The sequence of each motif is read once and scored against the k-mer
weights of every sample, so the correction differs by sample and motif
and survives a row-wise z-scoring.
Usage
accExpectedMatrix(tfbs, bias, genome, k = 6L, max.sites = 25000)
Arguments
- tfbs
A named list of prepared binding sites.
- bias
A named list of per sample k-mer weights.
- genome
A BSgenome object.
- k
Length of the k-mer.
- max.sites
Number of binding sites drawn per motif.
Value
A matrix of motifs by samples.
Examples
if (FALSE) { # \dontrun{
accExpectedMatrix(tfbs, bias, Hsapiens)
} # }