CustomConsensusClusters | 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()
,
cumulativeCTSSdistribution()
,
distclu()
,
getCTSS()
,
normalizeTagCount()
,
paraclu()
,
quantilePositions()
,
quickEnhancers()
,
resetCAGEexp()
,
summariseChrExpr()
Other CAGEr clusters functions:
CTSScumulativesTagClusters()
,
aggregateTagClusters()
,
consensusClustersDESeq2()
,
consensusClustersGR()
,
cumulativeCTSSdistribution()
,
distclu()
,
paraclu()
,
plotInterquantileWidth()
,
quantilePositions()
,
tagClustersGR()
cc <- consensusClustersGR(exampleCAGEexp)
CustomConsensusClusters(exampleCAGEexp, cc)
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