Mercurial > repos > vandelj > giant_aptsummarize
comparison src/VolcanoPlotsScript.R @ 0:708f43bda2b6 draft
"planemo upload for repository https://github.com/juliechevalier/GIANT/tree/master commit cb276a594444c8f32e9819fefde3a21f121d35df"
author | vandelj |
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date | Fri, 26 Jun 2020 09:35:11 -0400 |
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-1:000000000000 | 0:708f43bda2b6 |
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1 # R script to plot volcanos through Galaxy based GIANT tool | |
2 # written by Jimmy Vandel | |
3 # | |
4 # | |
5 initial.options <- commandArgs(trailingOnly = FALSE) | |
6 file.arg.name <- "--file=" | |
7 script.name <- sub(file.arg.name, "", initial.options[grep(file.arg.name, initial.options)]) | |
8 script.basename <- dirname(script.name) | |
9 source(file.path(script.basename, "utils.R")) | |
10 source(file.path(script.basename, "getopt.R")) | |
11 | |
12 #addComment("Welcome R!") | |
13 | |
14 # setup R error handling to go to stderr | |
15 options( show.error.messages=F, error = function () { cat(geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) | |
16 | |
17 # we need that to not crash galaxy with an UTF8 error on German LC settings. | |
18 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8") | |
19 loc <- Sys.setlocale("LC_NUMERIC", "C") | |
20 | |
21 #get starting time | |
22 start.time <- Sys.time() | |
23 | |
24 options(stringAsfactors = FALSE, useFancyQuotes = FALSE) | |
25 args <- commandArgs() | |
26 | |
27 # get options, using the spec as defined by the enclosed list. | |
28 # we read the options from the default: commandArgs(TRUE). | |
29 spec <- matrix(c( | |
30 "statisticsFile", "i", 1, "character", | |
31 "volcanoName" , "n", 1, "character", | |
32 "pvalColumnName" , "p", 1, "character", | |
33 "fdrColumnName" , "m", 1, "character", | |
34 "fcColumnName" , "c", 1, "character", | |
35 "fcKind","d", 1, "character", | |
36 "fdrThreshold","s", 1, "double", | |
37 "fcThreshold","e", 1, "double", | |
38 "organismID","x",1,"character", | |
39 "rowNameType","y",1,"character", | |
40 "log", "l", 1, "character", | |
41 "outputFile" , "o", 1, "character", | |
42 "format", "f", 1, "character", | |
43 "quiet", "q", 0, "logical"), | |
44 byrow=TRUE, ncol=4) | |
45 opt <- getopt(spec) | |
46 | |
47 # enforce the following required arguments | |
48 if (is.null(opt$log)) { | |
49 addComment("[ERROR]'log file' is required\n") | |
50 q( "no", 1, F ) | |
51 } | |
52 addComment("[INFO]Start of R script",T,opt$log,display=FALSE) | |
53 if (is.null(opt$statisticsFile)) { | |
54 addComment("[ERROR]'statisticsFile' is required",T,opt$log) | |
55 q( "no", 1, F ) | |
56 } | |
57 if (length(opt$pvalColumnName)==0 || length(opt$fdrColumnName)==0 || length(opt$fcColumnName)==0) { | |
58 addComment("[ERROR]no selected columns",T,opt$log) | |
59 q( "no", 1, F ) | |
60 } | |
61 if (length(opt$pvalColumnName)!=length(opt$fcColumnName) || length(opt$pvalColumnName)!=length(opt$fdrColumnName)) { | |
62 addComment("[ERROR]different number of selected columns between p.val, adj-p.val and FC ",T,opt$log) | |
63 q( "no", 1, F ) | |
64 } | |
65 if (is.null(opt$fcKind)) { | |
66 addComment("[ERROR]'fcKind' is required",T,opt$log) | |
67 q( "no", 1, F ) | |
68 } | |
69 if (is.null(opt$fdrThreshold)) { | |
70 addComment("[ERROR]'FDR threshold' is required",T,opt$log) | |
71 q( "no", 1, F ) | |
72 } | |
73 if (is.null(opt$fcThreshold)) { | |
74 addComment("[ERROR]'FC threshold' is required",T,opt$log) | |
75 q( "no", 1, F ) | |
76 } | |
77 if (is.null(opt$outputFile)) { | |
78 addComment("[ERROR]'output file' is required",T,opt$log) | |
79 q( "no", 1, F ) | |
80 } | |
81 if (is.null(opt$format)) { | |
82 addComment("[ERROR]'output format' is required",T,opt$log) | |
83 q( "no", 1, F ) | |
84 } | |
85 | |
86 #demande si le script sera bavard | |
87 verbose <- if (is.null(opt$quiet)) { | |
88 TRUE | |
89 }else{ | |
90 FALSE | |
91 } | |
92 | |
93 #paramètres internes | |
94 addComment("[INFO]Parameters checked test mode !",T,opt$log,display=FALSE) | |
95 | |
96 addComment(c("[INFO]Working directory: ",getwd()),TRUE,opt$log,display=FALSE) | |
97 addComment(c("[INFO]Command line: ",args),TRUE,opt$log,display=FALSE) | |
98 | |
99 #directory for plots | |
100 dir.create(file.path(getwd(), "plotDir")) | |
101 dir.create(file.path(getwd(), "plotLyDir")) | |
102 | |
103 #charge des packages silencieusement | |
104 suppressPackageStartupMessages({ | |
105 library("methods") | |
106 library("biomaRt") | |
107 library("ggplot2") | |
108 library("plotly") | |
109 library("stringr") | |
110 }) | |
111 | |
112 #define some usefull variable | |
113 nbVolcanosToPlot=length(opt$pvalColumnName) | |
114 | |
115 #load input file | |
116 statDataMatrix=read.csv(file=file.path(getwd(), opt$statisticsFile),header=F,sep="\t",colClasses="character") | |
117 #remove first colum to convert it as rownames | |
118 rownames(statDataMatrix)=statDataMatrix[,1] | |
119 statDataMatrix=statDataMatrix[,-1] | |
120 | |
121 #identify lines without adjusted p-value info (should contain the same content as rownames) and replace them with NA values | |
122 FDRinfo=rep(TRUE,nbVolcanosToPlot) | |
123 for(iVolcano in 1:nbVolcanosToPlot){ | |
124 #input parameter should be None when adjusted p-val are not available | |
125 if(opt$fdrColumnName[iVolcano]=="None"){ | |
126 #content of the corresponding column should also be the same as rownames | |
127 if(!all(statDataMatrix[,(iVolcano-1)*3+2]==rownames(statDataMatrix))){ | |
128 addComment(c("[ERROR]It seems that input stat matrix contains adjusted p-values for volcano",iVolcano,"whereas input parameter indicates that not."),T,opt$log) | |
129 q( "no", 1, F ) | |
130 } | |
131 FDRinfo[iVolcano]=FALSE | |
132 statDataMatrix[,(iVolcano-1)*3+2]=NA | |
133 } | |
134 } | |
135 | |
136 if(is.data.frame(statDataMatrix)){ | |
137 statDataMatrix=data.matrix(statDataMatrix) | |
138 }else{ | |
139 statDataMatrix=data.matrix(as.numeric(statDataMatrix)) | |
140 } | |
141 | |
142 #check if available column number match with volcano requested number | |
143 if(ncol(statDataMatrix)!=3*nbVolcanosToPlot){ | |
144 addComment("[ERROR]Input file column number is different from requested volcano number",T,opt$log) | |
145 q( "no", 1, F ) | |
146 } | |
147 | |
148 #build global dataFrame with data and fill with p.val and log2(FC) and FDR | |
149 dataFrame=data.frame(row.names = rownames(statDataMatrix)) | |
150 #start with p-value | |
151 dataFrame$p.value=statDataMatrix[,seq(1,nbVolcanosToPlot*3,3),drop=FALSE] | |
152 #compute FDR if needed or just get available info | |
153 dataFrame$adj_p.value=dataFrame$p.value | |
154 for(iVolcano in 1:nbVolcanosToPlot){ | |
155 #adjusted p-value are already computed | |
156 if(FDRinfo[iVolcano]){ | |
157 dataFrame$adj_p.value[,iVolcano]=statDataMatrix[,(iVolcano-1)*3+2,drop=FALSE] | |
158 }else{ | |
159 #adjusted p-value should be computed based on p-val using FDR | |
160 dataFrame$adj_p.value[,iVolcano]=p.adjust(dataFrame$p.value[,iVolcano,drop=FALSE],"fdr") | |
161 addComment(c("[INFO]Adjusted p-values are not available in input for volcano",iVolcano,", FDR approach will be used on available raw p-values"),T,opt$log) | |
162 } | |
163 } | |
164 if(opt$fcKind=="FC"){ | |
165 #we should transform as Log2FC | |
166 dataFrame$coefficients=log2(statDataMatrix[,seq(3,nbVolcanosToPlot*3,3),drop=FALSE]) | |
167 addComment(c("[INFO]FC are converted in log2(FC) for plotting"),T,opt$log) | |
168 }else{ | |
169 dataFrame$coefficients=statDataMatrix[,seq(3,nbVolcanosToPlot*3,3),drop=FALSE] | |
170 } | |
171 | |
172 addComment(c("[INFO]Input data available for",nbVolcanosToPlot,"volcano(s) with",nrow(statDataMatrix),"rows"),T,opt$log) | |
173 | |
174 | |
175 #plot VOLCANOs | |
176 volcanoPerPage=1 | |
177 logFCthreshold=log2(opt$fcThreshold) | |
178 iToPlot=1 | |
179 plotVector=list() | |
180 volcanoNameList=c() | |
181 for (iVolcano in 1:nbVolcanosToPlot){ | |
182 | |
183 if(nchar(opt$volcanoName[iVolcano])>0){ | |
184 curentVolcanoName=opt$volcanoName[iVolcano] | |
185 }else{ | |
186 curentVolcanoName=paste(iVolcano,opt$pvalColumnName[iVolcano],sep="_") | |
187 } | |
188 | |
189 #keep only rows without NA for p-val, adjusted p-val and coeff | |
190 pValToPlot=dataFrame$p.value[,iVolcano] | |
191 fdrToPlot=dataFrame$adj_p.value[,iVolcano] | |
192 coeffToPlot=dataFrame$coefficients[,iVolcano] | |
193 | |
194 rowToRemove=unique(c(which(is.na(pValToPlot)),which(is.na(fdrToPlot)),which(is.na(coeffToPlot)))) | |
195 if(length(rowToRemove)>0){ | |
196 pValToPlot=pValToPlot[-rowToRemove] | |
197 fdrToPlot=fdrToPlot[-rowToRemove] | |
198 coeffToPlot=coeffToPlot[-rowToRemove] | |
199 } | |
200 addComment(c("[INFO]For",curentVolcanoName,"volcano,",length(rowToRemove),"rows are discarded due to NA values,",length(pValToPlot),"remaining rows."),T,opt$log) | |
201 | |
202 #save volcano name | |
203 volcanoNameList=c(volcanoNameList,curentVolcanoName) | |
204 | |
205 #remove characters possibly troubling | |
206 volcanoFileName=iVolcano | |
207 | |
208 #define the log10(p-val) threshold corresponding to FDR threshold fixed by user | |
209 probeWithLowFDR=-log10(pValToPlot[which(fdrToPlot<=opt$fdrThreshold)]) | |
210 pvalThresholdFDR=NULL | |
211 if(length(probeWithLowFDR)>0)pvalThresholdFDR=min(probeWithLowFDR) | |
212 | |
213 #get significant points over FC and FDR thresholds | |
214 significativePoints=intersect(which(abs(coeffToPlot)>=logFCthreshold),which(fdrToPlot<=opt$fdrThreshold)) | |
215 | |
216 #to reduce size of html plot, we keep 20000 points maximum sampled amongst genes with pval>=33%(pval) and abs(log2(FC))<=66%(abs(log2(FC))) | |
217 htmlPointsToRemove=intersect(which(abs(coeffToPlot)<=quantile(abs(coeffToPlot),c(0.66))),which(pValToPlot>=quantile(abs(pValToPlot),c(0.33)))) | |
218 if(length(htmlPointsToRemove)>20000){ | |
219 htmlPointsToRemove=setdiff(htmlPointsToRemove,sample(htmlPointsToRemove,20000)) | |
220 }else{ | |
221 htmlPointsToRemove=c() | |
222 } | |
223 | |
224 xMinLimPlot=min(coeffToPlot)-0.2 | |
225 xMaxLimPlot=max(coeffToPlot)+0.2 | |
226 yMaxLimPlot= max(-log10(pValToPlot))+0.2 | |
227 | |
228 if(length(significativePoints)>0){ | |
229 dataSignifToPlot=data.frame(pval=-log10(pValToPlot[significativePoints]),FC=coeffToPlot[significativePoints],description=paste(names(coeffToPlot[significativePoints]),"\n","FC: " , round(2^coeffToPlot[significativePoints],2) , " | Adjusted p-val: ",prettyNum(fdrToPlot[significativePoints],digits=4), sep="")) | |
230 #to test if remains any normal points to draw | |
231 if(length(significativePoints)<length(pValToPlot)){ | |
232 dataToPlot=data.frame(pval=-log10(pValToPlot[-significativePoints]),FC=coeffToPlot[-significativePoints],description=paste("FC: " , round(2^coeffToPlot[-significativePoints],2) , " | Adjusted p-val: ",prettyNum(fdrToPlot[-significativePoints],digits=4), sep="")) | |
233 }else{ | |
234 dataToPlot=data.frame(pval=0,FC=0,description="null") | |
235 } | |
236 }else{ | |
237 dataToPlot=data.frame(pval=-log10(pValToPlot),FC=coeffToPlot,description=paste("FC: " , round(2^coeffToPlot,2) , " | Adjusted p-val: ",prettyNum(fdrToPlot,digits=4), sep="")) | |
238 } | |
239 | |
240 ##traditional plot | |
241 | |
242 p <- ggplot(data=dataToPlot, aes(x=FC, y=pval)) + geom_point() + | |
243 theme_bw() + ggtitle(curentVolcanoName) + ylab(label="-Log10(p-val)") + xlab(label="Log2 Fold Change") + | |
244 theme(panel.border=element_blank(),plot.title = element_text(hjust = 0.5),legend.position="none") | |
245 if(logFCthreshold!=0) p <- p + geom_vline(xintercept=-logFCthreshold, color="salmon",linetype="dotted", size=1) + geom_vline(xintercept=logFCthreshold, color="salmon",linetype="dotted", size=1) + geom_text(data.frame(text=c(paste(c("log2(1/FC=",opt$fcThreshold,")"),collapse=""),paste(c("log2(FC=",opt$fcThreshold,")"),collapse="")),x=c(-logFCthreshold,logFCthreshold),y=c(0,0)),mapping=aes(x=x, y=y, label=text), size=4, angle=90, vjust=-0.4, hjust=0, color="salmon") | |
246 if(!is.null(pvalThresholdFDR)) p <- p + geom_hline(yintercept=pvalThresholdFDR, color="skyblue1",linetype="dotted", size=0.5) + geom_text(data.frame(text=c(paste(c("Adjusted pval limit(",opt$fdrThreshold,")"),collapse="")),x=c(xMinLimPlot),y=c(pvalThresholdFDR)),mapping=aes(x=x, y=y, label=text), size=4, vjust=0, hjust=0, color="skyblue3") | |
247 if(length(significativePoints)>0)p <- p + geom_point(data=dataSignifToPlot,aes(colour=description)) | |
248 | |
249 ##interactive plot | |
250 | |
251 if(length(htmlPointsToRemove)>0){ | |
252 pointToRemove=union(htmlPointsToRemove,significativePoints) | |
253 #to test if it remains any normal points to draw | |
254 if(length(pointToRemove)<length(pValToPlot)){ | |
255 dataToPlot=data.frame(pval=-log10(pValToPlot[-pointToRemove]),FC=coeffToPlot[-pointToRemove],description=paste("FC: " , round(2^coeffToPlot[-pointToRemove],2) , " | Adjusted p-val: ", prettyNum(fdrToPlot[-pointToRemove],digits=4), sep="")) | |
256 }else{ | |
257 dataToPlot=data.frame(pval=0,FC=0,description="null") | |
258 } | |
259 } | |
260 | |
261 if((nrow(dataToPlot)+length(significativePoints))>40000)addComment(c("[WARNING]For",curentVolcanoName,"volcano, numerous points to plot(",nrow(dataToPlot)+nrow(dataSignifToPlot),"), resulting volcano could be heavy, using more stringent thresholds could be helpful."),T,opt$log) | |
262 | |
263 phtml <- plot_ly(data=dataToPlot, x=~FC, y=~pval,type="scatter", mode="markers",showlegend = FALSE, marker = list(color="gray",opacity=0.5), text=~description, hoverinfo="text") %>% | |
264 layout(title = curentVolcanoName[iVolcano],xaxis=list(title="Log2 Fold Change",showgrid=TRUE, zeroline=FALSE),yaxis=list(title="-Log10(p-val)", showgrid=TRUE, zeroline=FALSE)) | |
265 if(length(significativePoints)>0) phtml=add_markers(phtml,data=dataSignifToPlot, x=~FC, y=~pval, mode="markers" , marker=list( color=log10(abs(dataSignifToPlot$FC)*dataSignifToPlot$pval),colorscale='Rainbow'), text=~description, hoverinfo="text", inherit = FALSE) %>% hide_colorbar() | |
266 if(logFCthreshold!=0){ | |
267 phtml=add_trace(phtml,x=c(-logFCthreshold,-logFCthreshold), y=c(0,yMaxLimPlot), type="scatter", mode = "lines", line=list(color="coral",dash="dash"), hoverinfo='none', showlegend = FALSE,inherit = FALSE) | |
268 phtml=add_annotations(phtml,x=-logFCthreshold,y=0,xref = "x",yref = "y",text = paste(c("log2(1/FC=",opt$fcThreshold,")"),collapse=""),xanchor = 'right',showarrow = F,textangle=270,font=list(color="coral")) | |
269 phtml=add_trace(phtml,x=c(logFCthreshold,logFCthreshold), y=c(0, yMaxLimPlot), type="scatter", mode = "lines", line=list(color="coral",dash="dash"), hoverinfo='none', showlegend = FALSE,inherit = FALSE) | |
270 phtml=add_annotations(phtml,x=logFCthreshold,y=0,xref = "x",yref = "y",text = paste(c("log2(FC=",opt$fcThreshold,")"),collapse=""),xanchor = 'right',showarrow = F,textangle=270,font=list(color="coral")) | |
271 } | |
272 if(!is.null(pvalThresholdFDR)){ | |
273 phtml=add_trace(phtml,x=c(xMinLimPlot,xMaxLimPlot), y=c(pvalThresholdFDR,pvalThresholdFDR), type="scatter", mode = "lines", line=list(color="cornflowerblue",dash="dash"), hoverinfo='none', showlegend = FALSE,inherit = FALSE) | |
274 phtml=add_annotations(phtml,x=xMinLimPlot,y=pvalThresholdFDR+0.1,xref = "x",yref = "y",text = paste(c("Adjusted pval limit(",opt$fdrThreshold,")"),collapse=""),xanchor = 'left',showarrow = F,font=list(color="cornflowerblue")) | |
275 } | |
276 plotVector[[length(plotVector)+1]]=p | |
277 | |
278 #save plotly files | |
279 pp <- ggplotly(phtml) | |
280 htmlwidgets::saveWidget(as_widget(pp), paste(c(file.path(getwd(), "plotLyDir"),"/Volcanos_",volcanoFileName,".html"),collapse=""),selfcontained = F) | |
281 | |
282 | |
283 if(iVolcano==nbVolcanosToPlot || length(plotVector)==volcanoPerPage){ | |
284 #plot and close the actual plot | |
285 if(opt$format=="pdf"){ | |
286 pdf(paste(c("./plotDir/Volcanos_",volcanoFileName,".pdf"),collapse=""))}else{ | |
287 png(paste(c("./plotDir/Volcanos_",volcanoFileName,".png"),collapse="")) | |
288 } | |
289 multiplot(plotlist=plotVector,cols=1) | |
290 dev.off() | |
291 if(iVolcano<nbVolcanosToPlot){ | |
292 #prepare for a new ploting file if necessary | |
293 plotVector=list() | |
294 iToPlot=iToPlot+1 | |
295 } | |
296 } | |
297 } | |
298 remove(dataToPlot,dataSignifToPlot) | |
299 addComment("[INFO]Volcanos drawn",T,opt$log,T,display=FALSE) | |
300 | |
301 | |
302 #now add anotation infos about genes | |
303 | |
304 rowItemInfo=NULL | |
305 if(!is.null(opt$rowNameType) && !is.null(opt$organismID)){ | |
306 ##get gene information from BioMart | |
307 #if(!require("biomaRt")){ | |
308 # source("https://bioconductor.org/biocLite.R") | |
309 # biocLite("biomaRt") | |
310 #} | |
311 | |
312 ensembl_hs_mart <- useMart(biomart="ensembl", dataset=opt$organismID) | |
313 ensembl_df <- getBM(attributes=c(opt$rowNameType,"description"),mart=ensembl_hs_mart) | |
314 rowItemInfo=ensembl_df[which(ensembl_df[,1]!=""),2] | |
315 rowItemInfo=unlist(lapply(rowItemInfo,function(x)substr(unlist(strsplit(x," \\[Source"))[1],1,30))) | |
316 names(rowItemInfo)=ensembl_df[which(ensembl_df[,1]!=""),1] | |
317 } | |
318 | |
319 #filter out genes with higher p-values for all comparisons | |
320 genesToKeep=names(which(apply(dataFrame$adj_p.value,1,function(x)length(which(x<=opt$fdrThreshold))>0))) | |
321 #filter out genes with lower FC for all comparisons | |
322 genesToKeep=intersect(genesToKeep,names(which(apply(dataFrame$coefficients,1,function(x)length(which(abs(x)>=logFCthreshold))>0)))) | |
323 | |
324 if(length(genesToKeep)>0){ | |
325 dataFrameNew=data.frame(row.names=genesToKeep) | |
326 | |
327 dataFrameNew$adj_p.value=matrix(dataFrame$adj_p.value[genesToKeep,,drop=FALSE],ncol=ncol(dataFrame$adj_p.value)) | |
328 rownames(dataFrameNew$adj_p.value)=genesToKeep | |
329 colnames(dataFrameNew$adj_p.value)=colnames(dataFrame$p.value) | |
330 | |
331 dataFrameNew$p.value=matrix(dataFrame$p.value[genesToKeep,,drop=FALSE],ncol=ncol(dataFrame$p.value)) | |
332 rownames(dataFrameNew$p.value)=genesToKeep | |
333 colnames(dataFrameNew$p.value)=colnames(dataFrame$adj_p.value) | |
334 | |
335 dataFrameNew$coefficients=matrix(dataFrame$coefficients[genesToKeep,,drop=FALSE],ncol=ncol(dataFrame$coefficients)) | |
336 rownames(dataFrameNew$coefficients)=genesToKeep | |
337 colnames(dataFrameNew$coefficients)=colnames(dataFrame$adj_p.value) | |
338 | |
339 dataFrame=dataFrameNew | |
340 rm(dataFrameNew) | |
341 }else{ | |
342 addComment("[WARNING]No significative genes",T,opt$log,display=FALSE) | |
343 } | |
344 | |
345 addComment("[INFO]Significant genes filtering done",T,opt$log,T,display=FALSE) | |
346 | |
347 | |
348 #plot VennDiagramm for genes below threshold between comparisons | |
349 #t=apply(dataFrame$adj_p.value[,1:4],2,function(x)names(which(x<=opt$threshold))) | |
350 #get.venn.partitions(t) | |
351 #vennCounts(dataFrame$adj_p.value[,1:4]<=opt$threshold) | |
352 | |
353 #make a simple sort genes based only on the first comparison | |
354 #newOrder=order(dataFrame$adj_p.value[,1]) | |
355 #dataFrame$adj_p.value=dataFrame$adj_p.value[newOrder,] | |
356 | |
357 #alternative sorting strategy based on the mean gene rank over all comparisons | |
358 if(length(genesToKeep)>1){ | |
359 currentRank=rep(0,nrow(dataFrame$adj_p.value)) | |
360 for(iVolcano in 1:ncol(dataFrame$adj_p.value)){ | |
361 currentRank=currentRank+rank(dataFrame$adj_p.value[,iVolcano]) | |
362 } | |
363 currentRank=currentRank/ncol(dataFrame$adj_p.value) | |
364 newOrder=order(currentRank) | |
365 rownames(dataFrame)=rownames(dataFrame)[newOrder] | |
366 | |
367 dataFrame$adj_p.value=matrix(dataFrame$adj_p.value[newOrder,],ncol=ncol(dataFrame$adj_p.value)) | |
368 rownames(dataFrame$adj_p.value)=rownames(dataFrame$p.value)[newOrder] | |
369 colnames(dataFrame$adj_p.value)=colnames(dataFrame$p.value) | |
370 | |
371 dataFrame$p.value=matrix(dataFrame$p.value[newOrder,],ncol=ncol(dataFrame$p.value)) | |
372 rownames(dataFrame$p.value)=rownames(dataFrame$adj_p.value) | |
373 colnames(dataFrame$p.value)=colnames(dataFrame$adj_p.value) | |
374 | |
375 dataFrame$coefficients=matrix(dataFrame$coefficients[newOrder,],ncol=ncol(dataFrame$coefficients)) | |
376 rownames(dataFrame$coefficients)=rownames(dataFrame$adj_p.value) | |
377 colnames(dataFrame$coefficients)=colnames(dataFrame$adj_p.value) | |
378 } | |
379 | |
380 #formating output matrix depending on genes to keep | |
381 if(length(genesToKeep)==0){ | |
382 outputData=matrix(0,ncol=ncol(dataFrame$adj_p.value)*4+2,nrow=3) | |
383 outputData[1,]=c("X","X",rep(volcanoNameList,each=4)) | |
384 outputData[2,]=c("X","X",rep(c("p-val","Adjusted.p-val","FC","log2(FC)"),ncol(dataFrame$adj_p.value))) | |
385 outputData[,1]=c("Volcano","Gene","noGene") | |
386 outputData[,2]=c("Comparison","Info","noInfo") | |
387 }else{ | |
388 if(length(genesToKeep)==1){ | |
389 outputData=matrix(0,ncol=ncol(dataFrame$adj_p.value)*4+2,nrow=3) | |
390 outputData[1,]=c("X","X",rep(volcanoNameList,each=4)) | |
391 outputData[2,]=c("X","X",rep(c("p-val","Adjusted.p-val","FC","log2(FC)"),ncol(dataFrame$adj_p.value))) | |
392 outputData[,1]=c("Volcano","Gene",genesToKeep) | |
393 outputData[,2]=c("Comparison","Info","na") | |
394 if(!is.null(rowItemInfo))outputData[3,2]=rowItemInfo[genesToKeep] | |
395 outputData[3,seq(3,ncol(outputData),4)]=prettyNum(dataFrame$p.value,digits=4) | |
396 outputData[3,seq(4,ncol(outputData),4)]=prettyNum(dataFrame$adj_p.value,digits=4) | |
397 outputData[3,seq(5,ncol(outputData),4)]=prettyNum(2^dataFrame$coefficients,digits=4) | |
398 outputData[3,seq(6,ncol(outputData),4)]=prettyNum(dataFrame$coefficients,digits=4) | |
399 }else{ | |
400 #format matrix to be correctly read by galaxy (move headers in first column and row) | |
401 outputData=matrix(0,ncol=ncol(dataFrame$adj_p.value)*4+2,nrow=nrow(dataFrame$adj_p.value)+2) | |
402 outputData[1,]=c("X","X",rep(volcanoNameList,each=4)) | |
403 outputData[2,]=c("X","X",rep(c("p-val","Adjusted.p-val","FC","log2(FC)"),ncol(dataFrame$adj_p.value))) | |
404 outputData[,1]=c("Volcano","Gene",rownames(dataFrame$adj_p.value)) | |
405 outputData[,2]=c("Comparison","Info",rep("na",nrow(dataFrame$adj_p.value))) | |
406 if(!is.null(rowItemInfo))outputData[3:nrow(outputData),2]=rowItemInfo[rownames(dataFrame$adj_p.value)] | |
407 outputData[3:nrow(outputData),seq(3,ncol(outputData),4)]=prettyNum(dataFrame$p.value,digits=4) | |
408 outputData[3:nrow(outputData),seq(4,ncol(outputData),4)]=prettyNum(dataFrame$adj_p.value,digits=4) | |
409 outputData[3:nrow(outputData),seq(5,ncol(outputData),4)]=prettyNum(2^dataFrame$coefficients,digits=4) | |
410 outputData[3:nrow(outputData),seq(6,ncol(outputData),4)]=prettyNum(dataFrame$coefficients,digits=4) | |
411 } | |
412 } | |
413 addComment("[INFO]Formated output",T,opt$log,display=FALSE) | |
414 | |
415 #write output results | |
416 write.table(outputData,file=opt$outputFile,quote=FALSE,sep="\t",col.names = F,row.names = F) | |
417 | |
418 | |
419 end.time <- Sys.time() | |
420 addComment(c("[INFO]Total execution time for R script:",as.numeric(end.time - start.time,units="mins"),"mins"),T,opt$log,display=FALSE) | |
421 | |
422 addComment("[INFO]End of R script",T,opt$log,display=FALSE) | |
423 | |
424 printSessionInfo(opt$log) | |
425 | |
426 #sessionInfo() |