Find most covered features

Source: R/preprocessing_filtering_reduction.R

Find the top most covered features that will be used for dimensionality reduction. Optionally remove non-top features.

find_top_features(
  scExp,
  n = 20000,
  keep_others = FALSE,
  prioritize_genes = FALSE,
  max_distanceToTSS = 10000,
  verbose = TRUE
)

Arguments

scExp

A SingleCellExperiment.
n

Either an integer indicating the number of top covered regions to find or a character vector of the top percentile of features to keep (e.g. 'q20' to keep top 20% features).
keep_others

Logical indicating if non-top regions are to be removed from the SCE or not (FALSE).
prioritize_genes

First filter by loci being close to genes ? E.g. for differential analysis, it is more relevant to keep features close to genes
max_distanceToTSS

If prioritize_genes is TRUE, the maximum distance to consider a feature close to a gene.
verbose

Print ?

Value

A SCE with top features

Examples

data(scExp)
scExp_top = find_top_features(scExp, n = 4000, keep_others = FALSE)

#> ChromScape::find_top_features - 4000 features kept as  most covered features...