hicdiff2mtx: Converts significance maps to dense matrices.

In rz6/CopulaHiC: Hi-C differential analysis via dependency modelling of chromatin interactions with generalized linear models

Description

Given list of significance maps in sparse format produced by hicdiff function converts them to dense matrix format.

Usage

hicdiff2mtx(
  hicdiff.list,
  maps.dims,
  val.column = c("qvalue", "pvalue")[1],
  neg.log = TRUE,
  which.enrichment = c("both", "x", "y")[1]
)

Arguments

hicdiff.list	list of data frames, output from hicdiff function
maps.dims	list of data frames, usually an attribute of HiCglm object that was used to produce hicdiff.list
val.column	character indicating which column of sparse significance map to use as cell value for dense matrix (either pvalue or qvalue)
neg.log	logical wheter to apply -log transformation to val.column
which.enrichment	character indicating whether to calculate Y enrichment (i.e. E[Y | X] model) - choose y, X enrichment (i.e. E[X | Y] model) - choose x or both

Value

list with dense matrices containing significance in each cell; when which.enrichment is fixed to both upper triangular map will contain significances of E[Y | X] model and lower triangular will contain significances of E[X | Y]

See Also

hicdiff for generation of hicdiff.list

rz6/CopulaHiC documentation built on Dec. 31, 2019, 9:19 a.m.