Changes

pvalue.eg &lt;- results(test.eg)$P1df[results(test.eg)$P1df < alpha] lambda.eg &lt;- test.eg@lambda snp.eg

legend("topright", c("Original plot","After correction w/ EIGENSTRAT"), pch = c(1,3))==GWAS Data QC==  plink --file GWAS --noweb plink --file GWAS --mind 0.10 --recode --out GWAS_clean_mind --noweb plink --file GWAS_clean_mind --maf 0.05 --recode --out MAF_greater_5 --noweb plink --file GWAS_clean_mind --exclude MAF_greater_5.map --recode --out MAF_less_5 --noweb plink --file MAF_greater_5 --geno 0.05 --recode --out MAF_greater_5_clean --noweb plink --file MAF_less_5 --geno 0.01 --recode --out MAF_less_5_clean --noweb plink --file MAF_greater_5_clean --merge MAF_less_5_clean.ped MAF_less_5_clean.map --recode --out GWAS_MAF_clean --noweb plink --file GWAS_MAF_clean --mind 0.03 --recode --out GWAS_clean2 --noweb plink --file GWAS_clean2 --check-sex --out GWAS_sex_checking --noweb R sexcheck = read.table("GWAS_sex_checking.sexcheck", header=T) names(sexcheck) sex_problem = sexcheck[which(sexcheck$STATUS=="PROBLEM"),] sex_problem q() plink --file GWAS_clean2 --genome --out duplicates --noweb R dups = read.table("duplicates.genome", header = T) problem_pairs = dups[which(dups$PI_HAT > 0.4),] problem_pairs problem_pairs = dups[which(dups$PI_HAT > 0.05),] myvars = c("FID1", "IID1", "FID2", "IID2", "PI_HAT") problem_pairs[myvars] q() plink --file GWAS_clean2 --remove IBS_excluded.txt --recode --out GWAS_clean3 --noweb plink --file GWAS_clean3 --het --noweb R Dataset &lt;- read.table("plink.het", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE) mean(Dataset$F) sd(Dataset$F) jpeg("hist.jpeg", height=1000, width=1000) hist(scale(Dataset$F), xlim=c(-4,4)) dev.off() q() plink --file GWAS_clean3 --pheno pheno.txt --pheno-name Aff --hardy --noweb R hardy = read.table("plink.hwe", header = T) names(hardy) hwe_prob = hardy[which(hardy$P < 0.0000009),] hwe_prob q() plink --file GWAS_clean3 --exclude HWE_out.txt --recode --out GWAS_clean4 --noweb==GWAS Control Substructure== plink --file GWAS_clean4 --genome --mds-plot 10 --noweb R mydata = read.table("mds_components.txt", header=T) mydata$pch[mydata$Group==1 ] &lt;-15 mydata$pch[mydata$Group==2 ] &lt;-16 mydata$pch[mydata$Group==3 ] &lt;-2 jpeg("mds.jpeg", height=1000, width=1000) plot(mydata$C1, mydata$C2 ,pch=mydata$pch) dev.off() q() plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --logistic --adjust --out unadj --noweb plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --covar plink.mds --covar-name C1 --logistic --adjust --out C1 --noweb plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --covar plink.mds --covar-name C1-C2 --logistic --adjust --out C1-C2 --noweb R broadqq &lt;-function(pvals, title) { &nbsp;&nbsp;&nbsp;&nbsp;observed &lt;- sort(pvals) &nbsp;&nbsp;&nbsp;&nbsp;lobs &lt;- -(log10(observed)) &nbsp;&nbsp;&nbsp;&nbsp;expected &lt;- c(1:length(observed)) &nbsp;&nbsp;&nbsp;&nbsp;lexp &lt;- -(log10(expected / (length(expected)+1))) &nbsp;&nbsp;&nbsp;&nbsp;plot(c(0,7), c(0,7), col="red", lwd=3, type="l", xlab="Expected (-logP)", ylab="Observed (-logP)", xlim=c(0,max(lobs)), ylim=c(0,max(lobs)), las=1, xaxs="i", yaxs="i", bty="l", main = title) &nbsp;&nbsp;&nbsp;&nbsp;points(lexp, lobs, pch=23, cex=.4, bg="black") } jpeg("qqplot_compare.jpeg", height=1000, width=1000) par(mfrow=c(2,1)) aff_unadj&lt;-read.table("unadj.assoc.logistic", header=TRUE) aff_unadj.add.p&lt;-aff_unadj[aff_unadj$TEST==c("ADD"),]$P broadqq(aff_unadj.add.p,"Some Trait Unadjusted") aff_C1C2&lt;-read.table("C1-C2.assoc.logistic", header=TRUE) aff_C1C2.add.p&lt;-aff_C1C2[aff_C1C2$TEST==c("ADD"),]$P broadqq(aff_C1C2.add.p, "Some Trait Adjusted") dev.off() gws_unadj = aff_unadj[which(aff_unadj$P < 0.0000001),] gws_unadj gws_adjusted = aff_C1C2[which(aff_C1C2$P < 0.0000001),] gws_adjusted q()==VAT== vtools -h vtools init VATDemo vtools import *.vcf.gz --var_info DP filter --geno_info DP_geno --build hg18 -j1 vtools liftover hg19 head phenotypes.csv vtools phenotype --from_file phenotypes.csv --delimiter "," vtools show project vtools show tables vtools show table variant vtools show samples vtools show genotypes vtools show fields vtools select variant --count vtools show genotypes &gt; GenotypeSummary.txt head GenotypeSummary.txt vtools output variant "max(DP)" "min(DP)" "avg(DP)" "stdev(DP)" "lower_quartile(DP)" "upper_quartile(DP)" --header vtools select variant "filter='PASS'" --count vtools select variant "filter='PASS'" -o "max(DP)" "min(DP)" "avg(DP)" "stdev(DP)" "lower_quartile(DP)" "upper_quartile(DP)" --header vtools update variant --from_stat 'total=#(GT)' 'num=#(alt)' 'het=#(het)' 'hom=#(hom)' 'other=#(other)' 'minDP=min(DP_geno)' 'maxDP=max(DP_geno)' 'meanDP=avg(DP_geno)' 'maf=maf()' vtools show fields vtools show table variant vtools update variant --from_stat 'totalGD10=#(GT)' 'numGD10=#(alt)' 'hetGD10=#(het)' 'homGD10=#(hom)' 'otherGD10=#(other)' 'mafGD10=maf()' --genotypes "DP_geno &gt; 10" vtools show fields vtools show table variant vtools output variant chr pos maf mafGD10 --header --limit 20 vtools phenotype --set "RACE=0" --samples "filename like 'YRI%'" vtools phenotype --set "RACE=1" --samples "filename like 'CEU%'" vtools show samples --limit 10 vtools update variant --from_stat 'CEU_mafGD10=maf()' --genotypes 'DP_geno&gt;10' --samples "RACE=1" vtools update variant --from_stat 'YRI_mafGD10=maf()' --genotypes 'DP_geno&gt;10' --samples "RACE=0" vtools output variant chr pos mafGD10 CEU_mafGD10 YRI_mafGD10 --header --limit 10 vtools phenotype --from_stat 'CEU_totalGD10=#(GT)' 'CEU_numGD10=#(alt)' --genotypes 'DP_geno&gt;10' --samples "RACE=1" vtools phenotype --from_stat 'YRI_totalGD10=#(GT)' 'YRI_numGD10=#(alt)' --genotypes 'DP_geno&gt;10' --samples "RACE=0" vtools phenotype --output sample_name CEU_totalGD10 CEU_numGD10 YRI_totalGD10 YRI_numGD10 --header vtools select variant 'maf&gt;=0.01' -t variant_MAFge01 'Variants that have MAF &gt;= 0.01' vtools show tables vtools execute KING --var_table variant_MAFge01 vtools_report plot_pheno_fields KING_MDS1 KING_MDS2 RACE --dot KING.mds.race.pdf --discrete_color Dark2 vtools_report plot_pheno_fields KING_MDS1 KING_MDS2 panel --dot KING.mds.panel.pdf --discrete_color Dark2 vtools execute ANNOVAR geneanno vtools output variant chr pos ref alt mut_type --limit 20 --header vtools_report trans_ratio variant -n num vtools_report trans_ratio variant -n numGD10 vtools select variant "DP&lt;15" -t to_remove vtools show tables vtools remove variants to_remove -v0 vtools show tables vtools remove genotypes "DP_geno&lt;10" -v0 <br />vtools select variant "mut_type like 'non%' or mut_type like 'stop%' or region_type='splicing'" -t v_funct <br />vtools show tables <br />vtools show samples --limit 5 <br />vtools select variant --samples "RACE=1" -t CEU <br />mkdir -p ceu <br />cd ceu <br />vtools init ceu --parent ../ --variants CEU --samples "RACE=1" --build hg19 vtools show project vtools select variant "CEU_mafGD10&gt;=0.05" -t common_ceu vtools select v_funct "CEU_mafGD10&lt;0.01" -t rare_ceu <br />vtools use refGene <br />vtools show annotation refGene <br />vtools associate -h <br />vtools show tests <br />vtools show test LinRegBurden <br />vtools associate common_ceu BMI --covariate SEX -m "LinRegBurden --alternative 2" -j1 --to_db EA_CV &gt; EA_CV.asso.res grep -i error *.log less EA_CV.asso.res sort -g -k7 EA_CV.asso.res | head vtools show fields vtools associate rare_ceu BMI --covariate SEX -m "LinRegBurden --alternative 2" -g refGene.name2 -j1 --to_db EA_RV &gt; EA_RV.asso.res grep -i error *.log | tail -22 less EA_RV.asso.res sort -g -k6 EA_RV.asso.res | head vtools associate rare_ceu BMI --covariate SEX -m "VariableThresholdsQt --alternative 2 -p 100000 --adaptive 0.0005" -g refGene.name2 -j1 --to_db EA_RV &gt; EA_RV_VT.asso.res grep -i error *.log | tail -22 less EA_RV_VT.asso.res sort -g -k6 EA_RV_VT.asso.res | head vtools select rare_ceu "refGene.name2='ABCC1'" -o chr pos ref alt CEU_mafGD10 numGD10 mut_type --header vtools_report plot_association qq -o QQRV -b --label_top 2 -f 6 &lt; EA_RV.asso.res vtools_report plot_association manhattan -o MHRV -b --label_top 5 --color Dark2 --chrom_prefix None -f 6 &lt; EA_RV.asso.res <br />vtools associate rare_ceu BMI --covariate SEX KING_MDS1 KING_MDS2 -m "LinRegBurden --name RVMDS2 --alternative 2" -g refGene.name2 -j1 --to_db EA_RV &gt; EA_RV_MDS2.asso.res vtools_report plot_association qq -o QQRV_MDS2 -b --label_top 2 -f 6 &lt; EA_RV_MDS2.asso.res <br />cd .. <br />vtools select variant --samples "RACE=0" -t YRI <br />mkdir -p yri <br />cd yri <br />vtools init yri --parent ../ --variants YRI --samples "RACE=0" --build hg19 <br />vtools select variant "YRI_mafGD10&gt;=0.05" -t common_yri vtools select v_funct "YRI_mafGD10&lt;0.01" -t rare_yri <br />vtools use refGene <br />vtools associate common_yri BMI --covariate SEX -m "LinRegBurden --alternative 2" -j1 --to_db YA_CV &gt; YA_CV.asso.res vtools associate rare_yri BMI --covariate SEX -m "LinRegBurden --alternative 2" -g refGene.name2 -j1 --to_db YA_RV &gt; YA_RV.asso.res vtools associate rare_yri BMI --covariate SEX -m "VariableThresholdsQt --alternative 2 -p 100000 --adaptive 0.0005" -g refGene.name2 -j1 --to_db YA_RV &gt; YA_RV_VT.asso.res cd .. vtools_report meta_analysis ceu/EA_RV_VT.asso.res yri/YA_RV_VT.asso.res --beta 5 --pval 6 --se 7 -n 2 --link 1 &gt; META_RV_VT.asso.res cut -f1,3 META_RV_VT.asso.res | head