corrAnalyze {RLSeq} | R Documentation

## Analyze Correlations

### Description

Finds the pairwise correlation in signal around gold-standard R-Loop sites between the query sample and the coverage tracks in the RLBase database. See details.

### Usage

    corrAnalyze(object, force = FALSE)

### Arguments

`object` | An RLRanges object.
`force` | Force `corrAnalyze` to run, even if on Windows. Default: FALSE.

### Details

Currently, this does not work on windows.

#### Method

The `corrAnalyze` function performs a correlation test that can be used to assess sample-sample similarity by calculating coverage signal (from genomic alignments) around “gold standard” R-loop sites (PMID: 33411340). The resulting correlation matrix is useful for determining how well a supplied sample correlates with previously-published datasets.

During the RLBase-data workflow, the signal for each R-loop mapping sample within “gold standard” R-loop sites was calculated see RLHub::gs_signal.

The `corrAnalyze` function loads RLHub::gs_signal and accepts an RLRanges object with a valid coverage slot. It then does the following:

1. The coverage is quantified within the “gold standard” sites and added as a column to the signal matrix from RLHub::gs_signal.

2. Then, the stats::cor function is used to calculate the Pearson correlation pairwise between all samples, yielding a correlation matrix

3. Finally, the correlation matrix is stashed in the in the `correlationMat` slot of the RLResults and returned.

### Value

An RLRanges object with correlation results included as a `matrix`. The correlation matrix is accessed via `rlresults(object, "correlationMat")`.

### Examples

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

    # corrAnalyze does not work on Windows OS
    if (.Platform$OS.type != "windows") {

        # run corrAnalyze
        rlr <- corrAnalyze(rlr)
    }

[Package RLSeq version 1.0.0 Index]