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Jump to navigationJump to searchTutorial: EMMAX GotCloud STOM (view source)
Revision as of 15:40, 5 January 2014
, 15:40, 5 January 2014→Lecture 2
== Lecture 2 ==
== Lecture 2 ==
=== Basic Setup ===
* To see the files for the session, type
* To see the files for the session, type
export S2=/data/stom2014/session2
export S2=/data/stom2014/session2
mkdir ~/out
mkdir ~/out
=== Naive Association Test ===
* Run naive association test using PLINK
* Run naive association test using PLINK
> qq.conf.beta(T$P)
> qq.conf.beta(T$P)
> dev.off()
> dev.off()
=== Genomic Control ===
* Add --adjust option to enable genomic control
* Add --adjust option to enable genomic control
> 0.4958032/0.456
> 0.4958032/0.456
[1] 1.08704
[1] 1.08704
* Check out the custom script to calculate inflation factor
less $S2/r/calc.GC.lambda.r
** Feed the p-values from association results
cut -c 96- ~/out/naive.assoc.linear | Rscript $S2/r/calc.GC.lambda.r
=== Principal Component Analysis ===
* Convert PLINK format file to EMMAX-compatible format to obtain PCs
$S2/bin/plink --noweb --bfile $S2/data/1000G.auto.omni.phased.EUR --recode12 --output-missing-genotype 0 --transpose --out ~/out/1000G.auto.omni.phased.EUR
* Create kinship matrix using EMMAX
$S2/bin/emmax-kin-intel64 -T 1 -M 0.2 -v -d 10 ~/out/1000G.auto.omni.phased.EUR
less ~/out/1000G.auto.omni.phased.EUR.aBN.kinf
* Calculate principal component using custom script
Rscript $S2/r/calc.PC.from.kinf.r ~/out/1000G.auto.omni.phased.EUR.aBN.kinf ~/out/1000G.auto.omni.phased.EUR.tfam ~/out/1000G.auto.omni.phased.EUR.pc10
* Check out how the PCA outcome looks like
less ~/out/1000G.auto.omni.phased.EUR.pc10
* Visualize the population structure using PCs with custom script
Rscript $S2/r/plot_pc_pop.r ~/out/1000G.auto.omni.phased.EUR.pc10 $S2/data/1000G.auto.omni.phased.EUR.pop ~/out/1000G.auto.omni.phased.EUR.pc10.pdf
* Use PCs as covariates to adjust for PCs
$S2/bin/plink --noweb --bfile $S2/data/1000G.auto.omni.phased.EUR --pheno $S2/data/1000G_EUR_20_1459060.phe --covar ~/out/1000G.auto.omni.phased.EUR.pc10 --covar-number 1,2,3,4 --linear --adjust --out ~/out/pca
* Check out the p-value at the causal variant and inflation of statistics
grep -w ADD ~/out/pca.assoc.linear | grep 20:1459060
grep -w ADD ~/out/pca.assoc.linear | cut -c 96- | Rscript $S2/r/calc.GC.lambda.r
=== Mixed Model Association ===
* Run EMMAX association
$S2/bin/emmax-intel64 -t ~/out/1000G.auto.omni.phased.EUR -o ~/out/emmax -p $S2/data/1000G_EUR_20_1459060.phe -k ~/out/1000G.auto.omni.phased.EUR.aBN.kinf
* Check the inflation factor
cut -f 4 ~out/emmax.ps | Rscript $S2/r/calc.GC.lambda.r
[1] 1.006079
* Draw and compare multiple QQ plots using the R function provided
> source('/data/stom2014/session2/r/qqconf.r')
> T1 <- read.table('~/out/naive.assoc.linear',header=TRUE)
> T2 <- read.table('~/out/pca.assoc.linear',header=TRUE)
> T3 <- read.table('~/out/emmax.ps')
> pdf(‘~/out/na?)
> pdf('~/out/all.pdf')
> qq.conf.beta(T1$P)
> qq.conf.beta(T2$P,drawaxis=FALSE,ptcolor="blue")
> qq.conf.beta(T3$V4,drawaxis=FALSE,ptcolor="red")
> dev.off()
