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-rw-r--r--scripts/rqtl_wrapper.R130
1 files changed, 77 insertions, 53 deletions
diff --git a/scripts/rqtl_wrapper.R b/scripts/rqtl_wrapper.R
index b7a9ae0..eb660b5 100644
--- a/scripts/rqtl_wrapper.R
+++ b/scripts/rqtl_wrapper.R
@@ -12,6 +12,7 @@ option_list = list(
make_option(c("--covarstruct"), type="character", help="File detailing which covariates are categorical or numerical"),
make_option(c("--model"), type="character", default="normal", help="Mapping Model - Normal or Non-Parametric"),
make_option(c("--method"), type="character", default="hk", help="Mapping Method - hk (Haley Knott), ehk (Extended Haley Knott), mr (Marker Regression), em (Expectation-Maximization), imp (Imputation)"),
+ make_option(c("--pairscan"), action="store_true", default=NULL, help="Run Pair Scan - the R/qtl function scantwo"),
make_option(c("-i", "--interval"), action="store_true", default=NULL, help="Use interval mapping"),
make_option(c("--nperm"), type="integer", default=0, help="Number of permutations"),
make_option(c("--pstrata"), action="store_true", default=NULL, help="Use permutation strata (stored as final column/vector in phenotype input file)"),
@@ -174,6 +175,9 @@ cross_object = geno_to_csvr(geno_file, trait_names, trait_vals, cross_file, type
if (!is.null(opt$interval)) {
verbose_print('Calculating genotype probabilities with interval mapping\n')
cross_object <- calc.genoprob(cross_object, step=5, stepwidth="max")
+} else if (!is.null(opt$pairscan)) {
+ verbose_print('Calculating genotype probabilities for pair-scan\n')
+ cross_object <- calc.genoprob(cross_object, step=10)
} else {
verbose_print('Calculating genotype probabilities\n')
cross_object <- calc.genoprob(cross_object)
@@ -188,6 +192,7 @@ if (type == "4-way") {
# Pull covariates out of cross object, if they exist
covars <- c() # Holds the covariates which should be passed to R/qtl
if (!is.null(opt$addcovar)) {
+ verbose_print('Pulling covariates out of cross object\n')
# If perm strata are being used, it'll be included as the final column in the phenotype file
if (!is.null(opt$pstrata)) {
covar_names = trait_names[2:(length(trait_names)-1)]
@@ -218,16 +223,28 @@ if (!is.null(opt$addcovar)) {
# Pull permutation strata out of cross object, if it is being used
perm_strata = vector()
if (!is.null(opt$pstrata)) {
+ verbose_print('Pulling permutation strata out of cross object\n')
strata_col = trait_names[length(trait_names)]
perm_strata <- pull.pheno(cross_object, strata_col)
}
# If a marker name is supplied as covariate, get its vector of values and add them as a covariate
if (!is.null(opt$control)) {
+ verbose_print('Creating marker covariates and binding them to covariates vector\n')
marker_covars = create_marker_covars(cross_object, opt$control)
covars <- cbind(covars, marker_covars)
}
+if (!is.null(opt$pairscan)) {
+ scan_func <- function(...){
+ scantwo(...)
+ }
+} else {
+ scan_func <- function(...){
+ scanone(...)
+ }
+}
+
# Calculate permutations
if (opt$nperm > 0) {
if (!is.null(opt$filename)){
@@ -238,19 +255,19 @@ if (opt$nperm > 0) {
if (!is.null(opt$addcovar) || !is.null(opt$control)){
if (!is.null(opt$pstrata)) {
- verbose_print('Running ', opt$nperm, ' permutations with cofactors and strata\n')
- perm_results = scanone(cross_object, pheno.col=1, addcovar=covars, n.perm=opt$nperm, perm.strata=perm_strata, model=opt$model, method=opt$method)
+ verbose_print('Running permutations with cofactors and strata\n')
+ perm_results = scan_func(cross_object, pheno.col=1, addcovar=covars, n.perm=opt$nperm, perm.strata=perm_strata, model=opt$model, method=opt$method)
} else {
- verbose_print('Running ', opt$nperm, ' permutations with cofactors\n')
- perm_results = scanone(cross_object, pheno.col=1, addcovar=covars, n.perm=opt$nperm, model=opt$model, method=opt$method)
+ verbose_print('Running permutations with cofactors\n')
+ perm_results = scan_func(cross_object, pheno.col=1, addcovar=covars, n.perm=opt$nperm, model=opt$model, method=opt$method)
}
} else {
if (!is.null(opt$pstrata)) {
- verbose_print('Running ', opt$nperm, ' permutations with strata\n')
- perm_results = scanone(cross_object, pheno.col=1, n.perm=opt$nperm, perm.strata=perm_strata, model=opt$model, method=opt$method)
+ verbose_print('Running permutations with strata\n')
+ perm_results = scan_func(cross_object, pheno.col=1, n.perm=opt$nperm, perm.strata=perm_strata, model=opt$model, method=opt$method)
} else {
- verbose_print('Running ', opt$nperm, ' permutations\n')
- perm_results = scanone(cross_object, pheno.col=1, n.perm=opt$nperm, model=opt$model, method=opt$method)
+ verbose_print('Running permutations\n')
+ perm_results = scan_func(cross_object, pheno.col=1, n.perm=opt$nperm, model=opt$model, method=opt$method)
}
}
write.csv(perm_results, perm_out_file)
@@ -263,57 +280,64 @@ if (!is.null(opt$filename)){
}
if (!is.null(opt$addcovar) || !is.null(opt$control)){
- verbose_print('Running scanone with cofactors\n')
- qtl_results = scanone(cross_object, pheno.col=1, addcovar=covars, model=opt$model, method=opt$method)
+ verbose_print('Running scan with cofactors\n')
+ qtl_results = scan_func(cross_object, pheno.col=1, addcovar=covars, model=opt$model, method=opt$method)
} else {
- verbose_print('Running scanone\n')
- qtl_results = scanone(cross_object, pheno.col=1, model=opt$model, method=opt$method)
+ verbose_print('Running scan\n')
+ qtl_results = scan_func(cross_object, pheno.col=1, model=opt$model, method=opt$method)
}
-#QTL main effects on adjusted longevity
-getEffects <- function(sdata, gtsprob, marker = "1_24042124", model = "longevity ~ sex + site + cohort + treatment", trait = "longevity"){
- rownames(sdata) <- 1:nrow(sdata)
- rownames(gtsprob) <- 1:nrow(gtsprob)
- mp <- gtsprob[, grep(marker, colnames(gtsprob))]
- gts <- unlist(lapply(lapply(lapply(apply(mp,1,function(x){which(x > 0.85)}),names), strsplit, ":"), function(x){
- if(length(x) > 0){ return(x[[1]][2]); }else{ return(NA) }
- }))
-
- ismissing <- which(apply(sdata, 1, function(x){any(is.na(x))}))
- if(length(ismissing) > 0){
- sdata <- sdata[-ismissing, ]
- gts <- gts[-ismissing]
+verbose_print('Writing results to CSV file\n')
+if (!is.null(opt$pairscan)) {
+ map_out_file = file.path(opt$outdir, paste("MAP_", opt$filename, sep = "" ))
+ write.csv(qtl_results[1], out_file)
+ write.csv(qtl_results[2], map_out_file)
+} else {
+ # QTL main effects on adjusted longevity
+ getEffects <- function(sdata, gtsprob, marker = "1_24042124", model = "longevity ~ sex + site + cohort + treatment", trait = "longevity"){
+ rownames(sdata) <- 1:nrow(sdata)
+ rownames(gtsprob) <- 1:nrow(gtsprob)
+ mp <- gtsprob[, grep(marker, colnames(gtsprob))]
+ gts <- unlist(lapply(lapply(lapply(apply(mp,1,function(x){which(x > 0.85)}),names), strsplit, ":"), function(x){
+ if(length(x) > 0){ return(x[[1]][2]); }else{ return(NA) }
+ }))
+
+ ismissing <- which(apply(sdata, 1, function(x){any(is.na(x))}))
+ if(length(ismissing) > 0){
+ sdata <- sdata[-ismissing, ]
+ gts <- gts[-ismissing]
+ }
+
+ mlm <- lm(as.formula(model), data = sdata)
+ pheAdj <- rep(NA, nrow(sdata))
+ adj <- residuals(mlm) + mean(sdata[, trait])
+ pheAdj[as.numeric(names(adj))] <- adj
+ means <- c(mean(pheAdj[which(gts == "AC")],na.rm=TRUE),mean(pheAdj[which(gts == "AD")],na.rm=TRUE),mean(pheAdj[which(gts == "BC")],na.rm=TRUE),mean(pheAdj[which(gts == "BD")],na.rm=TRUE))
+ std <- function(x) sd(x,na.rm=TRUE)/sqrt(length(x))
+ stderrs <- c(std(pheAdj[which(gts == "AC")]),std(pheAdj[which(gts == "AD")]),std(pheAdj[which(gts == "BC")]),std(pheAdj[which(gts == "BD")]))
+ paste0(round(means,0), " ± ", round(stderrs,2))
}
- mlm <- lm(as.formula(model), data = sdata)
- pheAdj <- rep(NA, nrow(sdata))
- adj <- residuals(mlm) + mean(sdata[, trait])
- pheAdj[as.numeric(names(adj))] <- adj
- means <- c(mean(pheAdj[which(gts == "AC")],na.rm=TRUE),mean(pheAdj[which(gts == "AD")],na.rm=TRUE),mean(pheAdj[which(gts == "BC")],na.rm=TRUE),mean(pheAdj[which(gts == "BD")],na.rm=TRUE))
- std <- function(x) sd(x,na.rm=TRUE)/sqrt(length(x))
- stderrs <- c(std(pheAdj[which(gts == "AC")]),std(pheAdj[which(gts == "AD")]),std(pheAdj[which(gts == "BC")]),std(pheAdj[which(gts == "BD")]))
- paste0(round(means,0), " ± ", round(stderrs,2))
-}
+ if (type == "4-way") {
+ verbose_print("Get phenotype name + genoprob + all phenotypes + models for 4-way crosses")
+ traitname <- colnames(pull.pheno(cross_object))[1]
+ gtsp <- pull.genoprob(cross_object)
+ allpheno <- pull.pheno(cross_object)
+ if (!is.null(opt$addcovar)) {
+ model <- paste0(traitname, " ~ ", paste0(covar_names, sep="", collapse=" + "))
+ } else {
+ model <- paste0(traitname, " ~ 1 ")
+ }
-if (type == "4-way") {
- verbose_print("Get phenotype name + genoprob + all phenotypes + models for 4-way crosses")
- traitname <- colnames(pull.pheno(cross_object))[1]
- gtsp <- pull.genoprob(cross_object)
- allpheno <- pull.pheno(cross_object)
- if (!is.null(opt$addcovar)) {
- model <- paste0(traitname, " ~ ", paste0(covar_names, sep="", collapse=" + "))
- } else {
- model <- paste0(traitname, " ~ 1 ")
+ meffects <- c()
+ verbose_print("Getting QTL main effects for 4-way crosses")
+ for(marker in rownames(qtl_results)){
+ meff <- getEffects(allpheno, gtsp, marker = marker, model, trait = traitname)
+ meffects <- rbind(meffects, meff)
+ }
+ qtl_results <- cbind(data.frame(qtl_results[,1:3]), meffects)
+ colnames(qtl_results)[4:7] <- c("AC", "AD", "BC", "BD")
}
- meffects <- c()
- verbose_print("Getting QTL main effects for 4-way crosses")
- for(marker in rownames(qtl_results)){
- meff <- getEffects(allpheno, gtsp, marker = marker, model, trait = traitname)
- meffects <- rbind(meffects, meff)
- }
- qtl_results <- cbind(data.frame(qtl_results[,1:3]), meffects)
- colnames(qtl_results)[4:7] <- c("AC", "AD", "BC", "BD")
+ write.csv(qtl_results, out_file)
}
-
-write.csv(qtl_results, out_file)