R/read_masic_data_from_DMS.R

In vladpetyuk/PlexedPiper: Pipeline for isobaric quantification.

#' Reading MASIC results from PNNL's DMS
#'
#' @param data_pkg (Numeric or Character vector) containing Data Package ID(s) located in DMS
#' @param interference_score (logical) read interference score. Default is FALSE.
#' @return (data.frame) with reporter ion intensities and other metrics
#' @importFrom dplyr select %>%
#' @importFrom plyr llply
#' @importFrom data.table rbindlist
#' @export read_masic_data_from_DMS

read_masic_data_from_DMS <- function(data_pkg, interference_score=FALSE){
   # library("plyr")
   # library("data.table")
   
   # call gc upon exiting this function. All manners of exiting (return, error) count
   on.exit(gc(), add = TRUE)

   # Fetch job records for data package(s)
   if(length(data_pkg) > 1){
      job_rec_ls <- lapply(data_pkg, get_job_records_by_dataset_package)
      jobRecords <- Reduce(rbind, job_rec_ls)
   }else{
      jobRecords <- get_job_records_by_dataset_package(data_pkg)
   }

   jobRecords <- jobRecords[grepl("MASIC", jobRecords$Tool),]

   masicData <- get_results_for_multiple_jobs.dt(jobRecords)
   gc()

   if (interference_score) {
     masicStats = llply( jobRecords[["Folder"]],
                      get_results_for_single_job.dt,
                      fileNamePttrn="_SICstats.txt",
                      .progress = "text") %>%
        rbindlist(.) %>% as.data.frame(.)
     
     gc()
     
     masicStats <- masicStats[,-2] # Remove redundant Dataset column
     masicData  <- masicData[,-2] # Remove redundant Dataset column

     # Combine masicData and masicStats
     masicData <- select(masicData, Dataset, ScanNumber,
                 starts_with("Ion"), -contains("Resolution"))
     masicStats <- select(masicStats, Dataset, ScanNumber = FragScanNumber,
                 contains('InterferenceScore'))
     masicData <- inner_join(masicData, masicStats)
     rm(masicStats)

     return(masicData)
   }
   masicData <- masicData[,-2]
   masicData <- select(masicData, Dataset, ScanNumber,
                       starts_with("Ion"), -contains("Resolution"))

   return(masicData)

}


# fetch_masic_data_for_single_datset <- function(pathToFile, fileNamePttrn ){
#   pathToFile = list.files( path=as.character(pathToFile),
#                            pattern=fileNamePttrn,
#                            full.names=T)
#   if(length(pathToFile) == 0){
#     stop("can't find the results file")
#   }
#   if(length(pathToFile) > 1){
#     stop("ambiguous results files")
#   }
#   results = read.delim( pathToFile, header=T, stringsAsFactors = FALSE)
#   dataset = strsplit( basename(pathToFile), split=fileNamePttrn)[[1]]
#   out = data.table(Dataset=dataset, results)
#   return(out)
# }





#
#
#
#
# library("devtools")
# source_url("https://raw.githubusercontent.com/vladpetyuk/PNNL_misc/master/PNNL_DMS_utils.R")
#
#
# # 1
# jobRecords <- lapply(c(2930,2988,3087), get_job_records_by_dataset_package)
# jobRecords <- Reduce(rbind, jobRecords)
# jobRecords <- subset(jobRecords, Tool == "MASIC_Finnigan")
#
#
#
# system.time({
#     masicData <- get_results_for_multiple_jobs.dt(jobRecords)
# })
#
#
# library(plyr)
# library(data.table)
# results = llply( jobRecords[["Folder"]],
#                  get_results_for_single_job.dt,
#                  fileNamePattern="_SICstats.txt",
#                  .progress = "text")
# results.dt <- rbindlist(results)
# masicStats <- as.data.frame(results.dt)
#
# # hack to remove redundant Dataset column
# masicData  <- masicData[,-2] # use make.names and then remove Dataset.1
# masicStats <- masicStats[,-2]
# colnames(masicStats)[colnames(masicStats) == "FragScanNumber"] <- "ScanNumber" # dplyr::rename
#
# library(dplyr)
#
# x <- select(masicData, Dataset, ScanNumber, starts_with("Ion"), -contains("Resolution"))
# y <- select(masicStats, Dataset, ScanNumber, InterferenceScore)
# z <- inner_join(x, y)
# masicData <- z
# save(masicData, file="masicData_original.RData")
#
#
#
#
#
#