Mercurial > repos > computational-metabolomics > mspurity_purityx
comparison purityX.R @ 0:a141be614e76 draft
"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("--xset_path"), type="character"), | |
7 make_option(c("-o", "--out_dir"), type="character"), | |
8 make_option(c("--mzML_path"), type="character"), | |
9 make_option("--minOffset", default=0.5), | |
10 make_option("--maxOffset", default=0.5), | |
11 make_option("--ilim", default=0.05), | |
12 make_option("--iwNorm", default="none", type="character"), | |
13 make_option("--exclude_isotopes", action="store_true"), | |
14 make_option("--isotope_matrix", type="character"), | |
15 make_option("--purityType", default="purityFWHMmedian"), | |
16 make_option("--singleFile", default=0), | |
17 make_option("--cores", default=4), | |
18 make_option("--xgroups", type="character"), | |
19 make_option("--rdata_name", default='xset'), | |
20 make_option("--camera_xcms", default='xset'), | |
21 make_option("--files", type="character"), | |
22 make_option("--galaxy_files", type="character"), | |
23 make_option("--choose_class", type="character"), | |
24 make_option("--ignore_files", type="character"), | |
25 make_option("--rtraw_columns", action="store_true") | |
26 ) | |
27 | |
28 | |
29 opt<- parse_args(OptionParser(option_list=option_list)) | |
30 print(opt) | |
31 | |
32 | |
33 if (!is.null(opt$xgroups)){ | |
34 xgroups = as.numeric(strsplit(opt$xgroups, ',')[[1]]) | |
35 }else{ | |
36 xgroups = NULL | |
37 } | |
38 | |
39 | |
40 | |
41 print(xgroups) | |
42 | |
43 if (!is.null(opt$remove_nas)){ | |
44 df <- df[!is.na(df$mz),] | |
45 } | |
46 | |
47 if (is.null(opt$isotope_matrix)){ | |
48 im <- NULL | |
49 }else{ | |
50 im <- read.table(opt$isotope_matrix, | |
51 header = TRUE, sep='\t', stringsAsFactors = FALSE) | |
52 } | |
53 | |
54 if (is.null(opt$exclude_isotopes)){ | |
55 isotopes <- FALSE | |
56 }else{ | |
57 isotopes <- TRUE | |
58 } | |
59 | |
60 if (is.null(opt$rtraw_columns)){ | |
61 rtraw_columns <- FALSE | |
62 }else{ | |
63 rtraw_columns <- TRUE | |
64 } | |
65 | |
66 loadRData <- function(rdata_path, xset_name){ | |
67 #loads an RData file, and returns the named xset object if it is there | |
68 load(rdata_path) | |
69 return(get(ls()[ls() == xset_name])) | |
70 } | |
71 | |
72 target_obj <- loadRData(opt$xset_path, opt$rdata_name) | |
73 | |
74 if (opt$camera_xcms=='camera'){ | |
75 xset <- target_obj@xcmsSet | |
76 }else{ | |
77 xset <- target_obj | |
78 } | |
79 | |
80 print(xset) | |
81 | |
82 minOffset = as.numeric(opt$minOffset) | |
83 maxOffset = as.numeric(opt$maxOffset) | |
84 | |
85 | |
86 if (opt$iwNorm=='none'){ | |
87 iwNorm = FALSE | |
88 iwNormFun = NULL | |
89 }else if (opt$iwNorm=='gauss'){ | |
90 iwNorm = TRUE | |
91 iwNormFun = msPurity::iwNormGauss(minOff=-minOffset, maxOff=maxOffset) | |
92 }else if (opt$iwNorm=='rcosine'){ | |
93 iwNorm = TRUE | |
94 iwNormFun = msPurity::iwNormRcosine(minOff=-minOffset, maxOff=maxOffset) | |
95 }else if (opt$iwNorm=='QE5'){ | |
96 iwNorm = TRUE | |
97 iwNormFun = msPurity::iwNormQE.5() | |
98 } | |
99 | |
100 print(xset@filepaths) | |
101 | |
102 if (!is.null(opt$files)){ | |
103 updated_filepaths <- trimws(strsplit(opt$files, ',')[[1]]) | |
104 updated_filepaths <- updated_filepaths[updated_filepaths != ""] | |
105 print(updated_filepaths) | |
106 updated_filenames = basename(updated_filepaths) | |
107 original_filenames = basename(xset@filepaths) | |
108 update_idx = match(updated_filenames, original_filenames) | |
109 | |
110 if (!is.null(opt$galaxy_files)){ | |
111 galaxy_files <- trimws(strsplit(opt$galaxy_files, ',')[[1]]) | |
112 galaxy_files <- galaxy_files[galaxy_files != ""] | |
113 xset@filepaths <- galaxy_files[update_idx] | |
114 }else{ | |
115 xset@filepaths <- updated_filepaths[update_idx] | |
116 } | |
117 } | |
118 | |
119 if (!is.null(opt$choose_class)){ | |
120 classes <- trimws(strsplit(opt$choose_class, ',')[[1]]) | |
121 | |
122 | |
123 ignore_files_class <- which(!as.character(xset@phenoData$class) %in% classes) | |
124 | |
125 print('choose class') | |
126 print(ignore_files_class) | |
127 }else{ | |
128 ignore_files_class <- NA | |
129 } | |
130 | |
131 if (!is.null(opt$ignore_files)){ | |
132 ignore_files_string <- trimws(strsplit(opt$ignore_files, ',')[[1]]) | |
133 filenames <- rownames(xset@phenoData) | |
134 ignore_files <- which(filenames %in% ignore_files_string) | |
135 | |
136 ignore_files <- unique(c(ignore_files, ignore_files_class)) | |
137 ignore_files <- ignore_files[ignore_files != ""] | |
138 }else{ | |
139 if (anyNA(ignore_files_class)){ | |
140 ignore_files <- NULL | |
141 }else{ | |
142 ignore_files <- ignore_files_class | |
143 } | |
144 | |
145 } | |
146 | |
147 print('ignore_files') | |
148 print(ignore_files) | |
149 | |
150 | |
151 ppLCMS <- msPurity::purityX(xset=xset, | |
152 offsets=c(minOffset, maxOffset), | |
153 cores=opt$cores, | |
154 xgroups=xgroups, | |
155 purityType=opt$purityType, | |
156 ilim = opt$ilim, | |
157 isotopes = isotopes, | |
158 im = im, | |
159 iwNorm = iwNorm, | |
160 iwNormFun = iwNormFun, | |
161 singleFile = opt$singleFile, | |
162 fileignore = ignore_files, | |
163 rtrawColumns=rtraw_columns) | |
164 | |
165 | |
166 dfp <- ppLCMS@predictions | |
167 | |
168 # to make compatable with deconrank | |
169 colnames(dfp)[colnames(dfp)=='grpid'] = 'peakID' | |
170 colnames(dfp)[colnames(dfp)=='median'] = 'medianPurity' | |
171 colnames(dfp)[colnames(dfp)=='mean'] = 'meanPurity' | |
172 colnames(dfp)[colnames(dfp)=='sd'] = 'sdPurity' | |
173 colnames(dfp)[colnames(dfp)=='stde'] = 'sdePurity' | |
174 colnames(dfp)[colnames(dfp)=='RSD'] = 'cvPurity' | |
175 colnames(dfp)[colnames(dfp)=='pknm'] = 'pknmPurity' | |
176 if(sum(is.na(dfp$medianPurity))>0){ | |
177 dfp[is.na(dfp$medianPurity),]$medianPurity = 0 | |
178 } | |
179 | |
180 | |
181 print(head(dfp)) | |
182 write.table(dfp, file.path(opt$out_dir, 'purityX_output.tsv'), row.names=FALSE, sep='\t') | |
183 | |
184 save.image(file.path(opt$out_dir, 'purityX_output.RData')) |