CustomConsensusClusters {CAGEr} | R Documentation |
Intersects custom consensus clusters with the CTSS data in a
CAGEexp
object, and stores the result as a expression matrices
(raw and normalised tag counts).
CustomConsensusClusters( object, clusters, threshold = 0, nrPassThreshold = 1, thresholdIsTpm = TRUE ) ## S4 method for signature 'CAGEexp,GRanges' CustomConsensusClusters( object, clusters, threshold = 0, nrPassThreshold = 1, thresholdIsTpm = TRUE )
object |
A |
clusters |
Consensus clusters in |
threshold, nrPassThreshold |
Only CTSSs with signal |
thresholdIsTpm |
Logical, is threshold raw tag count value (FALSE) or normalized signal (TRUE). |
Consensus clusters must not overlap, so that a single base of the
genome can only be attributed to a single cluster. This is enforced by the
.ConsensusClusters
constructor.
stores the result as a new RangedSummarizedExperiment
in the
experiment
slot of the object. The assays of the new experiment are called
counts
and normalized
. An outOfClusters
column is added
to the sample metadata to reflect the number of molecules that do not have
their TSS in a consensus cluster.
Charles Plessy
Other CAGEr object modifiers:
CTSStoGenes()
,
aggregateTagClusters()
,
annotateCTSS()
,
clusterCTSS()
,
cumulativeCTSSdistribution()
,
getCTSS()
,
normalizeTagCount()
,
quantilePositions()
,
summariseChrExpr()
Other CAGEr clusters functions:
CTSSclusteringMethod()
,
CTSScumulativesTagClusters()
,
aggregateTagClusters()
,
clusterCTSS()
,
consensusClustersDESeq2()
,
consensusClustersGR()
,
cumulativeCTSSdistribution()
,
plotInterquantileWidth()
,
quantilePositions()
,
tagClustersGR()
cc <- consensusClustersGR(exampleCAGEexp) CustomConsensusClusters(exampleCAGEexp, cc)