RLSeq {RLSeq} | R Documentation

## RLSeq

### Description

Executes the RLSeq analysis workflow.

### Usage

    RLSeq(object, quiet = FALSE, skip = NULL, ...)

### Arguments

`object` | An RLRanges object.
`quiet` | If `TRUE`, messages are suppressed. Default: `FALSE`.
`skip` | Analysis steps to skip. Default: `NULL`. See details for options.
`...` | Arguments passed to analyzeRLFS.

### Details

The `RLSeq()` function does all of the following by default:

1. RLFS Perm Test. Runs the analyzeRLFS function to test the enrichment of user-supplied ranges within R-loop-forming sequences. Cannot be skipped.

2. Predict Condition. Runs the predictCondition function to predict whether the user-supplied sample robustly maps R-loops or not. Cannot be skipped.

3. Feature enrichment test. Runs the featureEnrich function to test the enrichment of user-supplied ranges within R-loop-relevant genomic features. Skip with `skip="featureEnrich"`.

4. Correlation Analysis. Runs the corrAnalyze function to test the correlation of user-supplied R-loop signal with other samples in RLBase around "gold-standard" R-loop regions. Skip with `skip="corrAnalyze"`.

5. Gene annotation. Runs the geneAnnotation function to find the overlap of genes with the user-supplied ranges. Skip with `skip="geneAnnotation"`.

6. R-loop Region Analysis. Runs the rlRegionTest function to find the overlap of user-supplied ranges with consensus R-loop sites (RL-Regions). Skip with `skip="rlRegionTest"`.

### Value

An RLRanges object with results available (see rlresult).

### Examples

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

    # Run RLSeq
    # `useMask=FALSE`, `ntime=10`, and `skip=` for demonstration purposes here.
    rlr <- RLSeq(
        rlr, useMask = FALSE, ntimes = 10,
        skip=c('featureEnrich', 'corrAnalyze', 'geneAnnotation', 'rlRegionTest')
    )

[Package RLSeq version 1.0.0 Index]