getTilingElementwiseStats: Find active elements by sliding window

Description Usage Arguments Value Examples

View source: R/MAUDE.R

Description

Tests guides for activity by considering a sliding window across the tested region and including all guides within the window for the test.

Usage

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getTilingElementwiseStats(experiments, normNBSummaries, tails = "both",
  location = "pos", chr = "chr", window = 500, minGuides = 5,
  nonTargeting = "NT", ...)

Arguments

experiments

a data.frame containing the headers that demarcate the screen ID, which are all also present in normNBSummaries

normNBSummaries

data.frame of guide-level statistics as generated by findGuideHits()

tails

whether to test for increased expression ("upper"), decreased ("lower"), or both ("both"); (defaults to "both")

location

the name of the column in normNBSummaries containing the chromosomal location (defaults to "pos")

chr

the name of the column in normNBSummaries containing the chromosome name (defaults to "chr")

window

the window width in base pairs (defaults to 500)

minGuides

the minimum number of guides in a window required for a test (defaults to 5)

nonTargeting

the name in normNBSummaries containing a logical representing whether or not the guide is non-Targeting (i.e. a negative control guide). Defaults to "NT"

...

other parameters for getZScalesWithNTGuides

Value

a data.frame containing the statistics for all windows tested for activity

Examples

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allGuideLevelStats = findGuideHitsAllScreens(myScreens, allDataCounts, allBinStats)
elementLevelStatsTiling = getTilingElementwiseStats(myScreens, allGuideLevelStats, tails = "upper")

klarman-cell-observatory/MAUDE documentation built on Nov. 4, 2019, 3:53 p.m.