callPeaks: Call peaks using transformed, background corrected, and...

Description Usage Arguments Details Value Author(s) Examples

View source: R/callPeaks.R

Description

Use limma to calculate p-values for NADs

Usage

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callPeaks(
  se,
  backgroundCorrectedAssay = "bcRatio",
  normalization.method = "quantile",
  N = 100,
  cutoffAdjPvalue = 1e-04,
  countFilter = 1000,
  combineP.method = "minimump",
  smooth.method = "loess",
  lfc = log2(1.5),
  ...
)

Arguments

se

An object of RangedSummarizedExperiment with assays of raw counts, tranformed ratios, background corrected ratios, smoothed ratios and z-scores. It should be an element of output of smoothRatiosByChromosome

backgroundCorrectedAssay

character(1). Assays names for background corrected log2-transformed ratios, CPMRatios or OddRatios.

normalization.method

character(1) specifying the normalization method to be used. Choices are "none", "scale", "quantile" or "cyclicloess". See normalizeBetweenArrays for details.

N

numeric(1) or integer(1). The number of neighboring windows used for loess smoothing or the inverse of the critical frequencies of the low pass filter for butterworth filter. 1/N is a cutoff at 1/N-th of the Nyquist frequency. Default 100.

cutoffAdjPvalue

numeric(1). Cutoff adjust p-value.

countFilter

numeric(1). Cutoff value for mean of raw reads count in each window.

combineP.method

A method used to combine P-values. Default minimump

smooth.method

A method used to smooth the ratios. Choices are "loess", "none" and "butterworthfilter".

lfc

the minimum log2-fold-change that is considered scientifically meaningful

...

Parameter not used.

Details

By default, use the mean smoothed ratio for each peak region to calculate p-values

Value

An object of GRanges of peak list with metadata "AveSig", "P.Value", and "adj.P.Val", where "AveSig" means average signal such as average log2OddsRatio, log2CPMRatio or log2Ratio.

Author(s)

Jianhong Ou, Haibo Liu and Julie Zhu

Examples

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data(triplicate.count)
se <- triplicate.count
se <- log2se(se, transformation = "log2CPMRatio",
             nucleolusCols = c("N18.subsampled.srt-2.bam",
             "N18.subsampled.srt-3.bam",
             "N18.subsampled.srt.bam"),
             genomeCols = c("G18.subsampled.srt-2.bam",
             "G18.subsampled.srt-3.bam",
             "G18.subsampled.srt.bam"))
se<- smoothRatiosByChromosome(se, chr="chr18")
#add some variability to the data since the triplicate.count data was created using one sample only
assays(se[[1]])$bcRatio[,2] <- assays(se[[1]])$bcRatio[,2] + 0.3
assays(se[[1]])$bcRatio[,3] <- assays(se[[1]])$bcRatio[,3] - 0.3
peaks <- callPeaks(se[[1]],
                cutoffAdjPvalue=0.001, countFilter=10)

NADfinder documentation built on Nov. 8, 2020, 5:35 p.m.