Difference between revisions of "Family-based Association Exercise"
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==Family-based Association Exercise== | ==Family-based Association Exercise== | ||
− | + | cd exercises/cordell/FASTLMM_GCTA | |
− | cd exercises/cordell/FASTLMM_GCTA | + | ls -l |
− | ls -l | + | plink --bfile quantfamdata --assoc --out plinkresults |
− | plink --bfile quantfamdata --assoc --out plinkresults | + | R |
− | R | + | res1<-read.table("plinkresults.qassoc", header=T) |
− | res1<-read.table("plinkresults.qassoc", header=T) | + | head(res1) |
− | head(res1) | + | source("qqmanHJCupdated.R") |
− | source("qqmanHJCupdated.R") | + | jpeg("mh1.jpeg", height=500, width=800) |
− | manhattan(res1, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) | + | manhattan(res1, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) |
− | qq(res1$P) | + | dev.off() |
− | chi<-(qchisq(1-res1$P,1)) | + | jpeg("qqplot1.jpeg", height=500, width=500) |
− | lambda=median(chi)/0.456 | + | qq(res1$P) |
− | lambda | + | dev.off() |
− | fastlmmc -bfile quantfamdata -pheno quantfamdata.fam -mpheno 4 -bfileSim quantfamdata -ML -out FLMMresults | + | chi<-(qchisq(1-res1$P,1)) |
− | R | + | lambda=median(chi)/0.456 |
− | res2<-read.table("FLMMresults", header=T) | + | lambda |
− | head(res2) | + | fastlmmc -bfile quantfamdata -pheno quantfamdata.fam -mpheno 4 -bfileSim quantfamdata -ML -out FLMMresults |
− | chi<-(qchisq(1-res2$Pvalue,1)) | + | R |
− | lambda=median(chi)/0.456 | + | res2<-read.table("FLMMresults", header=T) |
− | lambda | + | head(res2) |
− | new<-data.frame(res2$SNP, res2$Chromosome, res2$Position, res2$Pvalue) | + | chi<-(qchisq(1-res2$Pvalue,1)) |
− | names(new)<-c("SNP", "CHR", "BP", "P") | + | lambda=median(chi)/0.456 |
− | head(new) | + | lambda |
− | qq(new$P) | + | new<-data.frame(res2$SNP, res2$Chromosome, res2$Position, res2$Pvalue) |
− | manhattan(new, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) | + | names(new)<-c("SNP", "CHR", "BP", "P") |
+ | head(new) | ||
+ | jpeg("qqplot2.jpeg", height=500, width=500) | ||
+ | qq(new$P) | ||
+ | dev.off() | ||
+ | jpeg("mh2.jpeg", height=500, width=800) | ||
+ | manhattan(new, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) | ||
+ | dev.off() |
Latest revision as of 19:33, 24 January 2019
Family-based Association Exercise
cd exercises/cordell/FASTLMM_GCTA ls -l plink --bfile quantfamdata --assoc --out plinkresults R res1<-read.table("plinkresults.qassoc", header=T) head(res1) source("qqmanHJCupdated.R") jpeg("mh1.jpeg", height=500, width=800) manhattan(res1, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) dev.off() jpeg("qqplot1.jpeg", height=500, width=500) qq(res1$P) dev.off() chi<-(qchisq(1-res1$P,1)) lambda=median(chi)/0.456 lambda fastlmmc -bfile quantfamdata -pheno quantfamdata.fam -mpheno 4 -bfileSim quantfamdata -ML -out FLMMresults R res2<-read.table("FLMMresults", header=T) head(res2) chi<-(qchisq(1-res2$Pvalue,1)) lambda=median(chi)/0.456 lambda new<-data.frame(res2$SNP, res2$Chromosome, res2$Position, res2$Pvalue) names(new)<-c("SNP", "CHR", "BP", "P") head(new) jpeg("qqplot2.jpeg", height=500, width=500) qq(new$P) dev.off() jpeg("mh2.jpeg", height=500, width=800) manhattan(new, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) dev.off()