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comparison diffexp.R @ 0:7a80e9ec63cb

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- Initial commit
author shian_su <registertonysu@gmail.com>
date Tue, 16 Dec 2014 14:38:15 +1100
parents
children b2fe55fd0651
comparison
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-1:000000000000 0:7a80e9ec63cb
1 # This tool takes in a matrix of feature counts as well as gene annotations and
2 # outputs a table of top expressions as well as various plots for differential
3 # expression analysis
4 #
5 # ARGS: 1.countPath -Path to RData input containing counts
6 # 2.annoPath -Path to RData input containing gene annotations
7 # 3.htmlPath -Path to html file linking to other outputs
8 # 4.outPath -Path to folder to write all output to
9 # 5.rdaOpt -String specifying if RData should be saved
10 # 6.normOpt -String specifying type of normalisation used
11 # 7.weightOpt -String specifying usage of weights
12 # 8.contrastData -String containing contrasts of interest
13 # 9.cpmReq -Float specifying cpm requirement
14 # 10.sampleReq -Integer specifying cpm requirement
15 # 11.pAdjOpt -String specifying the p-value adjustment method
16 # 12.pValReq -Float specifying the p-value requirement
17 # 13.lfcReq -Float specifying the log-fold-change requirement
18 # 14.factorData -String containing factor names and values
19 #
20 # OUT: Voom Plot
21 # BCV Plot
22 # MA Plot
23 # Top Expression Table
24 # HTML file linking to the ouputs
25 #
26 # Author: Shian Su - registertonysu@gmail.com - Jan 2014
27
28 # Record starting time
29 timeStart <- as.character(Sys.time())
30
31 # Load all required libraries
32 library(methods, quietly=TRUE, warn.conflicts=FALSE)
33 library(statmod, quietly=TRUE, warn.conflicts=FALSE)
34 library(splines, quietly=TRUE, warn.conflicts=FALSE)
35 library(edgeR, quietly=TRUE, warn.conflicts=FALSE)
36 library(limma, quietly=TRUE, warn.conflicts=FALSE)
37 library(scales, quietly=TRUE, warn.conflicts=FALSE)
38
39 if (packageVersion("limma") < "3.20.1") {
40 stop("Please update 'limma' to version >= 3.20.1 to run this tool")
41 }
42
43 ################################################################################
44 ### Function Delcaration
45 ################################################################################
46 # Function to sanitise contrast equations so there are no whitespaces
47 # surrounding the arithmetic operators, leading or trailing whitespace
48 sanitiseEquation <- function(equation) {
49 equation <- gsub(" *[+] *", "+", equation)
50 equation <- gsub(" *[-] *", "-", equation)
51 equation <- gsub(" *[/] *", "/", equation)
52 equation <- gsub(" *[*] *", "*", equation)
53 equation <- gsub("^\\s+|\\s+$", "", equation)
54 return(equation)
55 }
56
57 # Function to sanitise group information
58 sanitiseGroups <- function(string) {
59 string <- gsub(" *[,] *", ",", string)
60 string <- gsub("^\\s+|\\s+$", "", string)
61 return(string)
62 }
63
64 # Function to change periods to whitespace in a string
65 unmake.names <- function(string) {
66 string <- gsub(".", " ", string, fixed=TRUE)
67 return(string)
68 }
69
70 # Generate output folder and paths
71 makeOut <- function(filename) {
72 return(paste0(outPath, "/", filename))
73 }
74
75 # Generating design information
76 pasteListName <- function(string) {
77 return(paste0("factors$", string))
78 }
79
80 # Create cata function: default path set, default seperator empty and appending
81 # true by default (Ripped straight from the cat function with altered argument
82 # defaults)
83 cata <- function(..., file = htmlPath, sep = "", fill = FALSE, labels = NULL,
84 append = TRUE) {
85 if (is.character(file))
86 if (file == "")
87 file <- stdout()
88 else if (substring(file, 1L, 1L) == "|") {
89 file <- pipe(substring(file, 2L), "w")
90 on.exit(close(file))
91 }
92 else {
93 file <- file(file, ifelse(append, "a", "w"))
94 on.exit(close(file))
95 }
96 .Internal(cat(list(...), file, sep, fill, labels, append))
97 }
98
99 # Function to write code for html head and title
100 HtmlHead <- function(title) {
101 cata("<head>\n")
102 cata("<title>", title, "</title>\n")
103 cata("</head>\n")
104 }
105
106 # Function to write code for html links
107 HtmlLink <- function(address, label=address) {
108 cata("<a href=\"", address, "\" target=\"_blank\">", label, "</a><br />\n")
109 }
110
111 # Function to write code for html images
112 HtmlImage <- function(source, label=source, height=600, width=600) {
113 cata("<img src=\"", source, "\" alt=\"", label, "\" height=\"", height)
114 cata("\" width=\"", width, "\"/>\n")
115 }
116
117 # Function to write code for html list items
118 ListItem <- function(...) {
119 cata("<li>", ..., "</li>\n")
120 }
121
122 TableItem <- function(...) {
123 cata("<td>", ..., "</td>\n")
124 }
125
126 TableHeadItem <- function(...) {
127 cata("<th>", ..., "</th>\n")
128 }
129
130 ################################################################################
131 ### Input Processing
132 ################################################################################
133
134 # Collects arguments from command line
135 argv <- commandArgs(TRUE)
136
137 # Grab arguments
138 countPath <- as.character(argv[1])
139 annoPath <- as.character(argv[2])
140 htmlPath <- as.character(argv[3])
141 outPath <- as.character(argv[4])
142 rdaOpt <- as.character(argv[5])
143 normOpt <- as.character(argv[6])
144 weightOpt <- as.character(argv[7])
145 contrastData <- as.character(argv[8])
146 cpmReq <- as.numeric(argv[9])
147 sampleReq <- as.numeric(argv[10])
148 pAdjOpt <- as.character(argv[11])
149 pValReq <- as.numeric(argv[12])
150 lfcReq <- as.numeric(argv[13])
151 factorData <- list()
152 for (i in 14:length(argv)) {
153 newFact <- unlist(strsplit(as.character(argv[i]), split="::"))
154 factorData <- rbind(factorData, newFact)
155 } # Factors have the form: FACT_NAME::LEVEL,LEVEL,LEVEL,LEVEL,...
156
157 # Process arguments
158 if (weightOpt=="yes") {
159 wantWeight <- TRUE
160 } else {
161 wantWeight <- FALSE
162 }
163
164 if (rdaOpt=="yes") {
165 wantRda <- TRUE
166 } else {
167 wantRda <- FALSE
168 }
169
170 if (annoPath=="None") {
171 haveAnno <- FALSE
172 } else {
173 haveAnno <- TRUE
174 }
175
176 # Set the row names to be the name of the factor and delete first row
177 row.names(factorData) <- factorData[, 1]
178 factorData <- factorData[, -1]
179 factorData <- sapply(factorData, sanitiseGroups)
180 factorData <- sapply(factorData, strsplit, split=",")
181 factorData <- sapply(factorData, make.names)
182
183 # Transform factor data into data frame of R factor objects
184 factors <- data.frame(factorData)
185
186 #Create output directory
187 dir.create(outPath, showWarnings=FALSE)
188
189 # Split up contrasts seperated by comma into a vector then sanitise
190 contrastData <- unlist(strsplit(contrastData, split=","))
191 contrastData <- sanitiseEquation(contrastData)
192 contrastData <- gsub(" ", ".", contrastData, fixed=TRUE)
193
194 bcvOutPdf <- makeOut("bcvplot.pdf")
195 bcvOutPng <- makeOut("bcvplot.png")
196 mdsOutPdf <- makeOut("mdsplot.pdf")
197 mdsOutPng <- makeOut("mdsplot.png")
198 voomOutPdf <- makeOut("voomplot.pdf")
199 voomOutPng <- makeOut("voomplot.png")
200 maOutPdf <- character() # Initialise character vector
201 maOutPng <- character()
202 topOut <- character()
203 for (i in 1:length(contrastData)) {
204 maOutPdf[i] <- makeOut(paste0("maplot(", contrastData[i], ").pdf"))
205 maOutPng[i] <- makeOut(paste0("maplot(", contrastData[i], ").png"))
206 topOut[i] <- makeOut(paste0("toptab(", contrastData[i], ").tsv"))
207 } # Save output paths for each contrast as vectors
208 rdaOut <- makeOut("RData.rda")
209 sessionOut <- makeOut("session_info.txt")
210
211 # Initialise data for html links and images, data frame with columns Label and
212 # Link
213 linkData <- data.frame(Label=character(), Link=character(),
214 stringsAsFactors=FALSE)
215 imageData <- data.frame(Label=character(), Link=character(),
216 stringsAsFactors=FALSE)
217
218 # Initialise vectors for storage of up/down/neutral regulated counts
219 upCount <- numeric()
220 downCount <- numeric()
221 flatCount <- numeric()
222
223 # Read in counts and geneanno data
224 counts <- read.table(countPath, header=TRUE, sep="\t")
225 row.names(counts) <- counts$GeneID
226 counts <- counts[ , !(colnames(counts)=="GeneID")]
227 countsRows <- nrow(counts)
228 if (haveAnno) {
229 geneanno <- read.table(annoPath, header=TRUE, sep="\t")
230 }
231
232 ################################################################################
233 ### Data Processing
234 ################################################################################
235
236 # Extract counts and annotation data
237 data <- list()
238 data$counts <- counts
239 if (haveAnno) {
240 data$genes <- geneanno
241 } else {
242 data$genes <- data.frame(GeneID=row.names(counts))
243 }
244
245 # Filter out genes that do not have a required cpm in a required number of
246 # samples
247 preFilterCount <- nrow(data$counts)
248 sel <- rowSums(cpm(data$counts) > cpmReq) >= sampleReq
249 data$counts <- data$counts[sel, ]
250 data$genes <- data$genes[sel, ]
251 postFilterCount <- nrow(data$counts)
252 filteredCount <- preFilterCount-postFilterCount
253
254 # Creating naming data
255 samplenames <- colnames(data$counts)
256 sampleanno <- data.frame("sampleID"=samplenames, factors)
257
258 # Generating the DGEList object "data"
259 data$samples <- sampleanno
260 data$samples$lib.size <- colSums(data$counts)
261 data$samples$norm.factors <- 1
262 row.names(data$samples) <- colnames(data$counts)
263 data <- new("DGEList", data)
264
265 factorList <- sapply(names(factors), pasteListName)
266 formula <- "~0"
267 for (i in 1:length(factorList)) {
268 formula <- paste(formula, factorList[i], sep="+")
269 }
270 formula <- formula(formula)
271 design <- model.matrix(formula)
272 for (i in 1:length(factorList)) {
273 colnames(design) <- gsub(factorList[i], "", colnames(design), fixed=TRUE)
274 }
275
276 # Calculating normalising factor, estimating dispersion
277 data <- calcNormFactors(data, method=normOpt)
278 #data <- estimateDisp(data, design=design, robust=TRUE)
279
280 # Generate contrasts information
281 contrasts <- makeContrasts(contrasts=contrastData, levels=design)
282
283 # Name rows of factors according to their sample
284 row.names(factors) <- names(data$counts)
285
286 ################################################################################
287 ### Data Output
288 ################################################################################
289
290 # BCV Plot
291 #png(bcvOutPng, width=600, height=600)
292 #plotBCV(data, main="BCV Plot")
293 #imageData[1, ] <- c("BCV Plot", "bcvplot.png")
294 #invisible(dev.off())
295
296 #pdf(bcvOutPdf)
297 #plotBCV(data, main="BCV Plot")
298 #invisible(dev.off())
299
300 if (wantWeight) {
301 # Creating voom data object and plot
302 png(voomOutPng, width=1000, height=600)
303 vData <- voomWithQualityWeights(data, design=design, plot=TRUE)
304 imageData[1, ] <- c("Voom Plot", "voomplot.png")
305 invisible(dev.off())
306
307 pdf(voomOutPdf, width=14)
308 vData <- voomWithQualityWeights(data, design=design, plot=TRUE)
309 linkData[1, ] <- c("Voom Plot (.pdf)", "voomplot.pdf")
310 invisible(dev.off())
311
312 # Generating fit data and top table with weights
313 wts <- vData$weights
314 voomFit <- lmFit(vData, design, weights=wts)
315
316 } else {
317 # Creating voom data object and plot
318 png(voomOutPng, width=600, height=600)
319 vData <- voom(data, design=design, plot=TRUE)
320 imageData[1, ] <- c("Voom Plot", "voomplot.png")
321 invisible(dev.off())
322
323 pdf(voomOutPdf)
324 vData <- voom(data, design=design, plot=TRUE)
325 linkData[1, ] <- c("Voom Plot (.pdf)", "voomplot.pdf")
326 invisible(dev.off())
327
328 # Generate voom fit
329 voomFit <- lmFit(vData, design)
330
331 }
332
333 # Fit linear model and estimate dispersion with eBayes
334 voomFit <- contrasts.fit(voomFit, contrasts)
335 voomFit <- eBayes(voomFit)
336
337 # Plot MDS
338 labels <- names(counts)
339 png(mdsOutPng, width=600, height=600)
340 # Currently only using a single factor
341 plotMDS(vData, labels=labels, col=as.numeric(factors[, 1]), cex=0.8)
342 imgName <- "Voom Plot"
343 imgAddr <- "mdsplot.png"
344 imageData <- rbind(imageData, c(imgName, imgAddr))
345 invisible(dev.off())
346
347 pdf(mdsOutPdf)
348 plotMDS(vData, labels=labels, cex=0.5)
349 linkName <- paste0("MDS Plot (.pdf)")
350 linkAddr <- paste0("mdsplot.pdf")
351 linkData <- rbind(linkData, c(linkName, linkAddr))
352 invisible(dev.off())
353
354
355 for (i in 1:length(contrastData)) {
356
357 status = decideTests(voomFit[, i], adjust.method=pAdjOpt, p.value=pValReq,
358 lfc=lfcReq)
359
360 sumStatus <- summary(status)
361
362 # Collect counts for differential expression
363 upCount[i] <- sumStatus["1",]
364 downCount[i] <- sumStatus["-1",]
365 flatCount[i] <- sumStatus["0",]
366
367 # Write top expressions table
368 top <- topTable(voomFit, coef=i, number=Inf, sort.by="P")
369 write.table(top, file=topOut[i], row.names=FALSE, sep="\t")
370
371 linkName <- paste0("Top Differential Expressions(", contrastData[i],
372 ") (.tsv)")
373 linkAddr <- paste0("toptab(", contrastData[i], ").tsv")
374 linkData <- rbind(linkData, c(linkName, linkAddr))
375
376 # Plot MA (log ratios vs mean average) using limma package on weighted data
377 pdf(maOutPdf[i])
378 limma::plotMA(voomFit, status=status, coef=i,
379 main=paste("MA Plot:", unmake.names(contrastData[i])),
380 col=alpha(c("firebrick", "blue"), 0.4), values=c("1", "-1"),
381 xlab="Average Expression", ylab="logFC")
382
383 abline(h=0, col="grey", lty=2)
384
385 linkName <- paste0("MA Plot(", contrastData[i], ")", " (.pdf)")
386 linkAddr <- paste0("maplot(", contrastData[i], ").pdf")
387 linkData <- rbind(linkData, c(linkName, linkAddr))
388 invisible(dev.off())
389
390 png(maOutPng[i], height=600, width=600)
391 limma::plotMA(voomFit, status=status, coef=i,
392 main=paste("MA Plot:", unmake.names(contrastData[i])),
393 col=alpha(c("firebrick", "blue"), 0.4), values=c("1", "-1"),
394 xlab="Average Expression", ylab="logFC")
395
396 abline(h=0, col="grey", lty=2)
397
398 imgName <- paste0("MA Plot(", contrastData[i], ")")
399 imgAddr <- paste0("maplot(", contrastData[i], ").png")
400 imageData <- rbind(imageData, c(imgName, imgAddr))
401 invisible(dev.off())
402 }
403 sigDiff <- data.frame(Up=upCount, Flat=flatCount, Down=downCount)
404 row.names(sigDiff) <- contrastData
405
406 # Save relevant items as rda object
407 if (wantRda) {
408 if (wantWeight) {
409 save(data, status, vData, labels, factors, wts, voomFit, top, contrasts,
410 design,
411 file=rdaOut, ascii=TRUE)
412 } else {
413 save(data, status, vData, labels, factors, voomFit, top, contrasts, design,
414 file=rdaOut, ascii=TRUE)
415 }
416 linkData <- rbind(linkData, c("RData (.rda)", "RData.rda"))
417 }
418
419 # Record session info
420 writeLines(capture.output(sessionInfo()), sessionOut)
421 linkData <- rbind(linkData, c("Session Info", "session_info.txt"))
422
423 # Record ending time and calculate total run time
424 timeEnd <- as.character(Sys.time())
425 timeTaken <- capture.output(round(difftime(timeEnd,timeStart), digits=3))
426 timeTaken <- gsub("Time difference of ", "", timeTaken, fixed=TRUE)
427 ################################################################################
428 ### HTML Generation
429 ################################################################################
430
431 # Clear file
432 cat("", file=htmlPath)
433
434 cata("<html>\n")
435
436 cata("<body>\n")
437 cata("<h3>Limma Voom Analysis Output:</h3>\n")
438 cata("PDF copies of JPEGS available in 'Plots' section.<br />\n")
439 if (wantWeight) {
440 HtmlImage(imageData$Link[1], imageData$Label[1], width=1000)
441 } else {
442 HtmlImage(imageData$Link[1], imageData$Label[1])
443 }
444
445 for (i in 2:nrow(imageData)) {
446 HtmlImage(imageData$Link[i], imageData$Label[i])
447 }
448
449 cata("<h4>Differential Expression Counts:</h4>\n")
450
451 cata("<table border=\"1\" cellpadding=\"4\">\n")
452 cata("<tr>\n")
453 TableItem()
454 for (i in colnames(sigDiff)) {
455 TableHeadItem(i)
456 }
457 cata("</tr>\n")
458 for (i in 1:nrow(sigDiff)) {
459 cata("<tr>\n")
460 TableHeadItem(unmake.names(row.names(sigDiff)[i]))
461 for (j in 1:ncol(sigDiff)) {
462 TableItem(as.character(sigDiff[i, j]))
463 }
464 cata("</tr>\n")
465 }
466 cata("</table>")
467
468 cata("<h4>Plots:</h4>\n")
469 for (i in 1:nrow(linkData)) {
470 if (grepl(".pdf", linkData$Link[i])) {
471 HtmlLink(linkData$Link[i], linkData$Label[i])
472 }
473 }
474
475 cata("<h4>Tables:</h4>\n")
476 for (i in 1:nrow(linkData)) {
477 if (grepl(".tsv", linkData$Link[i])) {
478 HtmlLink(linkData$Link[i], linkData$Label[i])
479 }
480 }
481
482 if (wantRda) {
483 cata("<h4>R Data Object:</h4>\n")
484 for (i in 1:nrow(linkData)) {
485 if (grepl(".rda", linkData$Link[i])) {
486 HtmlLink(linkData$Link[i], linkData$Label[i])
487 }
488 }
489 }
490
491 cata("<p>Alt-click links to download file.</p>\n")
492 cata("<p>Click floppy disc icon associated history item to download ")
493 cata("all files.</p>\n")
494 cata("<p>.tsv files can be viewed in Excel or any spreadsheet program.</p>\n")
495
496 cata("<h4>Additional Information</h4>\n")
497 cata("<ul>\n")
498 if (cpmReq!=0 && sampleReq!=0) {
499 tempStr <- paste("Genes without more than", cpmReq,
500 "CPM in at least", sampleReq, "samples are insignificant",
501 "and filtered out.")
502 ListItem(tempStr)
503 filterProp <- round(filteredCount/preFilterCount*100, digits=2)
504 tempStr <- paste0(filteredCount, " of ", preFilterCount," (", filterProp,
505 "%) genes were filtered out for low expression.")
506 ListItem(tempStr)
507 }
508 ListItem(normOpt, " was the method used to normalise library sizes.")
509 if (wantWeight) {
510 ListItem("Weights were applied to samples.")
511 } else {
512 ListItem("Weights were not applied to samples.")
513 }
514 if (pAdjOpt!="none") {
515 if (pAdjOpt=="BH" || pAdjOpt=="BY") {
516 tempStr <- paste0("MA-Plot highlighted genes are significant at FDR ",
517 "of ", pValReq," and exhibit log2-fold-change of at ",
518 "least ", lfcReq, ".")
519 ListItem(tempStr)
520 } else if (pAdjOpt=="holm") {
521 tempStr <- paste0("MA-Plot highlighted genes are significant at adjusted ",
522 "p-value of ", pValReq," by the Holm(1979) ",
523 "method, and exhibit log2-fold-change of at least ",
524 lfcReq, ".")
525 ListItem(tempStr)
526 }
527 } else {
528 tempStr <- paste0("MA-Plot highlighted genes are significant at p-value ",
529 "of ", pValReq," and exhibit log2-fold-change of at ",
530 "least ", lfcReq, ".")
531 ListItem(tempStr)
532 }
533 cata("</ul>\n")
534
535 cata("<h4>Summary of experimental data:</h4>\n")
536
537 cata("<p>*CHECK THAT SAMPLES ARE ASSOCIATED WITH CORRECT GROUP*</p>\n")
538
539 cata("<table border=\"1\" cellpadding=\"3\">\n")
540 cata("<tr>\n")
541 TableItem()
542 for (i in names(factors)) {
543 TableHeadItem(i)
544 }
545 cata("</tr>\n")
546
547 for (i in 1:nrow(factors)) {
548 cata("<tr>\n")
549 TableHeadItem(row.names(factors)[i])
550 for (j in ncol(factors)) {
551 TableItem(as.character(unmake.names(factors[i, j])))
552 }
553 cata("</tr>\n")
554 }
555 cata("</table>")
556
557 cit <- character()
558 link <- character()
559 link[1] <- paste0("<a href=\"",
560 "http://www.bioconductor.org/packages/release/bioc/",
561 "vignettes/limma/inst/doc/usersguide.pdf",
562 "\">", "limma User's Guide", "</a>.")
563
564 link[2] <- paste0("<a href=\"",
565 "http://www.bioconductor.org/packages/release/bioc/",
566 "vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf",
567 "\">", "edgeR User's Guide", "</a>")
568
569 cit[1] <- paste("Please cite the paper below for the limma software itself.",
570 "Please also try to cite the appropriate methodology articles",
571 "that describe the statistical methods implemented in limma,",
572 "depending on which limma functions you are using. The",
573 "methodology articles are listed in Section 2.1 of the",
574 link[1],
575 "Cite no. 3 only if sample weights were used.")
576 cit[2] <- paste("Smyth, GK (2005). Limma: linear models for microarray data.",
577 "In: 'Bioinformatics and Computational Biology Solutions using",
578 "R and Bioconductor'. R. Gentleman, V. Carey, S. doit,.",
579 "Irizarry, W. Huber (eds), Springer, New York, pages 397-420.")
580 cit[3] <- paste("Please cite the first paper for the software itself and the",
581 "other papers for the various original statistical methods",
582 "implemented in edgeR. See Section 1.2 in the", link[2],
583 "for more detail.")
584 cit[4] <- paste("Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a",
585 "Bioconductor package for differential expression analysis",
586 "of digital gene expression data. Bioinformatics 26, 139-140")
587 cit[5] <- paste("Robinson MD and Smyth GK (2007). Moderated statistical tests",
588 "for assessing differences in tag abundance. Bioinformatics",
589 "23, 2881-2887")
590 cit[6] <- paste("Robinson MD and Smyth GK (2008). Small-sample estimation of",
591 "negative binomial dispersion, with applications to SAGE data.",
592 "Biostatistics, 9, 321-332")
593 cit[7] <- paste("McCarthy DJ, Chen Y and Smyth GK (2012). Differential",
594 "expression analysis of multifactor RNA-Seq experiments with",
595 "respect to biological variation. Nucleic Acids Research 40,",
596 "4288-4297")
597 cit[8] <- paste("Law, CW, Chen, Y, Shi, W, and Smyth, GK (2014). Voom:",
598 "precision weights unlock linear model analysis tools for",
599 "RNA-seq read counts. Genome Biology 15, R29.")
600 cit[9] <- paste("Ritchie, M. E., Diyagama, D., Neilson, J., van Laar,",
601 "R., Dobrovic, A., Holloway, A., and Smyth, G. K. (2006).",
602 "Empirical array quality weights for microarray data.",
603 "BMC Bioinformatics 7, Article 261.")
604 cata("<h3>Citations</h3>\n")
605
606 cata("<h4>limma</h4>\n")
607 cata(cit[1], "\n")
608 cata("<ol>\n")
609 ListItem(cit[2])
610 ListItem(cit[8])
611 ListItem(cit[9])
612 cata("</ol>\n")
613
614 cata("<h4>edgeR</h4>\n")
615 cata(cit[3], "\n")
616 cata("<ol>\n")
617 ListItem(cit[4])
618 ListItem(cit[5])
619 ListItem(cit[6])
620 ListItem(cit[7])
621 cata("</ol>\n")
622
623 cata("<p>Report problems to: su.s@wehi.edu.au</p>\n")
624
625 for (i in 1:nrow(linkData)) {
626 if (grepl("session_info", linkData$Link[i])) {
627 HtmlLink(linkData$Link[i], linkData$Label[i])
628 }
629 }
630
631 cata("<table border=\"0\">\n")
632 cata("<tr>\n")
633 TableItem("Task started at:"); TableItem(timeStart)
634 cata("</tr>\n")
635 cata("<tr>\n")
636 TableItem("Task ended at:"); TableItem(timeEnd)
637 cata("</tr>\n")
638 cata("<tr>\n")
639 TableItem("Task run time:"); TableItem(timeTaken)
640 cata("<tr>\n")
641 cata("</table>\n")
642
643 cata("</body>\n")
644 cata("</html>")