R/older_funcs/qcfuncs.R

In IMBEIbioinformatics/BIUMmisc: A collection of functions and scripts commonly used by the BIUM-MZ Core Facility and the Bioinformatics group at the IMBEI

#' # rewrite of RSeQC functions, optimized for R
#'
#'
#'
#'
#'
#' # parsers for tools
#'
#'
#' #' Title
#' #'
#' #' @param allLogs
#' #'
#' #' @return A value
#' #' @export
#' #'
#' #' @examples # An example
#' parseRSEQCdistro <- function(allLogs){
#'   logsIn <- lapply(allLogs, function(arg){(strsplit(readLines(arg),"|\t",fixed = TRUE))})
#'   names(logsIn) <- basename(allLogs)
#'   groups <- c("CDS_Exons","5'UTR_Exons","3'UTR_Exons","Introns","TSS_up_1kb","TSS_up_5kb","TSS_up_10kb","TES_down_1kb","TES_down_5kb","TES_down_10kb")
#'   sampleValues <- sapply(9:18,function(arg){strsplit(gsub("^ *|(?<= ) | *$", "", logsIn[[1]][[arg]], perl=T)," ",fixed=TRUE)[[1]][[4]]})
#'
#'   res <- data.frame(matrix(NA,length(allLogs),length(groups)))
#'   names(res) <- groups
#'   row.names(res) <-  basename(allLogs)
#'   for(i in 1:length(allLogs)){
#'     res[i,] <-sapply(9:18,function(arg){strsplit(gsub("^ *|(?<= ) | *$", "", logsIn[[i]][[arg]], perl=T)," ",fixed=TRUE)[[1]][[4]]})
#'   }
#'   return(res)
#' }
#'
#'
#'
#'
#' #' Title
#' #'
#' #' @param folder
#' #'
#' #' @return A value
#' #' @export
#' #'
#' #' @examples # An example
#' parseStarLogs <- function(folder){
#'   allLogs <- list.files(path = folder, pattern = ".Log.final.out$",full.names = TRUE)
#'   logsIn <- lapply(allLogs, function(arg){(strsplit(readLines(arg),"|\t",fixed = TRUE))})
#'   names(logsIn) <- list.files(path = folder, pattern = ".Log.final.out$",full.names = FALSE)
#'
#'   rawReads <- sapply(logsIn,function(arg){as.numeric(arg[[6]][2])})
#'   uniquemappedReads <- sapply(logsIn,function(arg){as.numeric(arg[[9]][2])})
#'   multimappedReads <- sapply(logsIn,function(arg){as.numeric(arg[[24]][2])})
#'   overallMappedReads <- uniquemappedReads + multimappedReads
#'   percentUnique <- uniquemappedReads/rawReads * 100
#'   percentMulti <- multimappedReads/rawReads * 100
#'   percentOverall <- (uniquemappedReads+multimappedReads)/rawReads * 100
#'
#'   df_reads <- data.frame(rawReads=rawReads,uniquemappedReads=uniquemappedReads,multimappedReads=multimappedReads,
#'                          overallMappedReads=overallMappedReads,percentUnique=percentUnique,
#'                          percentMulti=percentMulti,percentOverall=percentOverall)
#'   names(df_reads) <- c("# raw reads","# uniquely mapped reads","# multimapped reads","# overall mapped reads","percent uniquely mapping",
#'                        "percent multimapping","percent overall mapped")
#'   return(df_reads)
#'
#'
#' }
#'
#'
#'
#' ## stats after running featureCounts
#'
#' #' Title
#' #'
#' #' @param fcoutput
#' #'
#' #' @return
#' #' @export
#' #'
#' #' @examples
#' statsFC <- function(fcoutput){
#'   library(dplyr)
#'   library(tidyr)
#'   library(ggplot2)
#'
#'   fc_stats <- fcoutput$stat
#'
#'   fcdf <- as.data.frame(t(fc_stats))
#'   colnames(fcdf) <- fc_stats[,1]
#'   fcdf <- fcdf[-1,]
#'
#'   # make a "sample" column from the rownames of the object.
#'   # remove the ".star.Aligned.out.sam" from the pattern
#'   fcdf %>%
#'     mutate(sample=gsub("_Aligned.sortedByName.bam", "", rownames(.))) %>%
#'     # Reorder the columns
#'     select(sample, Assigned:Unassigned_NoFeatures) %>% # the other columns are already always 0s
#'     # Make it tidy
#'     gather(Assignment, ReadCounts, -sample) -> fctidy
#'
#'   fctidy$sample <- gsub("X_tempSortedByName..","",fctidy$sample)
#'
#'   fctidy$ReadCounts <- as.numeric(fctidy$ReadCounts)/1e6 # to scale to millions of reads
#'
#'   p <- ggplot(fctidy,aes(Assignment, ReadCounts)) + geom_bar(stat="identity", aes(fill=sample), position="dodge") +
#'     ylab("read counts (millions)") + xlab("assigned read status")
#'   print(p)
#'
#'   return(fctidy)
#'
#'
#' }