 80330467 rs7837761 A G 0.9869565 -3.536816 0.5481756
## 110 8 80332180 rs113042618 T C 0.9884058 -4.199841 0.5725396
## 111 8 80332423 rs7001142 G T 0.9884058 -4.199841 0.5725396
## 112 8 80332520 rs6980915 G A 0.9884058 -4.199841 0.5725396
## 113 8 80332901 rs6473220 T C 0.9884058 -4.199841 0.5725396
## 114 8 80332907 rs6473221 A G 0.9884058 -4.199841 0.5725396
## 115 8 80333316 rs7835862 C T 0.9884058 -4.199841 0.5725396
## 116 8 80333340 rs7817696 A G 0.9884058 -4.199841 0.5725396
## 117 8 80333506 rs7817634 T C 0.9884058 -4.199841 0.5725396
## 118 8 80333599 rs57419267 C T 0.9884058 -4.199841 0.5725396
## 119 8 80333823 rs59130219 C T 0.9884058 -4.199841 0.5725396
## 120 8 80334098 rs73691385 T A 0.9884058 -4.199841 0.5725396
## 121 8 80334328 rs7840559 C T 0.9884058 -4.199841 0.5725396
## 122 8 80334334 rs7822177 G A 0.9884058 -4.199841 0.5725396
## 123 8 80334582 rs111631456 A G 0.9884058 -4.199841 0.5725396
## 124 8 80334982 rs58109903 T C 0.9884058 -4.199841 0.5725396
## 125 8 80335583 rs73691388 G A 0.9884058 -4.199841 0.5725396
## 126 8 80336124 rs7837108 T C 0.9884058 -4.199841 0.5725396
## 127 8 80336300 rs7840857 T G 0.9884058 -4.199841 0.5725396
## 128 8 80336310 rs7840861 T G 0.9884058 -4.199841 0.5725396
## 129 8 80337292 rs111888115 T C 0.9884058 -4.199841 0.5725396
## 130 8 80337308 rs56871558 T C 0.9884058 -4.199841 0.5725396
## 131 8 80337408 rs56116331 A G 0.9884058 -4.199841 0.5725396
## 132 8 80337443 rs58592997 T C 0.9884058 -4.199841 0.5725396
## 133 8 80337629 rs76783901 A G 0.9884058 -4.199841 0.5725396
## 134 8 80337634 rs74468856 G A 0.9884058 -4.199841 0.5725396
## 135 8 80337985 rs73691394 C A 0.9884058 -4.199841 0.5725396
## 136 8 80338076 rs73691395 T C 0.9884058 -4.199841 0.5725396
## 137 8 80338219 rs73691397 C G 0.9884058 -4.199841 0.5725396
## 138 8 80338255 rs73691398 G A 0.9884058 -4.199841 0.5725396
## 139 8 80338835 rs58958046 A G 0.9884058 -4.199841 0.5725396
## 140 8 80338910 rs58786240 C T 0.9884058 -4.199841 0.5725396
## 141 8 80338955 rs76867788 C T 0.9884058 -4.199841 0.5725396
## 142 8 80339017 rs73691399 T C 0.9884058 -4.199841 0.5725396
## 143 8 80339217 rs73691400 C G 0.9884058 -4.199841 0.5725396
## 144 8 80339959 rs61233095 C A 0.9884058 -4.199841 0.5725396
## 145 8 80340238 rs56408864 A T 0.9884058 -4.199841 0.5725396
## 146 8 80340749 rs7826667 A G 0.9884058 -4.199841 0.5725396
## 147 8 80341236 rs7000592 G C 0.9884058 -4.199841 0.5725396
## 148 10 25947431 rs144363867 G A 0.9565217 -1.684966 0.3067035
## 149 12 5987972 rs142100550 T G 0.9884058 -3.862914 0.5751795
## 150 14 82730166 rs139045884 A G 0.9826087 -2.639915 0.4897466
## 151 14 82743030 rs117385547 C T 0.9840580 -3.002400 0.5069886
## 152 16 63440590 rs141104955 G C 0.9898551 -3.424795 0.6265245
## 153 18 48847895 rs11665050 A G 0.9782609 -2.160804 0.4355790
## 154 18 48849360 rs141608868 C G 0.9782609 -2.160804 0.4355790
## 155 18 48850433 rs78852912 C G 0.9782609 -2.160804 0.4355790
## 156 18 48853167 rs151115377 A G 0.9840580 -2.946344 0.5003625
## 157 18 48855955 rs143153469 A G 0.9782609 -2.160804 0.4355790
## 158 18 48858545 rs117947063 G A 0.9782609 -2.160804 0.4355790
## 159 19 54022720 rs12460863 G A 0.9884058 -3.276104 0.5884045
## 160 19 54028461 rs117249591 G A 0.9884058 -3.276104 0.5884045
## 161 20 2977131 rs145336914 G C 0.9753623 -2.435610 0.4120601
## 162 20 2979974 rs141744903 G A 0.9681159 -1.719531 0.3783060
## 163 20 2985515 rs6138975 C T 0.9681159 -1.719531 0.3783060
## 164 20 2987464 rs74893620 A G 0.9681159 -1.719531 0.3783060
## 165 20 2994423 rs60040561 T G 0.9681159 -1.719531 0.3783060
## 166 20 2998407 rs78221943 G A 0.9681159 -1.719531 0.3783060
## 167 20 3004167 rs58156936 C A 0.9681159 -1.719531 0.3783060
## 168 20 3004208 rs146526220 A G 0.9681159 -1.719531 0.3783060
## 169 20 3004309 rs6132999 T C 0.9681159 -1.719531 0.3783060
## 170 20 3004313 rs6133000 T C 0.9681159 -1.719531 0.3783060
## 171 20 3004887 rs3746692 A C 0.9681159 -1.719531 0.3783060
## 172 20 3006691 rs6138976 T G 0.9681159 -1.719531 0.3783060
## 173 20 3009458 rs75990124 T G 0.9681159 -1.719531 0.3783060
## 174 20 3009687 rs6138979 A G 0.9681159 -1.719531 0.3783060
## 175 20 3011439 rs16988201 T C 0.9681159 -1.719531 0.3783060
## 176 20 3013926 rs6133003 G A 0.9681159 -1.719531 0.3783060
## 177 22 44078144 rs11705487 T C 0.9753623 -2.305982 0.4103061
## 178 22 44088452 rs147207731 A G 0.9797101 -2.851280 0.4413914
## p
## 1 7.001916e-10
## 2 7.001916e-10
## 3 1.357929e-11
## 4 7.001916e-10
## 5 7.001916e-10
## 6 7.001916e-10
## 7 7.001916e-10
## 8 7.001916e-10
## 9 7.001916e-10
## 10 7.001916e-10
## 11 7.001916e-10
## 12 1.357929e-11
## 13 1.357929e-11
## 14 3.209486e-11
## 15 3.209486e-11
## 16 3.209486e-11
## 17 3.209486e-11
## 18 2.783688e-10
## 19 2.783688e-10
## 20 1.829230e-08
## 21 2.783688e-10
## 22 2.783688e-10
## 23 2.783688e-10
## 24 2.783688e-10
## 25 2.783688e-10
## 26 1.603783e-09
## 27 4.135107e-09
## 28 4.356927e-12
## 29 4.356927e-12
## 30 4.356927e-12
## 31 4.356927e-12
## 32 1.041495e-13
## 33 4.356927e-12
## 34 4.356927e-12
## 35 4.356927e-12
## 36 4.356927e-12
## 37 4.356927e-12
## 38 4.356927e-12
## 39 4.356927e-12
## 40 1.041495e-13
## 41 4.016047e-09
## 42 4.356927e-12
## 43 4.356927e-12
## 44 4.356927e-12
## 45 6.329954e-10
## 46 6.329954e-10
## 47 6.329954e-10
## 48 7.161380e-09
## 49 1.720121e-07
## 50 1.651718e-12
## 51 1.651718e-12
## 52 7.004363e-06
## 53 1.651718e-12
## 54 3.825693e-10
## 55 1.651718e-12
## 56 1.651718e-12
## 57 1.651718e-12
## 58 1.651718e-12
## 59 7.004363e-06
## 60 1.651718e-12
## 61 1.651718e-12
## 62 1.651718e-12
## 63 1.651718e-12
## 64 1.651718e-12
## 65 1.651718e-12
## 66 1.651718e-12
## 67 1.651718e-12
## 68 1.651718e-12
## 69 7.004363e-06
## 70 1.651718e-12
## 71 1.651718e-12
## 72 1.651718e-12
## 73 1.651718e-12
## 74 7.004363e-06
## 75 1.651718e-12
## 76 1.651718e-12
## 77 1.651718e-12
## 78 1.651718e-12
## 79 7.004363e-06
## 80 1.651718e-12
## 81 1.651718e-12
## 82 1.651718e-12
## 83 1.651718e-12
## 84 1.651718e-12
## 85 1.651718e-12
## 86 1.651718e-12
## 87 7.004363e-06
## 88 1.651718e-12
## 89 1.651718e-12
## 90 1.651718e-12
## 91 1.651718e-12
## 92 1.651718e-12
## 93 1.651718e-12
## 94 1.651718e-12
## 95 7.004363e-06
## 96 1.651718e-12
## 97 7.004363e-06
## 98 1.651718e-12
## 99 7.004363e-06
## 100 7.004363e-06
## 101 7.004363e-06
## 102 1.651718e-12
## 103 1.651718e-12
## 104 7.004363e-06
## 105 1.651718e-12
## 106 1.651718e-12
## 107 1.651718e-12
## 108 1.651718e-12
## 109 3.825693e-10
## 110 1.651718e-12
## 111 1.651718e-12
## 112 1.651718e-12
## 113 1.651718e-12
## 114 1.651718e-12
## 115 1.651718e-12
## 116 1.651718e-12
## 117 1.651718e-12
## 118 1.651718e-12
## 119 1.651718e-12
## 120 1.651718e-12
## 121 1.651718e-12
## 122 1.651718e-12
## 123 1.651718e-12
## 124 1.651718e-12
## 125 1.651718e-12
## 126 1.651718e-12
## 127 1.651718e-12
## 128 1.651718e-12
## 129 1.651718e-12
## 130 1.651718e-12
## 131 1.651718e-12
## 132 1.651718e-12
## 133 1.651718e-12
## 134 1.651718e-12
## 135 1.651718e-12
## 136 1.651718e-12
## 137 1.651718e-12
## 138 1.651718e-12
## 139 1.651718e-12
## 140 1.651718e-12
## 141 1.651718e-12
## 142 1.651718e-12
## 143 1.651718e-12
## 144 1.651718e-12
## 145 1.651718e-12
## 146 1.651718e-12
## 147 1.651718e-12
## 148 7.752192e-08
## 149 7.922242e-11
## 150 1.322154e-07
## 151 7.822048e-09
## 152 8.939492e-08
## 153 1.114404e-06
## 154 1.114404e-06
## 155 1.114404e-06
## 156 9.409415e-09
## 157 1.114404e-06
## 158 1.114404e-06
## 159 5.265926e-08
## 160 5.265926e-08
## 161 8.320200e-09
## 162 7.648313e-06
## 163 7.648313e-06
## 164 7.648313e-06
## 165 7.648313e-06
## 166 7.648313e-06
## 167 7.648313e-06
## 168 7.648313e-06
## 169 7.648313e-06
## 170 7.648313e-06
## 171 7.648313e-06
## 172 7.648313e-06
## 173 7.648313e-06
## 174 7.648313e-06
## 175 7.648313e-06
## 176 7.648313e-06
## 177 3.995030e-08
## 178 3.654696e-107. PC4
pc4_wald_gwas <- association.test(merged_nies_210818, nies_heritable_pheno240918$coord.Dim.4, X = nies_covar, method="lm", test = "wald", response = "quantitative", K = merged_nies_GRM, eigenK = merged_nies_eiK, p = 2)
pc4_wald_gwas <- na.omit(pc4_wald_gwas)
pc4_wfiltered <- pc4_wald_gwas %>% filter(-log10(p)>1) %>% filter(freqA2 < 0.99)
pc4_wmeff <- pc4_wfiltered %>% filter(p < 1.84e-7)
pc4_wsig <- do.call(rbind, lapply(split(pc4_wmeff,pc4_wmeff$chr), function(x) {return(x[which.min(x$p),])}))
pc4_wres <- NULL
for (i in pc4_wsig$id) {
snpID <- i
snpCHR <- pc4_wfiltered[pc4_wfiltered$id == snpID,]$chr
snpPOS <- pc4_wfiltered[pc4_wfiltered$id ==snpID,]$pos
sig.peak <- pc4_wfiltered %>%
filter(chr == snpCHR) %>%
filter(pos > snpPOS - 50000) %>%
filter(pos < snpPOS + 50000) %>%
filter(p < 1e-5)
pc4_wres <- rbind(pc4_wres, sig.peak)
}
write.csv(pc4_wfiltered, 'C:/Users/Martha/Documents/Honours/Project/honours.project/Data/gwas_filter_covar/pc4_wald_filter.csv')
pc4_wres## NULLmanhattan(x = pc4_wfiltered, chr = "chr", bp = "pos", p = "p", snp = "id", ylim = c(0,12), genomewideline = -log10(1.84e-7), main = "Component 4")
8. PC8
pc8_wald_gwas <- association.test(merged_nies_210818, nies_heritable_pheno240918$coord.Dim.8, X = nies_covar, method="lm", test = "wald", response = "quantitative", K = merged_nies_GRM, eigenK = merged_nies_eiK, p = 2)## Warning in trans.X(X, mean.y = mean(Y)): An intercept column was added to
## the covariate matrix Xpc8_wald_gwas <- na.omit(pc8_wald_gwas)
pc8_wfiltered <- pc8_wald_gwas %>% filter(-log10(p)>1) %>% filter(freqA2 < 0.99)
pc8_wmeff <- pc8_wfiltered %>% filter(p < 1.84e-7)
pc8_wsig <- do.call(rbind, lapply(split(pc8_wmeff,pc8_wmeff$chr), function(x) {return(x[which.min(x$p),])}))
pc8_wres <- NULL
for (i in pc8_wsig$id) {
snpID <- i
snpCHR <- pc8_wfiltered[pc8_wfiltered$id == snpID,]$chr
snpPOS <- pc8_wfiltered[pc8_wfiltered$id ==snpID,]$pos
sig.peak <- pc8_wfiltered %>%
filter(chr == snpCHR) %>%
filter(pos > snpPOS - 50000) %>%
filter(pos < snpPOS + 50000) %>%
filter(p < 1e-5)
pc8_wres <- rbind(pc8_wres, sig.peak)
}
write.csv(pc8_wres, 'C:/Users/Martha/Documents/Honours/Project/honours.project/Data/gwas_filter_covar/pc8_wald_res.csv')
pc8_wres## chr pos id A1 A2 freqA2 beta sd
## 1 2 147529465 rs1438873 T C 0.5231884 -0.4168333 0.07894971
## 2 2 147529616 rs6710858 T A 0.5231884 -0.4168333 0.07894971
## 3 2 147530296 rs6753791 C G 0.5231884 -0.4168333 0.07894971
## 4 2 147530428 rs12469553 C T 0.5927536 0.3747363 0.07965598
## 5 2 147531132 rs4145334 T C 0.5927536 0.3747363 0.07965598
## 6 2 147531215 rs1347827 C G 0.5231884 -0.4168333 0.07894971
## 7 2 147532048 rs4662523 A T 0.5231884 -0.4168333 0.07894971
## 8 2 147532877 rs1438875 T C 0.5231884 -0.4168333 0.07894971
## 9 2 147534397 rs12691757 G A 0.5231884 -0.4168333 0.07894971
## 10 2 147534556 rs12691758 T G 0.5231884 -0.4168333 0.07894971
## 11 2 147539904 rs11680551 C T 0.5985507 0.3826837 0.07982540
## 12 2 147541431 rs4508547 A T 0.5985507 0.3826837 0.07982540
## 13 2 147545563 rs1550320 C A 0.5985507 0.3826837 0.07982540
## 14 2 147545749 rs1550319 T C 0.5985507 0.3826837 0.07982540
## 15 2 147546686 rs13390421 A G 0.5985507 0.3826837 0.07982540
## 16 2 147547000 rs13390757 A G 0.5985507 0.3826837 0.07982540
## 17 2 147548196 rs17724539 C T 0.5985507 0.3826837 0.07982540
## 18 2 147548936 rs6430197 C T 0.5985507 0.3826837 0.07982540
## 19 2 147549509 rs7588634 G A 0.5985507 0.3826837 0.07982540
## 20 2 147550185 rs17724612 G A 0.5985507 0.3826837 0.07982540
## 21 2 147550211 rs17673675 C T 0.5985507 0.3826837 0.07982540
## 22 2 147550250 rs17673688 G A 0.5985507 0.3826837 0.07982540
## 23 2 147550602 rs10208724 G A 0.5985507 0.3826837 0.07982540
## 24 2 147550839 rs10208983 G A 0.5985507 0.3826837 0.07982540
## 25 2 147551751 rs11691040 C T 0.5985507 0.3826837 0.07982540
## 26 2 147551802 rs11674017 G A 0.5985507 0.3826837 0.07982540
## 27 2 147552307 rs10201767 A T 0.5985507 0.3826837 0.07982540
## 28 2 147552592 rs7590223 C T 0.5985507 0.3826837 0.07982540
## 29 2 147571339 rs13413754 C A 0.5840580 0.4066055 0.08155988
## 30 2 147571830 rs13404881 C T 0.5840580 0.4066055 0.08155988
## 31 2 147572239 rs12691759 G A 0.5565217 0.4365917 0.07989172
## 32 2 147573800 rs4361065 A G 0.5855072 0.4051134 0.08132119
## 33 2 147579262 rs1550316 C T 0.5927536 0.4234348 0.08157517
## 34 2 147579526 rs11681804 A C 0.5927536 0.4234348 0.08157517
## 35 2 147579844 rs12477396 G A 0.5927536 0.4234348 0.08157517
## 36 2 147579987 rs12473660 C T 0.5927536 0.4234348 0.08157517
## 37 2 147580536 rs2033825 A G 0.5927536 0.4234348 0.08157517
## 38 9 108250136 rs1332299 C T 0.7855072 0.4383475 0.09741950
## 39 9 108252016 rs7025969 G C 0.7855072 0.4383475 0.09741950
## 40 9 108296877 rs10979308 A T 0.8072464 0.5024661 0.09973708
## 41 9 108299426 rs1885973 T A 0.7768116 0.5342126 0.09480874
## 42 9 108300235 rs10816656 G A 0.7826087 0.5180805 0.09700395
## 43 9 108302318 rs1407849 T A 0.8057971 0.4995299 0.09868402
## 44 9 108305442 rs16912866 G A 0.7768116 0.5342126 0.09480874
## 45 9 108305644 rs16912868 G A 0.7768116 0.5342126 0.09480874
## 46 9 108306203 rs1323384 A C 0.8086957 0.4986394 0.09989172
## 47 9 108307394 rs7030371 G A 0.7768116 0.5342126 0.09480874
## p
## 1 2.319963e-07
## 2 2.319963e-07
## 3 2.319963e-07
## 4 3.716545e-06
## 5 3.716545e-06
## 6 2.319963e-07
## 7 2.319963e-07
## 8 2.319963e-07
## 9 2.319963e-07
## 10 2.319963e-07
## 11 2.453938e-06
## 12 2.453938e-06
## 13 2.453938e-06
## 14 2.453938e-06
## 15 2.453938e-06
## 16 2.453938e-06
## 17 2.453938e-06
## 18 2.453938e-06
## 19 2.453938e-06
## 20 2.453938e-06
## 21 2.453938e-06
## 22 2.453938e-06
## 23 2.453938e-06
## 24 2.453938e-06
## 25 2.453938e-06
## 26 2.453938e-06
## 27 2.453938e-06
## 28 2.453938e-06
## 29 9.901037e-07
## 30 9.901037e-07
## 31 9.011323e-08
## 32 1.007980e-06
## 33 3.622683e-07
## 34 3.622683e-07
## 35 3.622683e-07
## 36 3.622683e-07
## 37 3.622683e-07
## 38 9.377780e-06
## 39 9.377780e-06
## 40 7.678797e-07
## 41 3.699907e-08
## 42 1.702717e-07
## 43 6.832079e-07
## 44 3.699907e-08
## 45 3.699907e-08
## 46 9.598554e-07
## 47 3.699907e-08Although most of these beta values are more sensible, the UVAF values are still significantly inflated. This indicates that there may be other confounders affecting results, other than population structure, age, and sex as these have been accounted for in the model. Some options to determine the cause of this artificial inflation may include, adding more components to the model, removing low frequency variants, or performing these association tests using a different tool.