Mercurial > repos > computational-metabolomics > mspurity_combineannotations
view purityX.R @ 5:03b45dceb134 draft
"planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit b1b879e29d5d6c97fdc3636aa6e900ad03695f9e"
author | computational-metabolomics |
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date | Fri, 13 Nov 2020 09:57:42 +0000 |
parents | 7f3183988100 |
children | 18c0038dde9c |
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library(msPurity) library(optparse) print(sessionInfo()) option_list <- list( make_option(c("--xset_path"), type="character"), make_option(c("-o", "--out_dir"), type="character"), make_option(c("--mzML_path"), type="character"), make_option("--minOffset", default=0.5), make_option("--maxOffset", default=0.5), make_option("--ilim", default=0.05), make_option("--iwNorm", default="none", type="character"), make_option("--exclude_isotopes", action="store_true"), make_option("--isotope_matrix", type="character"), make_option("--purityType", default="purityFWHMmedian"), make_option("--singleFile", default=0), make_option("--cores", default=4), make_option("--xgroups", type="character"), make_option("--rdata_name", default='xset'), make_option("--camera_xcms", default='xset'), make_option("--files", type="character"), make_option("--galaxy_files", type="character"), make_option("--choose_class", type="character"), make_option("--ignore_files", type="character"), make_option("--rtraw_columns", action="store_true") ) opt<- parse_args(OptionParser(option_list=option_list)) print(opt) if (!is.null(opt$xgroups)){ xgroups = as.numeric(strsplit(opt$xgroups, ',')[[1]]) }else{ xgroups = NULL } print(xgroups) if (!is.null(opt$remove_nas)){ df <- df[!is.na(df$mz),] } if (is.null(opt$isotope_matrix)){ im <- NULL }else{ im <- read.table(opt$isotope_matrix, header = TRUE, sep='\t', stringsAsFactors = FALSE) } if (is.null(opt$exclude_isotopes)){ isotopes <- FALSE }else{ isotopes <- TRUE } if (is.null(opt$rtraw_columns)){ rtraw_columns <- FALSE }else{ rtraw_columns <- TRUE } loadRData <- function(rdata_path, xset_name){ #loads an RData file, and returns the named xset object if it is there load(rdata_path) return(get(ls()[ls() == xset_name])) } target_obj <- loadRData(opt$xset_path, opt$rdata_name) if (opt$camera_xcms=='camera'){ xset <- target_obj@xcmsSet }else{ xset <- target_obj } print(xset) minOffset = as.numeric(opt$minOffset) maxOffset = as.numeric(opt$maxOffset) if (opt$iwNorm=='none'){ iwNorm = FALSE iwNormFun = NULL }else if (opt$iwNorm=='gauss'){ iwNorm = TRUE iwNormFun = msPurity::iwNormGauss(minOff=-minOffset, maxOff=maxOffset) }else if (opt$iwNorm=='rcosine'){ iwNorm = TRUE iwNormFun = msPurity::iwNormRcosine(minOff=-minOffset, maxOff=maxOffset) }else if (opt$iwNorm=='QE5'){ iwNorm = TRUE iwNormFun = msPurity::iwNormQE.5() } print(xset@filepaths) if (!is.null(opt$files)){ updated_filepaths <- trimws(strsplit(opt$files, ',')[[1]]) updated_filepaths <- updated_filepaths[updated_filepaths != ""] print(updated_filepaths) updated_filenames = basename(updated_filepaths) original_filenames = basename(xset@filepaths) update_idx = match(updated_filenames, original_filenames) if (!is.null(opt$galaxy_files)){ galaxy_files <- trimws(strsplit(opt$galaxy_files, ',')[[1]]) galaxy_files <- galaxy_files[galaxy_files != ""] xset@filepaths <- galaxy_files[update_idx] }else{ xset@filepaths <- updated_filepaths[update_idx] } } if (!is.null(opt$choose_class)){ classes <- trimws(strsplit(opt$choose_class, ',')[[1]]) ignore_files_class <- which(!as.character(xset@phenoData$class) %in% classes) print('choose class') print(ignore_files_class) }else{ ignore_files_class <- NA } if (!is.null(opt$ignore_files)){ ignore_files_string <- trimws(strsplit(opt$ignore_files, ',')[[1]]) filenames <- rownames(xset@phenoData) ignore_files <- which(filenames %in% ignore_files_string) ignore_files <- unique(c(ignore_files, ignore_files_class)) ignore_files <- ignore_files[ignore_files != ""] }else{ if (anyNA(ignore_files_class)){ ignore_files <- NULL }else{ ignore_files <- ignore_files_class } } print('ignore_files') print(ignore_files) ppLCMS <- msPurity::purityX(xset=xset, offsets=c(minOffset, maxOffset), cores=opt$cores, xgroups=xgroups, purityType=opt$purityType, ilim = opt$ilim, isotopes = isotopes, im = im, iwNorm = iwNorm, iwNormFun = iwNormFun, singleFile = opt$singleFile, fileignore = ignore_files, rtrawColumns=rtraw_columns) dfp <- ppLCMS@predictions # to make compatable with deconrank colnames(dfp)[colnames(dfp)=='grpid'] = 'peakID' colnames(dfp)[colnames(dfp)=='median'] = 'medianPurity' colnames(dfp)[colnames(dfp)=='mean'] = 'meanPurity' colnames(dfp)[colnames(dfp)=='sd'] = 'sdPurity' colnames(dfp)[colnames(dfp)=='stde'] = 'sdePurity' colnames(dfp)[colnames(dfp)=='RSD'] = 'cvPurity' colnames(dfp)[colnames(dfp)=='pknm'] = 'pknmPurity' if(sum(is.na(dfp$medianPurity))>0){ dfp[is.na(dfp$medianPurity),]$medianPurity = 0 } print(head(dfp)) write.table(dfp, file.path(opt$out_dir, 'purityX_output.tsv'), row.names=FALSE, sep='\t') save.image(file.path(opt$out_dir, 'purityX_output.RData'))