Mercurial > repos > lecorguille > xcms_plot_chromatogram
comparison lib.r @ 14:8846a03995d3 draft
planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics/ commit 2cb157bd9a8701a3d6874e084032cbd050b8953e
author | workflow4metabolomics |
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date | Mon, 11 Sep 2023 09:18:38 +0000 |
parents | 024974037c4e |
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13:024974037c4e | 14:8846a03995d3 |
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2 # lib.r for Galaxy Workflow4Metabolomics xcms tools | 2 # lib.r for Galaxy Workflow4Metabolomics xcms tools |
3 | 3 |
4 #@author G. Le Corguille | 4 #@author G. Le Corguille |
5 # solve an issue with batch if arguments are logical TRUE/FALSE | 5 # solve an issue with batch if arguments are logical TRUE/FALSE |
6 parseCommandArgs <- function(...) { | 6 parseCommandArgs <- function(...) { |
7 args <- batch::parseCommandArgs(...) | 7 args <- batch::parseCommandArgs(...) |
8 for (key in names(args)) { | 8 for (key in names(args)) { |
9 if (args[key] %in% c("TRUE", "FALSE")) | 9 if (args[key] %in% c("TRUE", "FALSE")) |
10 args[key] <- as.logical(args[key]) | 10 args[key] <- as.logical(args[key]) |
11 } | 11 } |
12 return(args) | 12 return(args) |
13 } | 13 } |
14 | 14 |
15 #@author G. Le Corguille | 15 #@author G. Le Corguille |
16 # This function will | 16 # This function will |
17 # - load the packages | 17 # - load the packages |
18 # - display the sessionInfo | 18 # - display the sessionInfo |
19 loadAndDisplayPackages <- function(pkgs) { | 19 loadAndDisplayPackages <- function(pkgs) { |
20 for (pkg in pkgs) suppressPackageStartupMessages(stopifnot(library(pkg, quietly = TRUE, logical.return = TRUE, character.only = TRUE))) | 20 for (pkg in pkgs) suppressPackageStartupMessages(stopifnot(library(pkg, quietly = TRUE, logical.return = TRUE, character.only = TRUE))) |
21 | 21 |
22 sessioninfo <- sessionInfo() | 22 sessioninfo <- sessionInfo() |
23 cat(sessioninfo$R.version$version.string, "\n") | 23 cat(sessioninfo$R.version$version.string, "\n") |
24 cat("Main packages:\n") | 24 cat("Main packages:\n") |
25 for (pkg in names(sessioninfo$otherPkgs)) { | 25 for (pkg in names(sessioninfo$otherPkgs)) { |
26 cat(paste(pkg, packageVersion(pkg)), "\t") | 26 cat(paste(pkg, packageVersion(pkg)), "\t") |
27 } | 27 } |
28 cat("\n") | 28 cat("\n") |
29 cat("Other loaded packages:\n") | 29 cat("Other loaded packages:\n") |
30 for (pkg in names(sessioninfo$loadedOnly)) { | 30 for (pkg in names(sessioninfo$loadedOnly)) { |
31 cat(paste(pkg, packageVersion(pkg)), "\t") | 31 cat(paste(pkg, packageVersion(pkg)), "\t") |
32 } | 32 } |
33 cat("\n") | 33 cat("\n") |
34 } | 34 } |
35 | 35 |
36 #@author G. Le Corguille | 36 #@author G. Le Corguille |
37 # This function merge several chromBPI or chromTIC into one. | 37 # This function merge several chromBPI or chromTIC into one. |
38 mergeChrom <- function(chrom_merged, chrom) { | 38 mergeChrom <- function(chrom_merged, chrom) { |
39 if (is.null(chrom_merged)) return(NULL) | 39 if (is.null(chrom_merged)) return(NULL) |
40 chrom_merged@.Data <- cbind(chrom_merged@.Data, chrom@.Data) | 40 chrom_merged@.Data <- cbind(chrom_merged@.Data, chrom@.Data) |
41 return(chrom_merged) | 41 return(chrom_merged) |
42 } | 42 } |
43 | 43 |
44 #@author G. Le Corguille | 44 #@author G. Le Corguille |
45 # This function merge several xdata into one. | 45 # This function merge several xdata into one. |
46 mergeXData <- function(args) { | 46 mergeXData <- function(args) { |
47 chromTIC <- NULL | 47 chromTIC <- NULL |
48 chromBPI <- NULL | 48 chromBPI <- NULL |
49 chromTIC_adjusted <- NULL | 49 chromTIC_adjusted <- NULL |
50 chromBPI_adjusted <- NULL | 50 chromBPI_adjusted <- NULL |
51 md5sumList <- NULL | 51 md5sumList <- NULL |
52 for (image in args$images) { | 52 for (image in args$images) { |
53 | 53 |
54 load(image) | 54 load(image) |
55 # Handle infiles | 55 # Handle infiles |
56 if (!exists("singlefile")) singlefile <- NULL | 56 if (!exists("singlefile")) singlefile <- NULL |
57 if (!exists("zipfile")) zipfile <- NULL | 57 if (!exists("zipfile")) zipfile <- NULL |
58 rawFilePath <- retrieveRawfileInTheWorkingDir(singlefile, zipfile, args) | 58 rawFilePath <- retrieveRawfileInTheWorkingDir(singlefile, zipfile, args) |
59 zipfile <- rawFilePath$zipfile | 59 zipfile <- rawFilePath$zipfile |
60 singlefile <- rawFilePath$singlefile | 60 singlefile <- rawFilePath$singlefile |
61 | 61 |
62 if (exists("raw_data")) xdata <- raw_data | 62 if (exists("raw_data")) xdata <- raw_data |
63 if (!exists("xdata")) stop("\n\nERROR: The RData doesn't contain any object called 'xdata'. This RData should have been created by an old version of XMCS 2.*") | 63 if (!exists("xdata")) stop("\n\nERROR: The RData doesn't contain any object called 'xdata'. This RData should have been created by an old version of XMCS 2.*") |
64 | 64 |
65 cat(sampleNamesList$sampleNamesOrigin, "\n") | 65 cat(sampleNamesList$sampleNamesOrigin, "\n") |
66 | 66 |
67 if (!exists("xdata_merged")) { | 67 if (!exists("xdata_merged")) { |
68 xdata_merged <- xdata | 68 xdata_merged <- xdata |
69 singlefile_merged <- singlefile | 69 singlefile_merged <- singlefile |
70 md5sumList_merged <- md5sumList | 70 md5sumList_merged <- md5sumList |
71 sampleNamesList_merged <- sampleNamesList | 71 sampleNamesList_merged <- sampleNamesList |
72 chromTIC_merged <- chromTIC | 72 chromTIC_merged <- chromTIC |
73 chromBPI_merged <- chromBPI | 73 chromBPI_merged <- chromBPI |
74 chromTIC_adjusted_merged <- chromTIC_adjusted | 74 chromTIC_adjusted_merged <- chromTIC_adjusted |
75 chromBPI_adjusted_merged <- chromBPI_adjusted | 75 chromBPI_adjusted_merged <- chromBPI_adjusted |
76 } else { | 76 } else { |
77 if (is(xdata, "XCMSnExp")) xdata_merged <- c(xdata_merged, xdata) | 77 if (is(xdata, "XCMSnExp")) xdata_merged <- c(xdata_merged, xdata) |
78 else if (is(xdata, "OnDiskMSnExp")) xdata_merged <- xcms:::.concatenate_OnDiskMSnExp(xdata_merged, xdata) | 78 else if (is(xdata, "OnDiskMSnExp")) xdata_merged <- xcms:::.concatenate_OnDiskMSnExp(xdata_merged, xdata) |
79 else stop("\n\nERROR: The RData either a OnDiskMSnExp object called raw_data or a XCMSnExp object called xdata") | 79 else stop("\n\nERROR: The RData either a OnDiskMSnExp object called raw_data or a XCMSnExp object called xdata") |
80 | 80 |
81 singlefile_merged <- c(singlefile_merged, singlefile) | 81 singlefile_merged <- c(singlefile_merged, singlefile) |
82 md5sumList_merged$origin <- rbind(md5sumList_merged$origin, md5sumList$origin) | 82 md5sumList_merged$origin <- rbind(md5sumList_merged$origin, md5sumList$origin) |
83 sampleNamesList_merged$sampleNamesOrigin <- c(sampleNamesList_merged$sampleNamesOrigin, sampleNamesList$sampleNamesOrigin) | 83 sampleNamesList_merged$sampleNamesOrigin <- c(sampleNamesList_merged$sampleNamesOrigin, sampleNamesList$sampleNamesOrigin) |
84 sampleNamesList_merged$sampleNamesMakeNames <- c(sampleNamesList_merged$sampleNamesMakeNames, sampleNamesList$sampleNamesMakeNames) | 84 sampleNamesList_merged$sampleNamesMakeNames <- c(sampleNamesList_merged$sampleNamesMakeNames, sampleNamesList$sampleNamesMakeNames) |
85 chromTIC_merged <- mergeChrom(chromTIC_merged, chromTIC) | 85 chromTIC_merged <- mergeChrom(chromTIC_merged, chromTIC) |
86 chromBPI_merged <- mergeChrom(chromBPI_merged, chromBPI) | 86 chromBPI_merged <- mergeChrom(chromBPI_merged, chromBPI) |
87 chromTIC_adjusted_merged <- mergeChrom(chromTIC_adjusted_merged, chromTIC_adjusted) | 87 chromTIC_adjusted_merged <- mergeChrom(chromTIC_adjusted_merged, chromTIC_adjusted) |
88 chromBPI_adjusted_merged <- mergeChrom(chromBPI_adjusted_merged, chromBPI_adjusted) | 88 chromBPI_adjusted_merged <- mergeChrom(chromBPI_adjusted_merged, chromBPI_adjusted) |
89 } | 89 } |
90 } | 90 } |
91 rm(image) | 91 rm(image) |
92 xdata <- xdata_merged; rm(xdata_merged) | 92 xdata <- xdata_merged |
93 singlefile <- singlefile_merged; rm(singlefile_merged) | 93 rm(xdata_merged) |
94 md5sumList <- md5sumList_merged; rm(md5sumList_merged) | 94 singlefile <- singlefile_merged |
95 sampleNamesList <- sampleNamesList_merged; rm(sampleNamesList_merged) | 95 rm(singlefile_merged) |
96 | 96 md5sumList <- md5sumList_merged |
97 if (!is.null(args$sampleMetadata)) { | 97 rm(md5sumList_merged) |
98 cat("\tXSET PHENODATA SETTING...\n") | 98 sampleNamesList <- sampleNamesList_merged |
99 sampleMetadataFile <- args$sampleMetadata | 99 rm(sampleNamesList_merged) |
100 sampleMetadata <- getDataFrameFromFile(sampleMetadataFile, header = F) | 100 |
101 xdata@phenoData@data$sample_group <- sampleMetadata$V2[match(xdata@phenoData@data$sample_name, sampleMetadata$V1)] | 101 if (!is.null(args$sampleMetadata)) { |
102 | 102 cat("\tXSET PHENODATA SETTING...\n") |
103 if (any(is.na(pData(xdata)$sample_group))) { | 103 sampleMetadataFile <- args$sampleMetadata |
104 sample_missing <- pData(xdata)$sample_name[is.na(pData(xdata)$sample_group)] | 104 sampleMetadata <- getDataFrameFromFile(sampleMetadataFile, header = FALSE) |
105 error_message <- paste("Those samples are missing in your sampleMetadata:", paste(sample_missing, collapse = " ")) | 105 xdata@phenoData@data$sample_group <- sampleMetadata$V2[match(xdata@phenoData@data$sample_name, sampleMetadata$V1)] |
106 print(error_message) | 106 |
107 stop(error_message) | 107 if (any(is.na(pData(xdata)$sample_group))) { |
108 } | 108 sample_missing <- pData(xdata)$sample_name[is.na(pData(xdata)$sample_group)] |
109 } | 109 error_message <- paste("Those samples are missing in your sampleMetadata:", paste(sample_missing, collapse = " ")) |
110 | 110 print(error_message) |
111 if (!is.null(chromTIC_merged)) { | 111 stop(error_message) |
112 chromTIC <- chromTIC_merged; chromTIC@phenoData <- xdata@phenoData | 112 } |
113 } | 113 } |
114 if (!is.null(chromBPI_merged)) { | 114 |
115 chromBPI <- chromBPI_merged; chromBPI@phenoData <- xdata@phenoData | 115 if (!is.null(chromTIC_merged)) { |
116 } | 116 chromTIC <- chromTIC_merged |
117 if (!is.null(chromTIC_adjusted_merged)) { | 117 chromTIC@phenoData <- xdata@phenoData |
118 chromTIC_adjusted <- chromTIC_adjusted_merged; chromTIC_adjusted@phenoData <- xdata@phenoData | 118 } |
119 } | 119 if (!is.null(chromBPI_merged)) { |
120 if (!is.null(chromBPI_adjusted_merged)) { | 120 chromBPI <- chromBPI_merged |
121 chromBPI_adjusted <- chromBPI_adjusted_merged; chromBPI_adjusted@phenoData <- xdata@phenoData | 121 chromBPI@phenoData <- xdata@phenoData |
122 } | 122 } |
123 | 123 if (!is.null(chromTIC_adjusted_merged)) { |
124 return(list("xdata" = xdata, "singlefile" = singlefile, "md5sumList" = md5sumList, "sampleNamesList" = sampleNamesList, "chromTIC" = chromTIC, "chromBPI" = chromBPI, "chromTIC_adjusted" = chromTIC_adjusted, "chromBPI_adjusted" = chromBPI_adjusted)) | 124 chromTIC_adjusted <- chromTIC_adjusted_merged |
125 chromTIC_adjusted@phenoData <- xdata@phenoData | |
126 } | |
127 if (!is.null(chromBPI_adjusted_merged)) { | |
128 chromBPI_adjusted <- chromBPI_adjusted_merged | |
129 chromBPI_adjusted@phenoData <- xdata@phenoData | |
130 } | |
131 | |
132 return(list("xdata" = xdata, "singlefile" = singlefile, "md5sumList" = md5sumList, "sampleNamesList" = sampleNamesList, "chromTIC" = chromTIC, "chromBPI" = chromBPI, "chromTIC_adjusted" = chromTIC_adjusted, "chromBPI_adjusted" = chromBPI_adjusted)) | |
125 } | 133 } |
126 | 134 |
127 #@author G. Le Corguille | 135 #@author G. Le Corguille |
128 # This function convert if it is required the Retention Time in minutes | 136 # This function convert if it is required the Retention Time in minutes |
129 RTSecondToMinute <- function(variableMetadata, convertRTMinute) { | 137 RTSecondToMinute <- function(variableMetadata, convertRTMinute) { |
130 if (convertRTMinute) { | 138 if (convertRTMinute) { |
131 #converting the retention times (seconds) into minutes | 139 #converting the retention times (seconds) into minutes |
132 print("converting the retention times into minutes in the variableMetadata") | 140 print("converting the retention times into minutes in the variableMetadata") |
133 variableMetadata[, "rt"] <- variableMetadata[, "rt"] / 60 | 141 variableMetadata[, "rt"] <- variableMetadata[, "rt"] / 60 |
134 variableMetadata[, "rtmin"] <- variableMetadata[, "rtmin"] / 60 | 142 variableMetadata[, "rtmin"] <- variableMetadata[, "rtmin"] / 60 |
135 variableMetadata[, "rtmax"] <- variableMetadata[, "rtmax"] / 60 | 143 variableMetadata[, "rtmax"] <- variableMetadata[, "rtmax"] / 60 |
136 } | 144 } |
137 return(variableMetadata) | 145 return(variableMetadata) |
138 } | 146 } |
139 | 147 |
140 #@author G. Le Corguille | 148 #@author G. Le Corguille |
141 # This function format ions identifiers | 149 # This function format ions identifiers |
142 formatIonIdentifiers <- function(variableMetadata, numDigitsRT = 0, numDigitsMZ = 0) { | 150 formatIonIdentifiers <- function(variableMetadata, numDigitsRT = 0, numDigitsMZ = 0) { |
143 splitDeco <- strsplit(as.character(variableMetadata$name), "_") | 151 splitDeco <- strsplit(as.character(variableMetadata$name), "_") |
144 idsDeco <- sapply(splitDeco, | 152 idsDeco <- sapply(splitDeco, |
145 function(x) { | 153 function(x) { |
146 deco <- unlist(x)[2]; if (is.na(deco)) return("") else return(paste0("_", deco)) | 154 deco <- unlist(x)[2] |
147 } | 155 if (is.na(deco)) return("") else return(paste0("_", deco)) |
148 ) | 156 } |
149 namecustom <- make.unique(paste0("M", round(variableMetadata[, "mz"], numDigitsMZ), "T", round(variableMetadata[, "rt"], numDigitsRT), idsDeco)) | 157 ) |
150 variableMetadata <- cbind(name = variableMetadata$name, namecustom = namecustom, variableMetadata[, !(colnames(variableMetadata) %in% c("name"))]) | 158 namecustom <- make.unique(paste0("M", round(variableMetadata[, "mz"], numDigitsMZ), "T", round(variableMetadata[, "rt"], numDigitsRT), idsDeco)) |
151 return(variableMetadata) | 159 variableMetadata <- cbind(name = variableMetadata$name, namecustom = namecustom, variableMetadata[, !(colnames(variableMetadata) %in% c("name"))]) |
160 return(variableMetadata) | |
152 } | 161 } |
153 | 162 |
154 #@author G. Le Corguille | 163 #@author G. Le Corguille |
155 # This function convert the remain NA to 0 in the dataMatrix | 164 # This function convert the remain NA to 0 in the dataMatrix |
156 naTOzeroDataMatrix <- function(dataMatrix, naTOzero) { | 165 naTOzeroDataMatrix <- function(dataMatrix, naTOzero) { |
157 if (naTOzero) { | 166 if (naTOzero) { |
158 dataMatrix[is.na(dataMatrix)] <- 0 | 167 dataMatrix[is.na(dataMatrix)] <- 0 |
159 } | 168 } |
160 return(dataMatrix) | 169 return(dataMatrix) |
161 } | 170 } |
162 | 171 |
163 #@author G. Le Corguille | 172 #@author G. Le Corguille |
164 # Draw the plotChromPeakDensity 3 per page in a pdf file | 173 # Draw the plotChromPeakDensity 3 per page in a pdf file |
165 getPlotChromPeakDensity <- function(xdata, param = NULL, mzdigit = 4) { | 174 getPlotChromPeakDensity <- function(xdata, param = NULL, mzdigit = 4) { |
166 pdf(file = "plotChromPeakDensity.pdf", width = 16, height = 12) | 175 pdf(file = "plotChromPeakDensity.pdf", width = 16, height = 12) |
167 | 176 |
168 par(mfrow = c(3, 1), mar = c(4, 4, 1, 0.5)) | 177 par(mfrow = c(3, 1), mar = c(4, 4, 1, 0.5)) |
169 | 178 |
170 if (length(unique(xdata$sample_group)) < 10) { | 179 if (length(unique(xdata$sample_group)) < 10) { |
171 group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") | 180 group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") |
172 }else{ | 181 } else { |
173 group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") | 182 group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") |
174 } | 183 } |
175 names(group_colors) <- unique(xdata$sample_group) | 184 names(group_colors) <- unique(xdata$sample_group) |
176 col_per_samp <- as.character(xdata$sample_group) | 185 col_per_samp <- as.character(xdata$sample_group) |
177 for (i in seq_len(length(group_colors))) { | 186 for (i in seq_len(length(group_colors))) { |
178 col_per_samp[col_per_samp == (names(group_colors)[i])] <- group_colors[i] | 187 col_per_samp[col_per_samp == (names(group_colors)[i])] <- group_colors[i] |
179 } | 188 } |
180 | 189 |
181 xlim <- c(min(featureDefinitions(xdata)$rtmin), max(featureDefinitions(xdata)$rtmax)) | 190 xlim <- c(min(featureDefinitions(xdata)$rtmin), max(featureDefinitions(xdata)$rtmax)) |
182 for (i in seq_len(nrow(featureDefinitions(xdata)))) { | 191 for (i in seq_len(nrow(featureDefinitions(xdata)))) { |
183 mzmin <- featureDefinitions(xdata)[i, ]$mzmin | 192 mzmin <- featureDefinitions(xdata)[i, ]$mzmin |
184 mzmax <- featureDefinitions(xdata)[i, ]$mzmax | 193 mzmax <- featureDefinitions(xdata)[i, ]$mzmax |
185 plotChromPeakDensity(xdata, param = param, mz = c(mzmin, mzmax), col = col_per_samp, pch = 16, xlim = xlim, main = paste(round(mzmin, mzdigit), round(mzmax, mzdigit))) | 194 plotChromPeakDensity(xdata, param = param, mz = c(mzmin, mzmax), col = col_per_samp, pch = 16, xlim = xlim, main = paste(round(mzmin, mzdigit), round(mzmax, mzdigit))) |
186 legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) | 195 legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) |
187 } | 196 } |
188 | 197 |
189 dev.off() | 198 dev.off() |
190 } | 199 } |
191 | 200 |
192 #@author G. Le Corguille | 201 #@author G. Le Corguille |
193 # Draw the plotChromPeakDensity 3 per page in a pdf file | 202 # Draw the plotChromPeakDensity 3 per page in a pdf file |
194 getPlotAdjustedRtime <- function(xdata) { | 203 getPlotAdjustedRtime <- function(xdata) { |
195 | 204 |
196 pdf(file = "raw_vs_adjusted_rt.pdf", width = 16, height = 12) | 205 pdf(file = "raw_vs_adjusted_rt.pdf", width = 16, height = 12) |
197 | 206 |
198 # Color by group | 207 # Color by group |
199 if (length(unique(xdata$sample_group)) < 10) { | 208 if (length(unique(xdata$sample_group)) < 10) { |
200 group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") | 209 group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") |
201 } else { | 210 } else { |
202 group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") | 211 group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") |
203 } | 212 } |
204 if (length(group_colors) > 1) { | 213 if (length(group_colors) > 1) { |
205 names(group_colors) <- unique(xdata$sample_group) | 214 names(group_colors) <- unique(xdata$sample_group) |
206 plotAdjustedRtime(xdata, col = group_colors[xdata$sample_group]) | 215 plotAdjustedRtime(xdata, col = group_colors[xdata$sample_group]) |
207 legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) | 216 legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) |
208 } | 217 } |
209 | 218 |
210 # Color by sample | 219 # Color by sample |
211 plotAdjustedRtime(xdata, col = rainbow(length(xdata@phenoData@data$sample_name))) | 220 plotAdjustedRtime(xdata, col = rainbow(length(xdata@phenoData@data$sample_name))) |
212 legend("topright", legend = xdata@phenoData@data$sample_name, col = rainbow(length(xdata@phenoData@data$sample_name)), cex = 0.8, lty = 1) | 221 legend("topright", legend = xdata@phenoData@data$sample_name, col = rainbow(length(xdata@phenoData@data$sample_name)), cex = 0.8, lty = 1) |
213 | 222 |
214 dev.off() | 223 dev.off() |
215 } | 224 } |
216 | 225 |
217 #@author G. Le Corguille | 226 #@author G. Le Corguille |
218 # value: intensity values to be used into, maxo or intb | 227 # value: intensity values to be used into, maxo or intb |
219 getPeaklistW4M <- function(xdata, intval = "into", convertRTMinute = F, numDigitsMZ = 4, numDigitsRT = 0, naTOzero = T, variableMetadataOutput, dataMatrixOutput, sampleNamesList) { | 228 getPeaklistW4M <- function(xdata, intval = "into", convertRTMinute = FALSE, numDigitsMZ = 4, numDigitsRT = 0, naTOzero = TRUE, variableMetadataOutput, dataMatrixOutput, sampleNamesList) { |
220 dataMatrix <- featureValues(xdata, method = "medret", value = intval) | 229 dataMatrix <- featureValues(xdata, method = "medret", value = intval) |
221 colnames(dataMatrix) <- make.names(tools::file_path_sans_ext(colnames(dataMatrix))) | 230 colnames(dataMatrix) <- make.names(tools::file_path_sans_ext(colnames(dataMatrix))) |
222 dataMatrix <- cbind(name = groupnames(xdata), dataMatrix) | 231 dataMatrix <- cbind(name = groupnames(xdata), dataMatrix) |
223 variableMetadata <- featureDefinitions(xdata) | 232 variableMetadata <- featureDefinitions(xdata) |
224 colnames(variableMetadata)[1] <- "mz"; colnames(variableMetadata)[4] <- "rt" | 233 colnames(variableMetadata)[1] <- "mz" |
225 variableMetadata <- data.frame(name = groupnames(xdata), variableMetadata) | 234 colnames(variableMetadata)[4] <- "rt" |
226 | 235 variableMetadata <- data.frame(name = groupnames(xdata), variableMetadata) |
227 variableMetadata <- RTSecondToMinute(variableMetadata, convertRTMinute) | 236 |
228 variableMetadata <- formatIonIdentifiers(variableMetadata, numDigitsRT = numDigitsRT, numDigitsMZ = numDigitsMZ) | 237 variableMetadata <- RTSecondToMinute(variableMetadata, convertRTMinute) |
229 dataMatrix <- naTOzeroDataMatrix(dataMatrix, naTOzero) | 238 variableMetadata <- formatIonIdentifiers(variableMetadata, numDigitsRT = numDigitsRT, numDigitsMZ = numDigitsMZ) |
230 | 239 dataMatrix <- naTOzeroDataMatrix(dataMatrix, naTOzero) |
231 # FIX: issue when the vector at peakidx is too long and is written in a new line during the export | 240 |
232 variableMetadata[, "peakidx"] <- vapply(variableMetadata[, "peakidx"], FUN = paste, FUN.VALUE = character(1), collapse = ",") | 241 # FIX: issue when the vector at peakidx is too long and is written in a new line during the export |
233 | 242 variableMetadata[, "peakidx"] <- vapply(variableMetadata[, "peakidx"], FUN = paste, FUN.VALUE = character(1), collapse = ",") |
234 write.table(variableMetadata, file = variableMetadataOutput, sep = "\t", quote = F, row.names = F) | 243 |
235 write.table(dataMatrix, file = dataMatrixOutput, sep = "\t", quote = F, row.names = F) | 244 write.table(variableMetadata, file = variableMetadataOutput, sep = "\t", quote = FALSE, row.names = FALSE) |
245 write.table(dataMatrix, file = dataMatrixOutput, sep = "\t", quote = FALSE, row.names = FALSE) | |
236 | 246 |
237 } | 247 } |
238 | 248 |
239 #@author G. Le Corguille | 249 #@author G. Le Corguille |
240 # It allow different of field separators | 250 # It allow different of field separators |
241 getDataFrameFromFile <- function(filename, header = T) { | 251 getDataFrameFromFile <- function(filename, header = TRUE) { |
242 myDataFrame <- read.table(filename, header = header, sep = ";", stringsAsFactors = F) | 252 myDataFrame <- read.table(filename, header = header, sep = ";", stringsAsFactors = FALSE) |
243 if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header = header, sep = "\t", stringsAsFactors = F) | 253 if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header = header, sep = "\t", stringsAsFactors = FALSE) |
244 if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header = header, sep = ",", stringsAsFactors = F) | 254 if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header = header, sep = ",", stringsAsFactors = FALSE) |
245 if (ncol(myDataFrame) < 2) { | 255 if (ncol(myDataFrame) < 2) { |
246 error_message <- "Your tabular file seems not well formatted. The column separators accepted are ; , and tabulation" | 256 error_message <- "Your tabular file seems not well formatted. The column separators accepted are ; , and tabulation" |
247 print(error_message) | 257 print(error_message) |
248 stop(error_message) | 258 stop(error_message) |
249 } | 259 } |
250 return(myDataFrame) | 260 return(myDataFrame) |
251 } | 261 } |
252 | 262 |
253 #@author G. Le Corguille | 263 #@author G. Le Corguille |
254 # Draw the BPI and TIC graphics | 264 # Draw the BPI and TIC graphics |
255 # colored by sample names or class names | 265 # colored by sample names or class names |
256 getPlotChromatogram <- function(chrom, xdata, pdfname = "Chromatogram.pdf", aggregationFun = "max") { | 266 getPlotChromatogram <- function(chrom, xdata, pdfname = "Chromatogram.pdf", aggregationFun = "max") { |
257 | 267 |
258 if (aggregationFun == "sum") | 268 if (aggregationFun == "sum") |
259 type <- "Total Ion Chromatograms" | 269 type <- "Total Ion Chromatograms" |
260 else | 270 else |
261 type <- "Base Peak Intensity Chromatograms" | 271 type <- "Base Peak Intensity Chromatograms" |
262 | 272 |
263 adjusted <- "Raw" | 273 adjusted <- "Raw" |
264 if (hasAdjustedRtime(xdata)) | 274 if (hasAdjustedRtime(xdata)) |
265 adjusted <- "Adjusted" | 275 adjusted <- "Adjusted" |
266 | 276 |
267 main <- paste(type, ":", adjusted, "data") | 277 main <- paste(type, ":", adjusted, "data") |
268 | 278 |
269 pdf(pdfname, width = 16, height = 10) | 279 pdf(pdfname, width = 16, height = 10) |
270 | 280 |
271 # Color by group | 281 # Color by group |
272 if (length(unique(xdata$sample_group)) < 10) { | 282 if (length(unique(xdata$sample_group)) < 10) { |
273 group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") | 283 group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") |
274 }else{ | 284 } else { |
275 group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") | 285 group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") |
276 } | 286 } |
277 if (length(group_colors) > 1) { | 287 if (length(group_colors) > 1) { |
278 names(group_colors) <- unique(xdata$sample_group) | 288 names(group_colors) <- unique(xdata$sample_group) |
279 plot(chrom, col = group_colors[chrom$sample_group], main = main, peakType = "none") | 289 plot(chrom, col = group_colors[chrom$sample_group], main = main, peakType = "none") |
280 legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) | 290 legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) |
281 } | 291 } |
282 | 292 |
283 # Color by sample | 293 # Color by sample |
284 plot(chrom, col = rainbow(length(xdata@phenoData@data$sample_name)), main = main, peakType = "none") | 294 plot(chrom, col = rainbow(length(xdata@phenoData@data$sample_name)), main = main, peakType = "none") |
285 legend("topright", legend = xdata@phenoData@data$sample_name, col = rainbow(length(xdata@phenoData@data$sample_name)), cex = 0.8, lty = 1) | 295 legend("topright", legend = xdata@phenoData@data$sample_name, col = rainbow(length(xdata@phenoData@data$sample_name)), cex = 0.8, lty = 1) |
286 | 296 |
287 dev.off() | 297 dev.off() |
288 } | 298 } |
289 | 299 |
290 | 300 |
291 # Get the polarities from all the samples of a condition | 301 # Get the polarities from all the samples of a condition |
292 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM | 302 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM |
293 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM | 303 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM |
294 getSampleMetadata <- function(xdata = NULL, sampleMetadataOutput = "sampleMetadata.tsv") { | 304 getSampleMetadata <- function(xdata = NULL, sampleMetadataOutput = "sampleMetadata.tsv") { |
295 cat("Creating the sampleMetadata file...\n") | 305 cat("Creating the sampleMetadata file...\n") |
296 | 306 |
297 #Create the sampleMetada dataframe | 307 #Create the sampleMetada dataframe |
298 sampleMetadata <- xdata@phenoData@data | 308 sampleMetadata <- xdata@phenoData@data |
299 rownames(sampleMetadata) <- NULL | 309 rownames(sampleMetadata) <- NULL |
300 colnames(sampleMetadata) <- c("sample_name", "class") | 310 colnames(sampleMetadata) <- c("sample_name", "class") |
301 | 311 |
302 sampleNamesOrigin <- sampleMetadata$sample_name | 312 sampleNamesOrigin <- sampleMetadata$sample_name |
303 sampleNamesMakeNames <- make.names(sampleNamesOrigin) | 313 sampleNamesMakeNames <- make.names(sampleNamesOrigin) |
304 | 314 |
305 if (any(duplicated(sampleNamesMakeNames))) { | 315 if (any(duplicated(sampleNamesMakeNames))) { |
306 write("\n\nERROR: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names().\nIn your case, at least two columns after the renaming obtain the same name, thus XCMS will collapse those columns per name.", stderr()) | 316 write("\n\nERROR: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names().\nIn your case, at least two columns after the renaming obtain the same name, thus XCMS will collapse those columns per name.", stderr()) |
307 for (sampleName in sampleNamesOrigin) { | 317 for (sampleName in sampleNamesOrigin) { |
308 write(paste(sampleName, "\t->\t", make.names(sampleName)), stderr()) | 318 write(paste(sampleName, "\t->\t", make.names(sampleName)), stderr()) |
309 } | 319 } |
310 stop("\n\nERROR: One or more of your files will not be import by xcmsSet. It may due to bad characters in their filenames.") | 320 stop("\n\nERROR: One or more of your files will not be import by xcmsSet. It may due to bad characters in their filenames.") |
311 } | 321 } |
312 | 322 |
313 if (!all(sampleNamesOrigin == sampleNamesMakeNames)) { | 323 if (!all(sampleNamesOrigin == sampleNamesMakeNames)) { |
314 cat("\n\nWARNING: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names()\nIn your case, one or more sample names will be renamed in the sampleMetadata and dataMatrix files:\n") | 324 cat("\n\nWARNING: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names()\nIn your case, one or more sample names will be renamed in the sampleMetadata and dataMatrix files:\n") |
315 for (sampleName in sampleNamesOrigin) { | 325 for (sampleName in sampleNamesOrigin) { |
316 cat(paste(sampleName, "\t->\t", make.names(sampleName), "\n")) | 326 cat(paste(sampleName, "\t->\t", make.names(sampleName), "\n")) |
317 } | 327 } |
318 } | 328 } |
319 | 329 |
320 sampleMetadata$sample_name <- sampleNamesMakeNames | 330 sampleMetadata$sample_name <- sampleNamesMakeNames |
321 | 331 |
322 | 332 |
323 #For each sample file, the following actions are done | 333 #For each sample file, the following actions are done |
324 for (fileIdx in seq_len(length(fileNames(xdata)))) { | 334 for (fileIdx in seq_len(length(fileNames(xdata)))) { |
325 #Check if the file is in the CDF format | 335 #Check if the file is in the CDF format |
326 if (!mzR:::netCDFIsFile(fileNames(xdata))) { | 336 if (!mzR:::netCDFIsFile(fileNames(xdata))) { |
327 | 337 |
328 # If the column isn't exist, with add one filled with NA | 338 # If the column isn't exist, with add one filled with NA |
329 if (is.null(sampleMetadata$polarity)) sampleMetadata$polarity <- NA | 339 if (is.null(sampleMetadata$polarity)) sampleMetadata$polarity <- NA |
330 | 340 |
331 #Extract the polarity (a list of polarities) | 341 #Extract the polarity (a list of polarities) |
332 polarity <- fData(xdata)[fData(xdata)$fileIdx == fileIdx, "polarity"] | 342 polarity <- fData(xdata)[fData(xdata)$fileIdx == fileIdx, "polarity"] |
333 #Verify if all the scans have the same polarity | 343 #Verify if all the scans have the same polarity |
334 uniq_list <- unique(polarity) | 344 uniq_list <- unique(polarity) |
335 if (length(uniq_list) > 1) { | 345 if (length(uniq_list) > 1) { |
336 polarity <- "mixed" | 346 polarity <- "mixed" |
337 } else { | 347 } else { |
338 polarity <- as.character(uniq_list) | 348 polarity <- as.character(uniq_list) |
339 } | 349 } |
340 | 350 |
341 #Set the polarity attribute | 351 #Set the polarity attribute |
342 sampleMetadata$polarity[fileIdx] <- polarity | 352 sampleMetadata$polarity[fileIdx] <- polarity |
343 } | 353 } |
344 | 354 |
345 } | 355 } |
346 | 356 |
347 write.table(sampleMetadata, sep = "\t", quote = FALSE, row.names = FALSE, file = sampleMetadataOutput) | 357 write.table(sampleMetadata, sep = "\t", quote = FALSE, row.names = FALSE, file = sampleMetadataOutput) |
348 | 358 |
349 return(list("sampleNamesOrigin" = sampleNamesOrigin, "sampleNamesMakeNames" = sampleNamesMakeNames)) | 359 return(list("sampleNamesOrigin" = sampleNamesOrigin, "sampleNamesMakeNames" = sampleNamesMakeNames)) |
350 | 360 |
351 } | 361 } |
352 | 362 |
353 | 363 |
354 # This function will compute MD5 checksum to check the data integrity | 364 # This function will compute MD5 checksum to check the data integrity |
355 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr | 365 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr |
356 getMd5sum <- function(files) { | 366 getMd5sum <- function(files) { |
357 cat("Compute md5 checksum...\n") | 367 cat("Compute md5 checksum...\n") |
358 library(tools) | 368 library(tools) |
359 return(as.matrix(md5sum(files))) | 369 return(as.matrix(md5sum(files))) |
360 } | 370 } |
361 | 371 |
362 # This function retrieve the raw file in the working directory | 372 # This function retrieve the raw file in the working directory |
363 # - if zipfile: unzip the file with its directory tree | 373 # - if zipfile: unzip the file with its directory tree |
364 # - if singlefiles: set symlink with the good filename | 374 # - if singlefiles: set symlink with the good filename |
365 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr | 375 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr |
366 retrieveRawfileInTheWorkingDir <- function(singlefile, zipfile, args, prefix = "") { | 376 retrieveRawfileInTheWorkingDir <- function(singlefile, zipfile, args, prefix = "") { |
367 | 377 |
368 if (!(prefix %in% c("", "Positive", "Negative", "MS1", "MS2"))) stop("prefix must be either '', 'Positive', 'Negative', 'MS1' or 'MS2'") | 378 if (!(prefix %in% c("", "Positive", "Negative", "MS1", "MS2"))) stop("prefix must be either '', 'Positive', 'Negative', 'MS1' or 'MS2'") |
369 | 379 |
370 # single - if the file are passed in the command arguments -> refresh singlefile | 380 # single - if the file are passed in the command arguments -> refresh singlefile |
371 if (!is.null(args[[paste0("singlefile_galaxyPath", prefix)]])) { | 381 if (!is.null(args[[paste0("singlefile_galaxyPath", prefix)]])) { |
372 singlefile_galaxyPaths <- unlist(strsplit(args[[paste0("singlefile_galaxyPath", prefix)]], "\\|")) | 382 singlefile_galaxyPaths <- unlist(strsplit(args[[paste0("singlefile_galaxyPath", prefix)]], "\\|")) |
373 singlefile_sampleNames <- unlist(strsplit(args[[paste0("singlefile_sampleName", prefix)]], "\\|")) | 383 singlefile_sampleNames <- unlist(strsplit(args[[paste0("singlefile_sampleName", prefix)]], "\\|")) |
374 | 384 |
375 singlefile <- NULL | 385 singlefile <- NULL |
376 for (singlefile_galaxyPath_i in seq_len(length(singlefile_galaxyPaths))) { | 386 for (singlefile_galaxyPath_i in seq_len(length(singlefile_galaxyPaths))) { |
377 singlefile_galaxyPath <- singlefile_galaxyPaths[singlefile_galaxyPath_i] | 387 singlefile_galaxyPath <- singlefile_galaxyPaths[singlefile_galaxyPath_i] |
378 singlefile_sampleName <- singlefile_sampleNames[singlefile_galaxyPath_i] | 388 singlefile_sampleName <- singlefile_sampleNames[singlefile_galaxyPath_i] |
379 # In case, an url is used to import data within Galaxy | 389 # In case, an url is used to import data within Galaxy |
380 singlefile_sampleName <- tail(unlist(strsplit(singlefile_sampleName, "/")), n = 1) | 390 singlefile_sampleName <- tail(unlist(strsplit(singlefile_sampleName, "/")), n = 1) |
381 singlefile[[singlefile_sampleName]] <- singlefile_galaxyPath | 391 singlefile[[singlefile_sampleName]] <- singlefile_galaxyPath |
392 } | |
393 } | |
394 # zipfile - if the file are passed in the command arguments -> refresh zipfile | |
395 if (!is.null(args[[paste0("zipfile", prefix)]])) | |
396 zipfile <- args[[paste0("zipfile", prefix)]] | |
397 | |
398 # single | |
399 if (!is.null(singlefile) && (length("singlefile") > 0)) { | |
400 files <- vector() | |
401 for (singlefile_sampleName in names(singlefile)) { | |
402 singlefile_galaxyPath <- singlefile[[singlefile_sampleName]] | |
403 if (!file.exists(singlefile_galaxyPath)) { | |
404 error_message <- paste("Cannot access the sample:", singlefile_sampleName, "located:", singlefile_galaxyPath, ". Please, contact your administrator ... if you have one!") | |
405 print(error_message) | |
406 stop(error_message) | |
382 } | 407 } |
383 } | 408 |
384 # zipfile - if the file are passed in the command arguments -> refresh zipfile | 409 if (!suppressWarnings(try(file.link(singlefile_galaxyPath, singlefile_sampleName), silent = TRUE))) |
385 if (!is.null(args[[paste0("zipfile", prefix)]])) | 410 file.copy(singlefile_galaxyPath, singlefile_sampleName) |
386 zipfile <- args[[paste0("zipfile", prefix)]] | 411 files <- c(files, singlefile_sampleName) |
387 | 412 } |
388 # single | 413 } |
389 if (!is.null(singlefile) && (length("singlefile") > 0)) { | 414 # zipfile |
390 files <- vector() | 415 if (!is.null(zipfile) && (zipfile != "")) { |
391 for (singlefile_sampleName in names(singlefile)) { | 416 if (!file.exists(zipfile)) { |
392 singlefile_galaxyPath <- singlefile[[singlefile_sampleName]] | 417 error_message <- paste("Cannot access the Zip file:", zipfile, ". Please, contact your administrator ... if you have one!") |
393 if (!file.exists(singlefile_galaxyPath)) { | 418 print(error_message) |
394 error_message <- paste("Cannot access the sample:", singlefile_sampleName, "located:", singlefile_galaxyPath, ". Please, contact your administrator ... if you have one!") | 419 stop(error_message) |
395 print(error_message); stop(error_message) | 420 } |
396 } | 421 suppressWarnings(unzip(zipfile, unzip = "unzip")) |
397 | 422 |
398 if (!suppressWarnings(try(file.link(singlefile_galaxyPath, singlefile_sampleName), silent = T))) | 423 #get the directory name |
399 file.copy(singlefile_galaxyPath, singlefile_sampleName) | 424 suppressWarnings(filesInZip <- unzip(zipfile, list = TRUE)) |
400 files <- c(files, singlefile_sampleName) | 425 directories <- unique(unlist(lapply(strsplit(filesInZip$Name, "/"), function(x) x[1]))) |
401 } | 426 directories <- directories[!(directories %in% c("__MACOSX")) & file.info(directories)$isdir] |
402 } | 427 directory <- "." |
403 # zipfile | 428 if (length(directories) == 1) directory <- directories |
404 if (!is.null(zipfile) && (zipfile != "")) { | 429 |
405 if (!file.exists(zipfile)) { | 430 cat("files_root_directory\t", directory, "\n") |
406 error_message <- paste("Cannot access the Zip file:", zipfile, ". Please, contact your administrator ... if you have one!") | 431 |
407 print(error_message) | 432 filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", "[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]") |
408 stop(error_message) | 433 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|") |
409 } | 434 info <- file.info(directory) |
410 suppressWarnings(unzip(zipfile, unzip = "unzip")) | 435 listed <- list.files(directory[info$isdir], pattern = filepattern, recursive = TRUE, full.names = TRUE) |
411 | 436 files <- c(directory[!info$isdir], listed) |
412 #get the directory name | 437 exists <- file.exists(files) |
413 suppressWarnings(filesInZip <- unzip(zipfile, list = T)) | 438 files <- files[exists] |
414 directories <- unique(unlist(lapply(strsplit(filesInZip$Name, "/"), function(x) x[1]))) | 439 |
415 directories <- directories[!(directories %in% c("__MACOSX")) & file.info(directories)$isdir] | 440 } |
416 directory <- "." | 441 return(list(zipfile = zipfile, singlefile = singlefile, files = files)) |
417 if (length(directories) == 1) directory <- directories | |
418 | |
419 cat("files_root_directory\t", directory, "\n") | |
420 | |
421 filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", "[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]") | |
422 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|") | |
423 info <- file.info(directory) | |
424 listed <- list.files(directory[info$isdir], pattern = filepattern, recursive = TRUE, full.names = TRUE) | |
425 files <- c(directory[!info$isdir], listed) | |
426 exists <- file.exists(files) | |
427 files <- files[exists] | |
428 | |
429 } | |
430 return(list(zipfile = zipfile, singlefile = singlefile, files = files)) | |
431 | |
432 } | 442 } |
433 | 443 |
434 | 444 |
435 # This function retrieve a xset like object | 445 # This function retrieve a xset like object |
436 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr | 446 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr |
437 getxcmsSetObject <- function(xobject) { | 447 getxcmsSetObject <- function(xobject) { |
438 # XCMS 1.x | 448 # XCMS 1.x |
439 if (class(xobject) == "xcmsSet") | 449 if (class(xobject) == "xcmsSet") |
440 return(xobject) | 450 return(xobject) |
441 # XCMS 3.x | 451 # XCMS 3.x |
442 if (class(xobject) == "XCMSnExp") { | 452 if (class(xobject) == "XCMSnExp") { |
443 # Get the legacy xcmsSet object | 453 # Get the legacy xcmsSet object |
444 suppressWarnings(xset <- as(xobject, "xcmsSet")) | 454 suppressWarnings(xset <- as(xobject, "xcmsSet")) |
445 if (!is.null(xset@phenoData$sample_group)) | 455 if (!is.null(xset@phenoData$sample_group)) |
446 sampclass(xset) <- xset@phenoData$sample_group | 456 sampclass(xset) <- xset@phenoData$sample_group |
447 else | 457 else |
448 sampclass(xset) <- "." | 458 sampclass(xset) <- "." |
449 return(xset) | 459 return(xset) |
450 } | 460 } |
451 } | 461 } |