featureEnrich: Test Genomic Feature Enrichment

In Bishop-Laboratory/RLSeq: RLSeq: An analysis package for R-loop mapping data

Test Genomic Feature Enrichment

Description

Tests the enrichment of genomic features in supplied peaks. See details.

Usage

featureEnrich(
  object,
  annotype = c("primary", "full"),
  annotations = NULL,
  downsample = 10000,
  quiet = FALSE
)

Arguments

object	An RLRanges object.
annotype	The type of annotations to use. Can be one of "primary" or "full". Default: "primary". See RLHub::annotations for greater detail.
annotations	A custom annotation list of the same structure described in RLHub::annotations.
downsample	If a numeric, data will be down sampled to the requested number of peaks. This improves the speed of genomic shuffling and helps prevent p-value inflation. If FALSE, then downsampling will not be performed. Default: 10000.
quiet	If TRUE, messages will be suppressed. Default: FALSE

Details

Method

Annotations relevant to R-loops were curated as part of the RLBase-data workflow and are provided via RLHub::annotations.

In featureEnrich, each annotation "type" (e.g., "Exons", "Introns", etc) is compared to the supplied RLRanges, yielding enrichment statistics with the following procedure:

1. For each annotation type, the peaks are overlapped with the annotations.

2. Then, valr::bed_reldist is used to find the relative distance distribution between the peaks and the annotations for both the supplied RLRanges and shuffled RLRanges (via valr::bed_shuffle). Significance of the relative distance is calculated via stats::ks.test.

3. Then, Fisher’s exact test is implemented via valr::bed_fisher to obtain the significance of the overlap and the odds ratio.

Value

An RLRanges object containing the results of the enrichment test accessed via rlresult(object, "featureEnrichment"). The results are in tbl format. For a full description of all columns in the output table see RLHub::feat_enrich_samples.

Examples

# Example RLRanges dataset
rlr <- readRDS(system.file("extdata", "rlrsmall.rds", package = "RLSeq"))

# RL Region Test
featureEnrich(rlr)

# With custom annotations
small_anno <- list(
    "Centromeres" = readr::read_csv(
        system.file("extdata", "Centromeres.csv.gz", package = "RLSeq"),
        show_col_types = FALSE
    )
)
featureEnrich(rlr, annotations = small_anno)

Bishop-Laboratory/RLSeq documentation built on Jan. 28, 2023, 11:38 p.m.