Difference between revisions of "Family-based Association Exercise"
From Statistical Genetics Courses
Serveradmin (Talk | contribs) (Created page with "__NOTITLE__ ==Family-based Association Exercise== cd exercises/cordell/FASTLMM_GCTA ls -l") |
Serveradmin (Talk | contribs) |
||
| Line 5: | Line 5: | ||
cd exercises/cordell/FASTLMM_GCTA | cd exercises/cordell/FASTLMM_GCTA | ||
ls -l | ls -l | ||
| + | plink --bfile quantfamdata --assoc --out plinkresults | ||
| + | R | ||
| + | res1<-read.table("plinkresults.qassoc", header=T) | ||
| + | head(res1) | ||
| + | source("qqmanHJCupdated.R") | ||
| + | manhattan(res1, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) | ||
| + | qq(res1$P) | ||
| + | chi<-(qchisq(1-res1$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$Pvalue) | ||
| + | names(new)<-c("SNP", "CHR", "BP", "P") | ||
| + | head(new) | ||
| + | qq(new$P) | ||
| + | manhattan(new, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) | ||
Revision as of 18:46, 23 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") manhattan(res1, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5) qq(res1$P) chi<-(qchisq(1-res1$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$Pvalue) names(new)<-c("SNP", "CHR", "BP", "P") head(new) qq(new$P) manhattan(new, pch=20, suggestiveline=F, genomewideline=F, ymin=2, cex.x.axis=0.65, colors=c("black","dodgerblue"), cex=0.5)
