Mercurial > repos > computational-metabolomics > mspurity_purityx

comparison dimsPredictPuritySingle.R @ 0:a141be614e76 draft

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"planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit cb903cd93f9378cfb5eeb68512a54178dcea7bbc-dirty"
author computational-metabolomics
date Wed, 27 Nov 2019 12:41:53 -0500
parents
children 6b9a83e08467
comparison
equal deleted inserted replaced
-1:000000000000 0:a141be614e76
1 library(msPurity)
2 library(optparse)
3 print(sessionInfo())
4
5 option_list <- list(
6 make_option(c("--mzML_file"), type="character"),
7 make_option(c("--mzML_files"), type="character"),
8 make_option(c("--mzML_filename"), type="character", default=''),
9 make_option(c("--mzML_galaxy_names"), type="character", default=''),
10 make_option(c("--peaks_file"), type="character"),
11 make_option(c("-o", "--out_dir"), type="character"),
12 make_option("--minoffset", default=0.5),
13 make_option("--maxoffset", default=0.5),
14 make_option("--ilim", default=0.05),
15 make_option("--ppm", default=4),
16 make_option("--dimspy", action="store_true"),
17 make_option("--sim", action="store_true"),
18 make_option("--remove_nas", action="store_true"),
19 make_option("--iwNorm", default="none", type="character"),
20 make_option("--file_num_dimspy", default=1),
21 make_option("--exclude_isotopes", action="store_true"),
22 make_option("--isotope_matrix", type="character")
23 )
24
25 # store options
26 opt<- parse_args(OptionParser(option_list=option_list))
27
28 print(sessionInfo())
29 print(opt)
30
31 print(opt$mzML_files)
32 print(opt$mzML_galaxy_names)
33
34 str_to_vec <- function(x){
35 print(x)
36 x <- trimws(strsplit(x, ',')[[1]])
37 return(x[x != ""])
38 }
39
40 find_mzml_file <- function(mzML_files, galaxy_names, mzML_filename){
41 mzML_filename <- trimws(mzML_filename)
42 mzML_files <- str_to_vec(mzML_files)
43 galaxy_names <- str_to_vec(galaxy_names)
44 if (mzML_filename %in% galaxy_names){
45 return(mzML_files[galaxy_names==mzML_filename])
46 }else{
47 stop(paste("mzML file not found - ", mzML_filename))
48 }
49 }
50
51
52 if (is.null(opt$dimspy)){
53 df <- read.table(opt$peaks_file, header = TRUE, sep='\t')
54 if (file.exists(opt$mzML_file)){
55 mzML_file <- opt$mzML_file
56 }else if (!is.null(opt$mzML_files)){
57 mzML_file <- find_mzml_file(opt$mzML_files, opt$mzML_galaxy_names,
58 opt$mzML_filename)
59 }else{
60 mzML_file <- file.path(opt$mzML_file, filename)
61 }
62 }else{
63 indf <- read.table(opt$peaks_file,
64 header = TRUE, sep='\t', stringsAsFactors = FALSE)
65
66 filename <- colnames(indf)[8:ncol(indf)][opt$file_num_dimspy]
67 print(filename)
68 # check if the data file is mzML or RAW (can only use mzML currently) so
69 # we expect an mzML file of the same name in the same folder
70 indf$i <- indf[,colnames(indf)==filename]
71 indf[,colnames(indf)==filename] <- as.numeric(indf[,colnames(indf)==filename])
72
73 filename = sub("raw", "mzML", filename, ignore.case = TRUE)
74 print(filename)
75
76
77 if (file.exists(opt$mzML_file)){
78 mzML_file <- opt$mzML_file
79 }else if (!is.null(opt$mzML_files)){
80 mzML_file <- find_mzml_file(opt$mzML_files, opt$mzML_galaxy_names, filename)
81 }else{
82 mzML_file <- file.path(opt$mzML_file, filename)
83 }
84
85 # Update the dimspy output with the correct information
86 df <- indf[4:nrow(indf),]
87 if ('blank_flag' %in% colnames(df)){
88 df <- df[df$blank_flag==1,]
89 }
90 colnames(df)[colnames(df)=='m.z'] <- 'mz'
91
92 if ('nan' %in% df$mz){
93 df[df$mz=='nan',]$mz <- NA
94 }
95 df$mz <- as.numeric(df$mz)
96 }
97
98 if (!is.null(opt$remove_nas)){
99 df <- df[!is.na(df$mz),]
100 }
101
102 if (is.null(opt$isotope_matrix)){
103 im <- NULL
104 }else{
105 im <- read.table(opt$isotope_matrix,
106 header = TRUE, sep='\t', stringsAsFactors = FALSE)
107 }
108
109 if (is.null(opt$exclude_isotopes)){
110 isotopes <- FALSE
111 }else{
112 isotopes <- TRUE
113 }
114
115 if (is.null(opt$sim)){
116 sim=FALSE
117 }else{
118 sim=TRUE
119 }
120
121 minOffset = as.numeric(opt$minoffset)
122 maxOffset = as.numeric(opt$maxoffset)
123
124 if (opt$iwNorm=='none'){
125 iwNorm = FALSE
126 iwNormFun = NULL
127 }else if (opt$iwNorm=='gauss'){
128 iwNorm = TRUE
129 iwNormFun = msPurity::iwNormGauss(minOff=-minOffset, maxOff=maxOffset)
130 }else if (opt$iwNorm=='rcosine'){
131 iwNorm = TRUE
132 iwNormFun = msPurity::iwNormRcosine(minOff=-minOffset, maxOff=maxOffset)
133 }else if (opt$iwNorm=='QE5'){
134 iwNorm = TRUE
135 iwNormFun = msPurity::iwNormQE.5()
136 }
137
138 print('FIRST ROWS OF PEAK FILE')
139 print(head(df))
140 print(mzML_file)
141 predicted <- msPurity::dimsPredictPuritySingle(df$mz,
142 filepth=mzML_file,
143 minOffset=minOffset,
144 maxOffset=maxOffset,
145 ppm=opt$ppm,
146 mzML=TRUE,
147 sim = sim,
148 ilim = opt$ilim,
149 isotopes = isotopes,
150 im = im,
151 iwNorm = iwNorm,
152 iwNormFun = iwNormFun
153 )
154 predicted <- cbind(df, predicted)
155
156 print(head(predicted))
157 print(file.path(opt$out_dir, 'dimsPredictPuritySingle_output.tsv'))
158
159 write.table(predicted,
160 file.path(opt$out_dir, 'dimsPredictPuritySingle_output.tsv'),
161 row.names=FALSE, sep='\t')
162
163