Mercurial > repos > computational-metabolomics > mspurity_averagefragspectra
view flagRemove.R @ 0:50eedf5ad217 draft
"planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit cb903cd93f9378cfb5eeb68512a54178dcea7bbc-dirty"
author | computational-metabolomics |
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date | Wed, 27 Nov 2019 13:35:22 -0500 |
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children | 4207233ead9c |
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library(msPurity) library(optparse) print(sessionInfo()) option_list <- list( make_option(c("-o", "--out_dir"), type="character", default=getwd(), help="Output folder for resulting files [default = %default]" ), make_option(c("-x", "--xset_path"), type="character", default=file.path(getwd(),"xset.rds"), help="The path to the xcmsSet object [default = %default]" ), make_option("--polarity", default=NA, help="polarity (just used for naming purpose for files being saved) [positive, negative, NA] [default %default]" ), make_option("--rsd_i_blank", default=100, help="RSD threshold for the blank [default = %default]" ), make_option("--minfrac_blank", default=0.5, help="minimum fraction of files for features needed for the blank [default = %default]" ), make_option("--rsd_rt_blank", default=100, help="RSD threshold for the RT of the blank [default = %default]" ), make_option("--ithres_blank", default=0, help="Intensity threshold for the blank [default = %default]" ), make_option("--s2b", default=10, help="fold change (sample/blank) needed for sample peak to be allowed. e.g. if s2b set to 10 and the recorded sample 'intensity' value was 100 and blank was 10. 1000/10 = 100, so sample has fold change higher than the threshold and the peak is not considered a blank [default = %default]" ), make_option("--blank_class", default='blank', type="character", help="A string representing the class that will be used for the blank.[default = %default]" ), make_option("--egauss_thr", default=NA, help="Threshold for filtering out non gaussian shaped peaks. Note this only works if the 'verbose columns' and 'fit gauss' was used with xcms [default = %default]" ), make_option("--rsd_i_sample", default=100, help="RSD threshold for the samples [default = %default]" ), make_option("--minfrac_sample", default=0.8, help="minimum fraction of files for features needed for the samples [default = %default]" ), make_option("--rsd_rt_sample", default=100, help="RSD threshold for the RT of the samples [default = %default]" ), make_option("--ithres_sample", default=5000, help="Intensity threshold for the sample [default = %default]" ), make_option("--grp_rm_ids", default=NA, help="vector of grouped_xcms peaks to remove (corresponds to the row from xcms::group output) [default = %default]" ), make_option("--remove_spectra", action="store_true", help=" TRUE if flagged spectra is to be removed [default = %default]" ), make_option("--minfrac_xcms", default=0.5, help="minfrac for xcms grouping [default = %default]" ), make_option("--mzwid", default=0.001, help="mzwid for xcms grouping [default = %default]" ), make_option("--bw", default=5, help="bw for xcms grouping [default = %default]" ), make_option("--temp_save", action="store_true", help="Assign True if files for each step saved (for testing purposes) [default = %default]" ), make_option("--samplelist", type="character", help="Sample list to determine the blank class") ) #make_option("--multilist", action="store_true" # help="NOT CURRENTLY IMPLEMENTED: If paired blank removal is to be performed a - multilist - sample list file has to be provided" #), # store options opt<- parse_args(OptionParser(option_list=option_list)) opt <- replace(opt, opt == "NA", NA) if (is.null(opt$temp_save)){ temp_save<-FALSE }else{ temp_save<-TRUE } if (is.null(opt$remove_spectra)){ remove_spectra<-FALSE }else{ remove_spectra<-TRUE } print(opt) getxcmsSetObject <- function(xobject) { # XCMS 1.x if (class(xobject) == "xcmsSet") return (xobject) # XCMS 3.x if (class(xobject) == "XCMSnExp") { # Get the legacy xcmsSet object suppressWarnings(xset <- as(xobject, 'xcmsSet')) sampclass(xset) <- xset@phenoData$sample_group return (xset) } } loadRData <- function(rdata_path, name){ #loads an RData file, and returns the named xset object if it is there load(rdata_path) return(get(ls()[ls() %in% name])) } xset <- getxcmsSetObject(loadRData(opt$xset_path, c('xset','xdata'))) print(xset) if (is.null(opt$samplelist)){ blank_class <- opt$blank_class }else{ samplelist <- read.table(opt$samplelist, sep='\t', header=TRUE) samplelist_blank <- unique(samplelist$sample_class[samplelist$blank=='yes']) chosen_blank <- samplelist_blank[samplelist_blank %in% xset@phenoData$class] if (length(chosen_blank)>1){ print('ERROR: only 1 blank is currently allowed to be used with this tool') exit() } blank_class <- as.character(chosen_blank) print(blank_class) } if (is.null(opt$multilist)){ ffrm_out <- flag_remove(xset, pol=opt$polarity, rsd_i_blank=opt$rsd_i_blank, minfrac_blank=opt$minfrac_blank, rsd_rt_blank=opt$rsd_rt_blank, ithres_blank=opt$ithres_blank, s2b=opt$s2b, ref.class=blank_class, egauss_thr=opt$egauss_thr, rsd_i_sample=opt$rsd_i_sample, minfrac_sample=opt$minfrac_sample, rsd_rt_sample=opt$rsd_rt_sample, ithres_sample=opt$ithres_sample, minfrac_xcms=opt$minfrac_xcms, mzwid=opt$mzwid, bw=opt$bw, out_dir=opt$out_dir, temp_save=temp_save, remove_spectra=remove_spectra, grp_rm_ids=unlist(strsplit(as.character(opt$grp_rm_ids), split=", "))[[1]]) print('flag remove finished') xset <- ffrm_out[[1]] grp_peaklist <- ffrm_out[[2]] removed_peaks <- ffrm_out[[3]] save.image(file=file.path(opt$out_dir, 'xset_filtered.RData')) # grpid needed for mspurity ID needed for deconrank... (will clean up at some up) peak_pth <- file.path(opt$out_dir, 'peaklist_filtered.tsv') print(peak_pth) write.table(data.frame('grpid'=rownames(grp_peaklist), 'ID'=rownames(grp_peaklist), grp_peaklist), peak_pth, row.names=FALSE, sep='\t') removed_peaks <- data.frame(removed_peaks) write.table(data.frame('ID'=rownames(removed_peaks),removed_peaks), file.path(opt$out_dir, 'removed_peaks.tsv'), row.names=FALSE, sep='\t') }else{ # TODO #xsets <- split(xset, multilist_df$multlist) # #mult_grps <- unique(multilist_df$multlist) # #for (mgrp in mult_grps){ # xset_i <- xsets[mgrp] # xcms::group(xset_i, # # } }