| tagClustersGR {CAGEr} | R Documentation |
Extracts tag clusters (TCs) produced by clusterCTSS function
for a specified CAGE experiment from a CAGEexp object.
tagClustersGR( object, sample = NULL, returnInterquantileWidth = FALSE, qLow = NULL, qUp = NULL ) ## S4 method for signature 'CAGEexp' tagClustersGR( object, sample = NULL, returnInterquantileWidth = FALSE, qLow = NULL, qUp = NULL ) tagClustersGR(object, sample = NULL) <- value ## S4 replacement method for signature 'CAGEexp,ANY,TagClusters' tagClustersGR(object, sample = NULL) <- value ## S4 replacement method for signature 'CAGEexp,missing,GRangesList' tagClustersGR(object, sample = NULL) <- value
object |
A |
sample |
Label of the CAGE dataset (experiment, sample) for which to
extract tag clusters. If |
returnInterquantileWidth |
Return the interquantile width for each tag cluster. |
qLow, qUp |
Position of which quantile should be used as a left (lower)
or right (upper) boundary (for |
value |
A |
Returns a GRangesList or a GRanges object with genomic coordinates,
position of dominant TSS, total CAGE signal and additional information for
all TCs from specified CAGE dataset (sample). If
returnInterquantileWidth = TRUE, interquantile width for each TC is also
calculated using provided quantile positions.
Vanja Haberle
Charles Plessy
Other CAGEr accessor methods:
CTSSclusteringMethod(),
CTSScoordinatesGR(),
CTSScumulativesTagClusters(),
CTSSnormalizedTpmDF(),
CTSStagCountDF(),
GeneExpDESeq2(),
GeneExpSE(),
consensusClustersGR(),
expressionClasses(),
genomeName(),
inputFilesType(),
inputFiles(),
librarySizes(),
sampleLabels(),
seqNameTotalsSE()
Other CAGEr clusters functions:
CTSSclusteringMethod(),
CTSScumulativesTagClusters(),
CustomConsensusClusters(),
aggregateTagClusters(),
clusterCTSS(),
consensusClustersDESeq2(),
consensusClustersGR(),
cumulativeCTSSdistribution(),
plotInterquantileWidth(),
quantilePositions()
tagClustersGR( exampleCAGEexp, "Zf.high", TRUE, 0.1, 0.9 )
tagClustersGR( exampleCAGEexp, 1
, returnInterquantileWidth = TRUE, qLow = 0.1, qUp = 0.9 )