rlfs_res: RLFS-Test Results

In Bishop-Laboratory/RLHub: An ExperimentHub package for accessing processed RLSuite data sets

Description

A list containing the results of R-loop-forming sequences analysis (RLSeq::analyzeRLFS()) and subsequent sample classification RLSeq::predictCondition() as "POS" (robustly maps R-loops) or "NEG" (poorly maps R-loops) with all samples in RLBase.

Usage

rlfs_res(quiet = FALSE)

Arguments

quiet

If TRUE, messages are suppressed. Default: FALSE.

Details

Source

R-loop-forming sequences were computationally predicted using QmRLFS-finder.py. The relevant section of the RLBase data prep protocol can be found here. Briefly, genomes available from UCSC were downloaded and analyzed with QmRLFS-finder.py on default settings. The resulting RLFS ranges were converted to .bed format.

RLFS analysis (via RLSeq::analyzeRLFS()) implements permutation testing to calculate the enrichment of a query R-loop mapping peakset within the relevant RLFS ranges. This analysis produces a p value and a Z-score distribution which are subsequently analyzed with RLSeq::predictCondition() (see models), yielding a quality prediction of "POS" (robustly maps R-loops) or "NEG" (poorly maps R-loops).

This approach was applied to every sample in RLBase (see rlbase_samples) to yield rlfs_res.

Structure

rlfs_res is a named list where each name is the ID of a sample in RLBase (see rlbase_samples).

Each list item is itself a list comprising the following:

• rlfsData - A list with this structure:

  • perTestResults

    • An object of the class permTestResultsList from regioneR.

    • Contains the results of permutation testing.

  • Z-scores

    • An object of the class localZScoreResultsList from regioneR.

    • Contains the results of local Z-score analysis +/-5kb around each RLFS.

• rlfsPred - A list with this structure:

  • Features

    • A tbl containing the raw and transformed values of features used in RLSeq::predictCondition().

  • Criteria

    • A list containing the results of analyzing the four criteria which must all be TRUE for a prediction of "POS":

      • PVal Significant - The permutation test p value is < .05

      • ZApex > 0 - The center of the Z-score distribution is > 0.

      • ZApex > ZEdge - The center of the Z-score distribution is > left edge and right edge.

      • Predicted 'Case' - The classifier predicted the "Case" label ("POS").

  • prediction

    • The final prediction: "POS" or "NEG"

Value

A named list.

Examples

rlfsRes <- rlfs_res()

Bishop-Laboratory/RLHub documentation built on Jan. 20, 2022, 3:47 p.m.