ct.targetSetEnrichment {gCrisprTools} | R Documentation

## Test Whether a Specified Target Set is Enriched Within a Pooled Screen

### Description

This function takes in a `resultsDF` and a vector of `targets` (contained in the `geneID` column of `resultsDF`) and determines whether the specified targets are enriched within the set of all significantly altered targets. It does this by iteratively testing whether `targets` are more likely to be among the set of enriched or depleted targets at various significance thresholds using a hypergeometric test. Note that the returned Hypergeometric P-values are not corrected for multiple testing.

Returns a list detailing the `targets` used in the tests, and tables indicating the results of the hypergeometric test at various significance thresholds.

### Usage

    ct.targetSetEnrichment(summaryDF, targets, enrich = c(TRUE, FALSE),
      ignore = NULL)

### Arguments

`summaryDF` | A dataframe summarizing the results of the screen, returned by the function `ct.generateResults`.
`targets` | A character vector containing the names of the targets to be tested. Only targets contained in the `geneID` column of the provided `summaryDF` are considered.
`enrich` | Logical indicating whether to consider guides that are enriched (default) or depleted within the screen.
`ignore` | Optionally, a character vector containing elements of the `geneID` column of the provided `summaryDF` that should be ignored in the analysis (e.g., unassignable or nonfunctional targets, such as nontargeting controls). By default, this function omits targets with `geneSymbol` 'NoTarget'.

### Value

A named list containing the tested target set and tables detailing the hypergeometric test results using various P-value and Q-value thresholds.

### Author(s)

Russell Bainer

### Examples

    data(resultsDF)
    tar <-  sample(unique(resultsDF$geneID), 20)
    res <- ct.targetSetEnrichment(resultsDF, tar)

[Package gCrisprTools version 1.10.1 Index]