# GetResultsFromJunctionSeq
#' Get analysis results using JunctionSeq
#'
#' @param dir.name
#' @param file.sample
#' @param file.count
#' @param file.gff
#'
#' @return return an analysis results from JunctionSeq
#' @export
#'
#' @examples
#'
#' # For example data set
#'
#' #dir.name='/media/H_driver/Aimin_project/'
#'
#' #file.sample='decoder.bySample.Mut_WT_2.rtf'
#' #file.gff='Homo_sapiens.GRCh38.84.processed.sorted.4.JunctionSeq.flat.gff'
#' #file.count='/QC.spliceJunctionAndExonCounts.forJunctionSeq.txt'
#'
#' #Re.example<-GetResultsFromJunctionSeq(dir.name,file.sample,file.count,file.gff)
#'
GetResultsFromJunctionSeq <- function(dir.name, file.sample,
file.count, file.gff) {
# Get sample file
dir.name = reformatPath(dir.name)
path.file.sample <- paste0(dir.name, file.sample)
decoder.bySample <- read.table(path.file.sample, header = TRUE,
stringsAsFactors = FALSE)
# Get count file
path.file.count <- paste0(dir.name, decoder.bySample$sample.ID,
file.count)
countFiles <- paste0(path.file.count)
# Get annotation file
path.file.gff <- paste0(dir.name, "GTF_Files/", file.gff)
# Analysis using exonsOnly , and adjust Gender
jscs.2 <- runJunctionSeqAnalyses(sample.files = countFiles,
sample.names = decoder.bySample$sample.ID, condition = decoder.bySample$group.ID,
flat.gff.file = path.file.gff, analysis.type = "exonsOnly",
nCores = 1, use.covars = decoder.bySample[, "Gender",
drop = FALSE], test.formula0 = ~sample + countbin +
Gender:countbin, test.formula1 = ~sample + countbin +
Gender:countbin + condition:countbin, effect.formula = ~condition +
Gender + countbin + Gender:countbin + condition:countbin,
geneLevel.formula = ~Gender + condition, verbose = TRUE,
debug.mode = TRUE, use.multigene.aggregates = TRUE)
return(jscs.2)
}
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