Difference between revisions of "Family-based Association Exercise"
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==Family-based Association Exercise== | ==Family-based Association Exercise== | ||
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cd exercises/cordell/FASTLMM_GCTA | cd exercises/cordell/FASTLMM_GCTA | ||
ls -l | ls -l | ||
| Line 10: | Line 9: | ||
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) | ||
| + | dev.off() | ||
| + | jpeg("qqplot1.jpeg", height=500, width=500) | ||
qq(res1$P) | qq(res1$P) | ||
| + | dev.off() | ||
chi<-(qchisq(1-res1$P,1)) | chi<-(qchisq(1-res1$P,1)) | ||
lambda=median(chi)/0.456 | lambda=median(chi)/0.456 | ||
| Line 25: | Line 28: | ||
names(new)<-c("SNP", "CHR", "BP", "P") | names(new)<-c("SNP", "CHR", "BP", "P") | ||
head(new) | head(new) | ||
| + | jpeg("qqplot2.jpeg", height=500, width=500) | ||
qq(new$P) | qq(new$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) | 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()
