tuneTagClustering: Determine the optimal pooled threshold for unidirectional tag...

In MalteThodberg/CAGEfightR: Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor

Description

This function counts the number of Tag Clusters (TCs) for an series of small incremental pooled cutoffs

Usage

tuneTagClustering(object, ...)

## S4 method for signature 'GRanges'
tuneTagClustering(
  object,
  steps = 10L,
  mergeDist = 20L,
  searchMethod = "minUnique",
  maxExponent = 1
)

## S4 method for signature 'RangedSummarizedExperiment'
tuneTagClustering(object, ...)

## S4 method for signature 'GPos'
tuneTagClustering(object, ...)

Arguments

object	GenomicRanges or RangedSummarizedExperiment: Pooled CTSS.
...	additional arguments passed to methods.
steps	integer: Number of thresholds to analyze (in addition to treshold=0).
mergeDist	integer: Merge TCs within this distance.
searchMethod	character: For advanced user only, see details.
maxExponent	numeric: The maximal threshold to analyse is obtained as min(score)*2^maxExponent (only used if searchMethod='exponential').

Value

data.frame with two columns: threshold and nTCs (number of Tag Clusters)

See Also

Other Clustering functions: clusterBidirectionally(), clusterUnidirectionally(), trimToPeak(), trimToPercentiles()

Examples

## Not run: 
data(exampleCTSSs)

# Calculate pooledTPM, using supplied number of total tags
exampleCTSSs <- calcTPM(exampleCTSSs,
                        inputAssay='counts',
                        outputAssay='TPM',
                        totalTags='totalTags')
exampleCTSSs <- calcPooled(exampleCTSSs, inputAssay='TPM')

# Set backend
library(BiocParallel)
register(SerialParam())

# Find optimal slice-threshold for reduce distance of 20:
tuneTagClustering(object=exampleCTSSs)

## End(Not run)

MalteThodberg/CAGEfightR documentation built on Sept. 11, 2021, 4:42 a.m.