trimClusters | R Documentation |
Trimming of the clusters removes redundant information derived from random
fragmentation of the reads during library preparation. This method takes
a rnaCrosslinkDataSet
object where clustering has been performed with
the clusterrnaCrosslink method and trims the clusters according to the
trimFactor argument.
trimClusters(clusteredCds, trimFactor = 2.5, clusterCutoff = 1)
clusteredCds |
a |
trimFactor |
a positive value that defines how much the clusters will |
clusterCutoff |
Minimum number of reads before discarding cluster be trimmed = mean + ( sd * trimFactor ) |
The 3 attributes; matrixList, clusterTableList and clusterGrangesList
will gain the types
"superClusters" and "trimmedClusters"
Returns a rnaCrosslinkDataSet
object
cds = makeExamplernaCrosslinkDataSet()
clusteredCds = clusterrnaCrosslink(cds,
cores = 1,
stepCount = 1,
clusterCutoff = 0)
trimClusters(clusteredCds = clusteredCds,
trimFactor = 1,
clusterCutoff = 0)
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