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| == Lecture 2 == | | == Lecture 2 == |
| | | |
− | The slides describing the notes below are available [[Media:Stom practice 02.pdf | here (PDF)]]
| + | Please see [[Tutorial:_EMMAX_GotCloud_STOM:_Lecture_2]] |
| | | |
− | === Basic Setup === | + | == Lecture 5 == |
| | | |
− | * To see the files for the session, type
| + | Please see [[Tutorial:_EMMAX_GotCloud_STOM:_Lecture_5]] |
− | ls /data/stom2014/session2/
| |
− | If you see any errors, please let me know now!
| |
| | | |
− | * For convenience, let’s set some variables
| + | == Lecture 6 == |
− | export S2=/data/stom2014/session2
| |
− | mkdir ~/out
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| | | |
− | === Naive Association Test ===
| + | Please see [[Tutorial:_EMMAX_GotCloud_STOM:_Lecture_6]] |
− | | |
− | * Run naive association test using PLINK
| |
− | | |
− | $S2/bin/plink --noweb --bfile $S2/data/1000G.auto.omni.phased.EUR --pheno $S2/data/1000G_EUR_20_1459060.phe --linear --out ~/out/naive
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− | | |
− | * Check your output file and see what it looks like
| |
− | | |
− | less ~/out/naive.assoc.linear
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− | | |
− | * Check the p-value at the causal variant
| |
− | | |
− | grep -w ADD ~/out/naive.assoc.linear | grep 20:1459060
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− | | |
− | * Draw QQ plot using the following R commands
| |
− | | |
− | > source('/data/stom2014/session2/r/qqconf.r')
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− | > T <- read.table('~/out/naive.assoc.linear',header=TRUE)
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− | > pdf('~/out/naive.pdf')
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− | > qq.conf.beta(T$P)
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− | > dev.off()
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− | | |
− | === Genomic Control ===
| |
− | | |
− | * Add --adjust option to enable genomic control
| |
− | | |
− | $S2/bin/plink --noweb --bfile $S2/data/1000G.auto.omni.phased.EUR --pheno $S2/data/1000G_EUR_20_1459060.phe --linear --adjust --out ~/out/naive
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− | | |
− | * Calculate inflation factor on your own
| |
− | | |
− | > T <- read.table('~/out/naive.assoc.linear',header=TRUE)
| |
− | | |
− | ** First, find the median p-value
| |
− | | |
− | > median(T$P)
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− | > 0.4814
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− | | |
− | ** Convert p-value into chi-square using R, and compute lambda
| |
− | | |
− | > qchisq(0.4814,1,lower.tail=FALSE)
| |
− | [1] 0,4956901
| |
− | > 0.4958032/0.456
| |
− | [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 $S2/r/calc.GC.lambda.r
| |
− | [1] 1.006079
| |
− | | |
− | * Draw and compare multiple QQ plots using the R function provided
| |
− | | |
− | > source('/data/stom2014/session2/r/qqconf.r')
| |
− | > T1 <- read.table('~/out/naive.assoc.linear',header=TRUE)
| |
− | > T2 <- read.table('~/out/pca.assoc.linear',header=TRUE)
| |
− | > T3 <- read.table('~/out/emmax.ps')
| |
− | > pdf('~/out/all.pdf')
| |
− | > qq.conf.beta(T1$P)
| |
− | > qq.conf.beta(T2$P,drawaxis=FALSE,ptcolor="blue")
| |
− | > qq.conf.beta(T3$V4,drawaxis=FALSE,ptcolor="red")
| |
− | > dev.off()
| |
STOM 2014 Workshop - Practical Sessions
Welcome to Hyun Min Kang's practical session guide page for STOM 2014 workshop. If you do not know what STOM 2014 workshop is please follow http://bibs.snu.ac.kr/board/index.php?catid=201&bcid=344
This page is intended to supplement the slides presented in the practical sessions of STOM 2014 workshop by facilitating easy copy-and paste of commands illustrated in the example, in the case the speed of the lecture is too fast for you.
This page only covers lecture 2, 5, 6, 8 that are taught by Hyun Min Kang.
Here I assume that
- The audience has basic knowledge of Unix system, basic utilities, and pipes
- The audience has the account in the cluster system and know how to access to the resources presented here
Note that some commands can be very long and may go farther than the browser's width
Lecture 2
Please see Tutorial:_EMMAX_GotCloud_STOM:_Lecture_2
Lecture 5
Please see Tutorial:_EMMAX_GotCloud_STOM:_Lecture_5
Lecture 6
Please see Tutorial:_EMMAX_GotCloud_STOM:_Lecture_6