JunctionSeqCountSet
object.
This function is called internally by the runJunctionSeqAnalyses
function, and thus for most purposes users should not need to call this
function directly. It may be useful to advanced users performing non-standard
analyses.
readJunctionSeqCounts(countfiles, countdata, samplenames, design, flat.gff.file, test.formula1 = formula(~ sample + countbin + condition : countbin), analysis.type = c("junctionsAndExons","junctionsOnly","exonsOnly"), nCores = 1, use.exons, use.junctions, use.known.junctions = TRUE, use.novel.junctions = TRUE, use.multigene.aggregates = FALSE, gene.names, verbose = TRUE, method.countVectors = c("geneLevelCounts","sumOfAllBinsForGene", "sumOfAllBinsOfSameTypeForGene")
)
analysis.type
parameter.
If TRUE
, then exonic region loci will be included in the analyses and will be tested for
differential usage. If this parameter is set, then parameter use.junctions
must also be set.
analysis.type
parameter.
If TRUE
, then splice junction loci will be included in the analyses and will be tested for
differential usage. If this parameter is set, then parameter use.exons
must also be set.
TRUE
, then known splice junctions will not be filtered out prior to analysis. Note: this is overidden if use.junctions is FALSE
or if analysis.type
is set to "exonsOnly".
TRUE
, then novel splice junctions will not be filtered out prior to analysis. Note: this is overidden if use.junctions is FALSE
or if analysis.type
is set to "exonsOnly".
Determines the type of count vectors to be used in the model framework. By default JunctionSeq compares the counts for a specific feature against the counts across the rest of the gene minus the counts for the specific feature. Alternatively, the sum of all other features on the gene can be used, like in DEXSeq. The advantage to the default JunctionSeq behavior is that no read or read-pair is ever counted more than once in any model. Under DEXSeq, some reads may cover many exonic segments and thus be counted repeatedly.
######################################## #Set up example data: decoder.file <- system.file( "extdata/annoFiles/decoder.bySample.txt", package="JctSeqData"); decoder <- read.table(decoder.file, header=TRUE, stringsAsFactors=FALSE); gff.file <- system.file( "extdata/tiny/withNovel.forJunctionSeq.gff.gz", package="JctSeqData"); countFiles <- system.file(paste0("extdata/tiny/", decoder$sample.ID, "/QC.spliceJunctionAndExonCounts.withNovel.forJunctionSeq.txt.gz"), package="JctSeqData"); ######################################## #Advanced Analysis: #Make a "design" dataframe: design <- data.frame(condition = factor(decoder$group.ID)); #Read the QoRTs counts. jscs = readJunctionSeqCounts(countfiles = countFiles, samplenames = decoder$sample.ID, design = design, flat.gff.file = gff.file );
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