| subsetByComposition {CAGEfightR} | R Documentation |
A convenient wrapper around calcComposition and subset.
subsetByComposition(object, inputAssay = "counts", outputColumn = "composition", unexpressed = 0.1, genes = "geneID", minSamples = 1)
object |
RangedSummarizedExperiment: CAGE data quantified at CTSS, cluster or gene-level. |
inputAssay |
character: Name of assay holding input expression values. |
outputColumn |
character: Name of column in rowRanges to hold composition values. |
unexpressed |
numeric: Composition will be calculated based on features larger than this cutoff. |
genes |
character: Name of column in rowData holding genes (NAs are not allowed.) |
minSamples |
numeric: Only features with composition in more than this number of samples will be kept. |
RangedSummarizedExperiment with composition values added as a column in rowData and features with less composition than minSamples removed.
Other Subsetting functions: subsetByBidirectionality,
subsetBySupport
Other Calculation functions: calcBidirectionality,
calcComposition, calcPooled,
calcShape, calcSupport,
calcTPM, calcTotalTags,
subsetByBidirectionality,
subsetBySupport
data(exampleUnidirectional)
# Annotate clusters with geneIDs:
library(TxDb.Mmusculus.UCSC.mm9.knownGene)
txdb <- TxDb.Mmusculus.UCSC.mm9.knownGene
exampleUnidirectional <- assignGeneID(exampleUnidirectional,
geneModels=txdb,
outputColumn='geneID')
exampleUnidirectional <- subset(exampleUnidirectional, !is.na(geneID))
# Keep only clusters more than 10% in more than one sample:
calcComposition(exampleUnidirectional)
# Keep only clusters more than 5% in more than 2 samples:
subsetByComposition(exampleUnidirectional, unexpressed = 0.05, minSamples=2)