Difference between revisions of "AdvGeneMap2018Commands"

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__NOTITLE__
 
__NOTITLE__
  
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==Data QC Plink==
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==Plink Data QC==
 
  #PLINK
 
  #PLINK
−
 
 
  plink --file GWAS
 
  plink --file GWAS
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  plink --file GWAS --mind 0.10 --recode --out GWAS_clean_mind
 
  plink --file GWAS --mind 0.10 --recode --out GWAS_clean_mind
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  plink --file GWAS_clean_mind --maf 0.05 --recode --out MAF_greater_5
 
  plink --file GWAS_clean_mind --maf 0.05 --recode --out MAF_greater_5
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  plink --file GWAS_clean_mind --exclude MAF_greater_5.map --recode --out MAF_less_5
 
  plink --file GWAS_clean_mind --exclude MAF_greater_5.map --recode --out MAF_less_5
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  plink --file MAF_greater_5 --geno 0.05 --recode --out MAF_greater_5_clean
 
  plink --file MAF_greater_5 --geno 0.05 --recode --out MAF_greater_5_clean
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  plink --file MAF_less_5 --geno 0.01 --recode --out MAF_less_5_clean
 
  plink --file MAF_less_5 --geno 0.01 --recode --out MAF_less_5_clean
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  plink --file MAF_greater_5_clean --merge MAF_less_5_clean.ped MAF_less_5_clean.map --recode --out GWAS_MAF_clean
 
  plink --file MAF_greater_5_clean --merge MAF_less_5_clean.ped MAF_less_5_clean.map --recode --out GWAS_MAF_clean
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  plink --file GWAS_MAF_clean --mind 0.03 --recode --out GWAS_clean2
 
  plink --file GWAS_MAF_clean --mind 0.03 --recode --out GWAS_clean2
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  plink --file GWAS_clean2 --check-sex --out GWAS_sex_checking
 
  plink --file GWAS_clean2 --check-sex --out GWAS_sex_checking
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  #### in R - open R by simply typing R
 
  #### in R - open R by simply typing R
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  setwd("to_your_working_directory/")
 
  setwd("to_your_working_directory/")
−
 
 
  sexcheck = read.table("GWAS_sex_checking.sexcheck", header=T)
 
  sexcheck = read.table("GWAS_sex_checking.sexcheck", header=T)
 
  names(sexcheck)
 
  names(sexcheck)
 
  sex_problem = sexcheck[which(sexcheck$STATUS=="PROBLEM"),]
 
  sex_problem = sexcheck[which(sexcheck$STATUS=="PROBLEM"),]
 
  sex_problem
 
  sex_problem
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  q()
 
  q()
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  ##################################
 
  ##################################
−
 
 
  plink --file GWAS_clean2 --genome --out duplicates
 
  plink --file GWAS_clean2 --genome --out duplicates
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  #### in R
 
  #### in R
−
 
 
  setwd("to_your_working_directory/")
 
  setwd("to_your_working_directory/")
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  dups = read.table("duplicates.genome", header = T)
 
  dups = read.table("duplicates.genome", header = T)
 
  problem_pairs = dups[which(dups$PI_HAT > 0.4),]
 
  problem_pairs = dups[which(dups$PI_HAT > 0.4),]
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  myvars = c("FID1", "IID1", "FID2", "IID2", "PI_HAT")
 
  myvars = c("FID1", "IID1", "FID2", "IID2", "PI_HAT")
 
  problem_pairs[myvars]
 
  problem_pairs[myvars]
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  q()
 
  q()
−
 
 
  ######
 
  ######
−
 
 
  plink --file GWAS_clean2 --remove IBS_excluded.txt --recode --out GWAS_clean3
 
  plink --file GWAS_clean2 --remove IBS_excluded.txt --recode --out GWAS_clean3
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  plink --file GWAS_clean3 --het
 
  plink --file GWAS_clean3 --het
−
 
 
  ###### in R
 
  ###### in R
−
 
 
  Dataset <- read.table("plink.het", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
 
  Dataset <- read.table("plink.het", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
−
 
 
  mean(Dataset$F)
 
  mean(Dataset$F)
 
  sd(Dataset$F)
 
  sd(Dataset$F)
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  jpeg("hist.jpeg", height=1000, width=1000)
 
  jpeg("hist.jpeg", height=1000, width=1000)
 
  hist(scale(Dataset$F), xlim=c(-4,4))
 
  hist(scale(Dataset$F), xlim=c(-4,4))
 
  dev.off()
 
  dev.off()
−
 
 
  q()
 
  q()
−
 
 
  ######
 
  ######
−
 
 
  plink --file GWAS_clean3 --pheno pheno.txt --pheno-name Aff --hardy  
 
  plink --file GWAS_clean3 --pheno pheno.txt --pheno-name Aff --hardy  
−
 
 
  ##### in R
 
  ##### in R
−
 
 
  hardy = read.table("plink.hwe", header = T)
 
  hardy = read.table("plink.hwe", header = T)
 
  names(hardy)
 
  names(hardy)
 
  hwe_prob = hardy[which(hardy$P < 0.0000009),]
 
  hwe_prob = hardy[which(hardy$P < 0.0000009),]
 
  hwe_prob
 
  hwe_prob
−
 
−
 
 
  q()
 
  q()
−
 
−
 
 
  ##########
 
  ##########
−
 
 
  plink --file GWAS_clean3 --exclude HWE_out.txt --recode --out GWAS_clean4
 
  plink --file GWAS_clean3 --exclude HWE_out.txt --recode --out GWAS_clean4
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###############################################
 
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##### Part 2: controlling for substructure#####
 
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###############################################
 
−
 
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plink --file GWAS_clean4 --genome --cluster --mds-plot 10
 
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−
#### in R
 
−
 
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mydata = read.table("mds_components.txt", header=T)
 
−
 
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mydata$pch[mydata$Group==1 ] <-15
 
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mydata$pch[mydata$Group==2 ] <-16
 
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mydata$pch[mydata$Group==3 ] <-2
 
−
 
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jpeg("mds.jpeg", height=500, width=500)
 
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plot(mydata$C1, mydata$C2 ,pch=mydata$pch)
 
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dev.off()
 
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q()
 
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−
######
 
−
 
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plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --logistic --adjust --out unadj
 
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plink --file GWAS_clean4 --genome --cluster --pca 10 header
 
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plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --covar plink.eigenvec --covar-name PC1 --logistic --adjust --out PC1
 
−
 
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plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --covar plink.eigenvec --covar-name PC1-PC2 --logistic --adjust --out PC1-PC2
 
−
 
−
#### in R
 
−
 
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broadqq <-function(pvals, title)
 
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{
 
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observed <- sort(pvals)
 
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lobs <- -(log10(observed))
 
−
 
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expected <- c(1:length(observed))
 
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lexp <- -(log10(expected / (length(expected)+1)))
 
−
 
−
plot(c(0,7), c(0,7), col="red", lwd=3, type="l", xlab="Expected (-logP)", ylab="Observed (-logP)", xlim=c(0,max(lobs)), ylim=c(0,max(lobs)), las=1, xaxs="i", yaxs="i", bty="l", main = title)
 
−
points(lexp, lobs, pch=23, cex=.4, bg="black") }
 
−
 
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jpeg("qqplot_compare.jpeg", height=1000, width=500)
 
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par(mfrow=c(2,1))
 
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aff_unadj<-read.table("unadj.assoc.logistic", header=TRUE)
 
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aff_unadj.add.p<-aff_unadj[aff_unadj$TEST==c("ADD"),]$P
 
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broadqq(aff_unadj.add.p,"Some Trait Unadjusted")
 
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aff_C1C2<-read.table("PC1-PC2.assoc.logistic", header=TRUE)
 
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aff_C1C2.add.p<-aff_C1C2[aff_C1C2$TEST==c("ADD"),]$P
 
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broadqq(aff_C1C2.add.p, "Some Trait Adjusted for PC1 and PC2")
 
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dev.off()
 
−
 
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gws_unadj = aff_unadj[which(aff_unadj$P < 0.0000001),]
 
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gws_unadj
 
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gws_adjusted = aff_C1C2[which(aff_C1C2$P < 0.0000001),]
 
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gws_adjusted
 

Revision as of 17:16, 22 January 2018

Plink Data QC

#PLINK
plink --file GWAS
plink --file GWAS --mind 0.10 --recode --out GWAS_clean_mind
plink --file GWAS_clean_mind --maf 0.05 --recode --out MAF_greater_5
plink --file GWAS_clean_mind --exclude MAF_greater_5.map --recode --out MAF_less_5
plink --file MAF_greater_5 --geno 0.05 --recode --out MAF_greater_5_clean
plink --file MAF_less_5 --geno 0.01 --recode --out MAF_less_5_clean
plink --file MAF_greater_5_clean --merge MAF_less_5_clean.ped MAF_less_5_clean.map --recode --out GWAS_MAF_clean
plink --file GWAS_MAF_clean --mind 0.03 --recode --out GWAS_clean2
plink --file GWAS_clean2 --check-sex --out GWAS_sex_checking
#### in R - open R by simply typing R
setwd("to_your_working_directory/")
sexcheck = read.table("GWAS_sex_checking.sexcheck", header=T)
names(sexcheck)
sex_problem = sexcheck[which(sexcheck$STATUS=="PROBLEM"),]
sex_problem
q()
##################################
plink --file GWAS_clean2 --genome --out duplicates
#### in R
setwd("to_your_working_directory/")
dups = read.table("duplicates.genome", header = T)
problem_pairs = dups[which(dups$PI_HAT > 0.4),]
problem_pairs
problem_pairs = dups[which(dups$PI_HAT > 0.05),]
myvars = c("FID1", "IID1", "FID2", "IID2", "PI_HAT")
problem_pairs[myvars]
q()
######
plink --file GWAS_clean2 --remove IBS_excluded.txt --recode --out GWAS_clean3
plink --file GWAS_clean3 --het
###### in R
Dataset <- read.table("plink.het", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
mean(Dataset$F)
sd(Dataset$F)
jpeg("hist.jpeg", height=1000, width=1000)
hist(scale(Dataset$F), xlim=c(-4,4))
dev.off()
q()
######
plink --file GWAS_clean3 --pheno pheno.txt --pheno-name Aff --hardy 
##### in R
hardy = read.table("plink.hwe", header = T)
names(hardy)
hwe_prob = hardy[which(hardy$P < 0.0000009),]
hwe_prob
q()
##########
plink --file GWAS_clean3 --exclude HWE_out.txt --recode --out GWAS_clean4
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