Description Usage Arguments Details Value Author(s) See Also Examples
Aggregates tag clusters (TCs) across all CAGE datasets within the CAGEr object to create a referent set of consensus clusters.
1 2 3 4 5 6 7 8 | aggregateTagClusters(object, tpmThreshold = 5,
excludeSignalBelowThreshold = TRUE, qLow = NULL, qUp = NULL,
maxDist = 100, useMulticore = FALSE, nrCores = NULL)
## S4 method for signature 'CAGEr'
aggregateTagClusters(object, tpmThreshold = 5,
excludeSignalBelowThreshold = TRUE, qLow = NULL, qUp = NULL,
maxDist = 100, useMulticore = FALSE, nrCores = NULL)
|
object |
A |
tpmThreshold |
Ignore tag clusters with normalized signal |
excludeSignalBelowThreshold |
When |
qLow, qUp |
Set which "lower" (or "upper") quantile should be used as 5'
(or 3') boundary of the tag cluster. If |
maxDist |
Maximal length of the gap (in base-pairs) between two tag clusters for them to be part of the same consensus clusters. |
useMulticore |
Logical, should multicore be used (supported only on Unix-like platforms). |
nrCores |
Number of cores to use when |
Since the tag clusters (TCs) returned by the clusterCTSS
function are constructed separately for every CAGE sample within the CAGEr
object, they can differ between samples in both their number, genomic
coordinates, position of dominant TSS and #' overall signal. To be able to
compare all samples at the level of clusters of TSSs, TCs from all CAGE
datasets are aggregated into a single set of consensus clusters. First, TCs
with signal >= tpmThreshold from all CAGE datasets are selected, and their
5' and 3' boundaries are determined based on provided qLow and qUp
parameter (or the start and end coordinates, if they are set to NULL).
Finally, the defined set of TCs from all CAGE datasets is reduced to a
non-overlapping set of consensus clusters by merging overlapping TCs and TCs
<= maxDist base-pairs apart. Consensus clusters represent a referent set
of promoters that can be further used for expression profiling or detecting
"shifting" (differentially used) promoters between different CAGE samples.
For CAGEset objects, the consensusClusters slot will be
populated with a data frame indicating the cluster name, chromosome, start
and end coordinates, the strand, and the normalised expression score of the
cluster. This table is returned by the consensusClusters function.
For CAGEexp objects, the experiment consensusClusters will be occupied
by a RangedSummarizedExperiment containing the cluster coodinates as row
ranges, and their expression levels in the counts and normalized assays.
These genomic ranges are returned by the consensusClustersGR function.
The CTSS ranges of the tagCountMatrix experiment will gain a cluster
column indicating which cluster they belong to. Lastly, the number of
CTSS outside clusters will be documented in the outOfClusters column data.
This table is returned by the consensusClusters function.
Vanja Haberle
Charles Plessy
Other CAGEr object modifiers: CTSStoGenes,
CustomConsensusClusters,
annotateCTSS, clusterCTSS,
cumulativeCTSSdistribution,
getCTSS, normalizeTagCount,
quantilePositions,
summariseChrExpr
Other CAGEr clusters functions: CTSSclusteringMethod,
CTSScumulativesTagClusters,
CustomConsensusClusters,
clusterCTSS,
consensusClustersDESeq2,
consensusClustersGR,
cumulativeCTSSdistribution,
plotInterquantileWidth,
quantilePositions,
tagClusters
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | head(consensusClusters(exampleCAGEset))
aggregateTagClusters( exampleCAGEset, tpmThreshold = 50
, excludeSignalBelowThreshold = FALSE, maxDist = 100)
head(consensusClusters(exampleCAGEset))
aggregateTagClusters(object = exampleCAGEset, tpmThreshold = 50,
excludeSignalBelowThreshold = FALSE, qLow = 0.1, qUp = 0.9, maxDist = 100)
head(consensusClusters(exampleCAGEset))
consensusClustersGR(exampleCAGEexp)
aggregateTagClusters( exampleCAGEexp, tpmThreshold = 50
, excludeSignalBelowThreshold = FALSE, maxDist = 100)
consensusClustersGR(exampleCAGEexp)
aggregateTagClusters( exampleCAGEexp, tpmThreshold = 50
, excludeSignalBelowThreshold = TRUE, maxDist = 100)
consensusClustersGR(exampleCAGEexp)
aggregateTagClusters( exampleCAGEexp, tpmThreshold = 50
, excludeSignalBelowThreshold = TRUE, maxDist = 100
, qLow = 0.1, qUp = 0.9)
consensusClustersGR(exampleCAGEexp)
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