Mercurial > repos > computational-metabolomics > mspurity_frag4feature

comparison dimsPredictPuritySingle.R @ 0:85bc606fd219 draft default tip

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"planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit 2579c8746819670348c378f86116f83703c493eb"
author computational-metabolomics
date Thu, 04 Mar 2021 12:22:55 +0000
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comparison
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-1:000000000000 0:85bc606fd219
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 if (file.exists(opt$mzML_file)) {
77 mzML_file <- opt$mzML_file
78 }else if (!is.null(opt$mzML_files)) {
79 mzML_file <- find_mzml_file(opt$mzML_files, opt$mzML_galaxy_names, filename)
80 }else{
81 mzML_file <- file.path(opt$mzML_file, filename)
82 }
83
84 # Update the dimspy output with the correct information
85 df <- indf[4:nrow(indf), ]
86 if ("blank_flag" %in% colnames(df)) {
87 df <- df[df$blank_flag == 1, ]
88 }
89 colnames(df)[colnames(df) == "m.z"] <- "mz"
90
91 if ("nan" %in% df$mz) {
92 df[df$mz == "nan", ]$mz <- NA
93 }
94 df$mz <- as.numeric(df$mz)
95 }
96
97 if (!is.null(opt$remove_nas)) {
98 df <- df[!is.na(df$mz), ]
99 }
100
101 if (is.null(opt$isotope_matrix)) {
102 im <- NULL
103 }else{
104 im <- read.table(opt$isotope_matrix,
105 header = TRUE, sep = "\t", stringsAsFactors = FALSE)
106 }
107
108 if (is.null(opt$exclude_isotopes)) {
109 isotopes <- FALSE
110 }else{
111 isotopes <- TRUE
112 }
113
114 if (is.null(opt$sim)) {
115 sim <- FALSE
116 }else{
117 sim <- TRUE
118 }
119
120 minOffset <- as.numeric(opt$minoffset)
121 maxOffset <- as.numeric(opt$maxoffset)
122
123 if (opt$iwNorm == "none") {
124 iwNorm <- FALSE
125 iwNormFun <- NULL
126 }else if (opt$iwNorm == "gauss") {
127 iwNorm <- TRUE
128 iwNormFun <- msPurity::iwNormGauss(minOff = -minOffset, maxOff = maxOffset)
129 }else if (opt$iwNorm == "rcosine") {
130 iwNorm <- TRUE
131 iwNormFun <- msPurity::iwNormRcosine(minOff = -minOffset, maxOff = maxOffset)
132 }else if (opt$iwNorm == "QE5") {
133 iwNorm <- TRUE
134 iwNormFun <- msPurity::iwNormQE.5()
135 }
136
137 print("FIRST ROWS OF PEAK FILE")
138 print(head(df))
139 print(mzML_file)
140 predicted <- msPurity::dimsPredictPuritySingle(df$mz,
141 filepth = mzML_file,
142 minOffset = minOffset,
143 maxOffset = maxOffset,
144 ppm = opt$ppm,
145 mzML = TRUE,
146 sim = sim,
147 ilim = opt$ilim,
148 isotopes = isotopes,
149 im = im,
150 iwNorm = iwNorm,
151 iwNormFun = iwNormFun
152 )
153 predicted <- cbind(df, predicted)
154
155 print(head(predicted))
156 print(file.path(opt$out_dir, "dimsPredictPuritySingle_output.tsv"))
157
158 write.table(predicted,
159 file.path(opt$out_dir, "dimsPredictPuritySingle_output.tsv"),
160 row.names = FALSE, sep = "\t")