diff options
Diffstat (limited to 'scripts/ctl_analysis.R')
| -rw-r--r-- | scripts/ctl_analysis.R | 36 |
1 files changed, 25 insertions, 11 deletions
diff --git a/scripts/ctl_analysis.R b/scripts/ctl_analysis.R index d9a937f..8c831ad 100644 --- a/scripts/ctl_analysis.R +++ b/scripts/ctl_analysis.R @@ -1,4 +1,5 @@ library(ctl) +library(stringi); library(rjson) options(stringsAsFactors = FALSE); @@ -7,6 +8,8 @@ options(stringsAsFactors = FALSE); args = commandArgs(trailingOnly=TRUE) +imgDir = Sys.getenv("GENERATED_IMAGE_DIR") + if (length(args)==0) { stop("Argument for the data file", call.=FALSE) } else { @@ -14,20 +17,32 @@ if (length(args)==0) { json_file_path = args[1] } +json_file_path # add validation for the files input <- fromJSON(file = json_file_path) +genoData <- input$geno +phenoData <- input$pheno + +formData <- input$form +# create the matixes +genoData +geno_matrix = t(matrix(unlist(genoData$genotypes), + nrow=length(genoData$markernames), ncol=length(genoData$individuals), + dimnames=list(genoData$markernames, genoData$individuals), byrow=TRUE)) + +pheno_matrix = t(matrix(as.numeric(unlist(phenoData$traits)), nrow=length(phenoData$trait_db_list), ncol=length( + phenoData$individuals), dimnames= list(phenoData$trait_db_list, phenoData$individuals), byrow=TRUE)) -genotypes <- read.csv(input$geno_file,row.names=1, header=FALSE, sep="\t") -# The phenotypes.csv file containing individuals (rows) x traits (columns) measurements: -traits <- read.csv(input$pheno_file,row.names=1, header=FALSE, sep="\t") +# Use a data frame to store the objects +pheno = data.frame(pheno_matrix, check.names=FALSE) +geno = data.frame(geno_matrix, check.names=FALSE) -ctls <- CTLscan(geno,traits,strategy=input$strategy, - nperm=input$nperms,parametric =input$parametric, - nthreads=6,verbose=TRUE) +ctls <- CTLscan(geno,pheno,verbose=TRUE) + # same function used in a different script:refactor genImageRandStr <- function(prefix){ @@ -38,16 +53,15 @@ genImageRandStr <- function(prefix){ #output matrix significant CTL interactions with 4 columns: trait, marker, trait, lod -sign <- CTLsignificant(ctls,significance = input$significance) +sign <- CTLsignificant(ctls,significance = formData$significance) # Create the lineplot imageLoc = file.path(imgDir,genImageRandStr("CTLline")) png(imageLoc,width=1000,height=600,type='cairo-png') -lineplot(res, significance=input$significance) - +ctl.lineplot(ctls, significance=formData$significance) -json_data <- list(significance=signs, - images=lists("image_1"=imageLoc), +json_data <- list(significance=sign, + images=list("image_1"=imageLoc), network_figure_location="/location")
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