R: Write splice junction browser tracks

writeBedTrack {JunctionSeq}

R Documentation

Write splice junction browser tracks

Description

This function saves the JunctionSeq results in the form of a set of "bed" files designed for use with the UCSC genome browser.

Usage

writeExprBedTrack(file, jscs, 
     trackLine,
     only.with.sig.gene = FALSE,
     only.sig = FALSE, 
     only.testable = TRUE, 
     plot.exons = TRUE, plot.junctions = TRUE, plot.novel.junctions = TRUE,
     group.RGB, 
     use.score = FALSE, 
     FDR.threshold = 0.05, 
     count.digits = 1, 
     includeGeneID = FALSE,
     includeLocusID = TRUE,
     includeGroupID = TRUE,
     output.format = c("BED", "GTF", "GFF3"),
     use.gzip = TRUE,
     verbose = TRUE)

writeSigBedTrack(file, 
     jscs, 
     trackLine,
     only.sig = TRUE, 
     only.testable = TRUE, 
     plot.exons = TRUE, plot.junctions = TRUE, plot.novel.junctions = TRUE,
     sig.RGB = "255,0,0", 
     nonsig.RGB = "0,0,0", 
     use.score = TRUE, 
     FDR.threshold = 0.05, 
     pval.digits = 4, 
     includeGeneID = FALSE,
     includeLocusID = TRUE,
     output.format = c("BED", "GTF", "GFF3"),
     use.gzip = TRUE,
     verbose = TRUE)

Arguments

`file`	Character string. File path for the output bed file.
`jscs`	A `JunctionSeqCountSet`. Usually created by `runJunctionSeqAnalyses`. Alternatively, this can be created manually by `readJunctionSeqCounts`. However in this case a number of additional steps will be necessary: Dispersions and size factors must then be set, usually using functions `estimateSizeFactors` and `estimateJunctionSeqDispersions`. Hypothesis tests must be performed by `testForDiffUsage`. Effect sizes and parameter estimates must be created via `estimateEffectSizes`.
`trackLine`	The "track line" of the bed file. In other words, the first line of the file. By default JunctionSeq will attempt to automatically generate a reasonable track line.
`only.with.sig.gene`	Logical. If `TRUE`, only genes containing statistically significant results will be included.
`only.sig`	Logical. If `TRUE`, only statistically significant loci will be included.
`only.testable`	Logical. If `TRUE`, only loci with sufficiently high expression to be tested will be included.
`plot.exons`	Logical. If `TRUE`, exons will be plotted.
`plot.junctions`	Logical. If `TRUE`, splice junctions will be plotted.
`plot.novel.junctions`	Logical. If `TRUE`, novel splice junctions will be plotted (if plot.junctions is also `TRUE`).
`sig.RGB`	Character string. The RGB color for significant genes. Must be in the format "r,g,b", with each value ranging from 0 to 255.
`nonsig.RGB`	Character string. The RGB color for non-significant loci. Must be in the format "r,g,b", with each value ranging from 0 to 255.
`group.RGB`	Character string. The RGB color used for each experimental group. Must be in the format "r,g,b", with each value ranging from 0 to 255. Must have a length equal to the number of experimental condition values.
`use.score`	Logical. If TRUE, score each locus based on the p-value.
`FDR.threshold`	Numeric. The FDR-adjusted p-value threshold to use to assign statistical significance.
`count.digits`	Numeric. The number of digits after the decimal point to include for the mean normalized counts.
`pval.digits`	Numeric. The number of digits after the decimal point to include for the p-values.
`includeGeneID`	Logical. If TRUE, include the ID of the gene in the "name" field of each line.
`includeLocusID`	Logical. If TRUE, include the ID of the locus in the "name" field of each line.
`includeGroupID`	Logical. If TRUE, include the ID of the group in the "name" field of each line.
`output.format`	Character string. The format to use.
`use.gzip`	Logical. Whether or not to gzip the bed file.
`verbose`	Logical. if TRUE, output debugging/progress information.

Value

This is a side-effecting function, and does not return a value.

Examples

data(exampleDataSet,package="JctSeqData");
writeExprBedTrack("test.exonCoverage.bed.gz", jscs, 
                  plot.exons = TRUE, plot.junctions = FALSE)

## Not run: 
##D ########################################
##D #Set up example data:
##D decoder.file <- system.file(
##D                   "extdata/annoFiles/decoder.bySample.txt",
##D                   package="JctSeqData");
##D decoder <- read.table(decoder.file,
##D                   header=TRUE,
##D                   stringsAsFactors=FALSE);
##D gff.file <- system.file(
##D             "extdata/cts/withNovel.forJunctionSeq.gff.gz",
##D             package="JctSeqData");
##D countFiles <- system.file(paste0("extdata/cts/",
##D      decoder$sample.ID,
##D      "/QC.spliceJunctionAndExonCounts.withNovel.forJunctionSeq.txt.gz"),
##D      package="JctSeqData");
##D ######################
##D #Run example analysis:
##D jscs <- runJunctionSeqAnalyses(sample.files = countFiles,
##D            sample.names = decoder$sample.ID,
##D            condition=factor(decoder$group.ID),
##D            flat.gff.file = gff.file,
##D            analysis.type = "junctionsAndExons"
##D );
##D ########################################
##D 
##D #Exon coverage:
##D writeExprBedTrack("test.exonCoverage.bed.gz", jscs, 
##D                   plot.exons = TRUE, plot.junctions = FALSE)
##D #Junction coverage:
##D writeExprBedTrack("test.jctCoverage.bed.gz", jscs, 
##D                   plot.exons = FALSE, plot.junctions = TRUE)
##D #Both Exon and Junction coverage:
##D writeExprBedTrack("test.featureCoverage.bed.gz", jscs)
##D 
##D #p-values of significant features:
##D writeSigBedTrack("test.pvals.bed.gz", jscs)
##D 
## End(Not run)

[Package JunctionSeq version 1.5.4 Index]