Agregate counts across a set of regions, e.g. for footprinting analysis

# S4 method for DsATAC
aggregateRegionCounts(
  .object,
  regionGr,
  samples = getSamples(.object),
  countAggrFun = "sum",
  norm = "tailMean",
  normTailW = 0.1,
  kmerBiasAdj = TRUE,
  k = 6,
  sampleCovg = NULL,
  sampleKmerFreqM = NULL,
  regionKmerFreqM = NULL,
  silent = FALSE
)

Arguments

.object

DsATAC object

regionGr

GRanges object specifying the regions to aggregate over

samples

sample identifiers

countAggrFun

aggration function to be used for summarizing the insertion counts at each position. Possible values include "sum", "mean", and "median"

norm

method used for normalizing the resulting position-wise counts. Currently only 'tailMean' is supported, which computes normalization factors as the mean signal in the tails of the window

normTailW

fraction of the region window to be used on each side of the window to be used for normalization if norm is one of 'tailMean'

kmerBiasAdj

compute Tn5 bias and use it to adjust the counts as in Corces, et al., Science, (2018)

k

length of the kmer to be used for sequence bias correction. Only relevant if kmerBiasAdj==TRUE.

sampleCovg

to save compute time, a sample coverage track list (as computed by getCoverage(.object)) can be supplied. If not, it will be computed on the fly.

sampleKmerFreqM

to save compute time, a matrix of sample kmer frequency at insertion sites (as computed by getInsertionKmerFreq(.object, ...)) can be supplied. If not, it will be computed on the fly. Only relevant if kmerBiasAdj==TRUE.

regionKmerFreqM

to save compute time, a matrix of region kmer frequencies (kmers X window width). Must have the same number of rows as the specified (or computed) sampleKmerFreqM (kmers) and the same number of columns as the window width (median width of regionGr). Only relevant if kmerBiasAdj==TRUE.

silent

limit log messages

Value

a data.frame containing position-wise counts (raw, normalized and optionally Tn5-bias-corrected) for each sample

Author

Fabian Mueller