voomWeightsFromCPM: Estimate voom precision weights directly From CPM values

In steveped/chipExtra: Additional functions for working with ChIP-Seq data

Estimate voom precision weights directly From CPM values

Description

Estimate voom precision weights directly From CPM values

Usage

voomWeightsFromCPM(
  cpm,
  design = NULL,
  w0 = NULL,
  lib.size = NULL,
  isLogCPM = TRUE,
  span = 0.5,
  ...
)

Arguments

cpm	Matrix of CPM or logCPM values
design	The design matrix for the experiment
w0	Initial vector of sample weights. Should be calculated using arrayWeights
lib.size	Initial library sizes. Must be provided as these are no estimable from CPM values
isLogCPM	logical(1). Indicates whether the data is log2 transformed already. Most commonly (e.g. if using the output of cqn) it will be,
span	Width of the smoothing window used for the lowess mean-variance trend. Expressed as a proportion between 0 and 1.
...	Passed to lmFit internally

Details

This function takes CPM or logCPM values and estimates the precision weights as would be done by providing counts directly to voom. Using this function enables the use of logCPM values which have been normalised using other methods such as Conditional-Quantile or Smooth-Quantile Normalisation.

The precision weights are returned as part of the EList output, and these are automatically passed to the function lmFit during model fitting. This will ensure that the mean-variance relationship is appropriate for the linear modelling steps as performed by limma.

Initial sample weights can be passed to the function, and should be calculated using arrayWeights called on the normalised logCPM values. The returned sample weights will be different to these, given that the function voomWithQualityWeights performs two rounds of estimation. The first is on the initial data, with the inappropriate mean-variance relationship, whilst the second round is after incorporation of the precision weights.

Value

An object of class EList as would be output by voom. Importantly, there will be no genes element, although this can be added later. Similarly, the returned targets element will only contain sample names and library sizes. This can be incorporated with any other metadata as required.

Plotting data is always returned, noting the the value sx has been offset by the library sizes and will be simple logCPM values. As such, the fitted Amean is also returned in this list element.

If initial sample weights were provided, modified weights will also be returned, as the initial function voomWithQualityWeights performs two rounds of estimation of sample weights. Here we would simply provide the initial weights a priori, with the second round performed within the function. Importantly, this second round of sample weight estimation uses the precision weights ensuring the correct mean-variance relationship is used for the final estimation of sample weights

Examples

bamFiles <- system.file("exdata", c("rep1.bam", "rep2.bam"), package="csaw")
wc <- csaw::windowCounts(bamFiles, filter=1)
cpm <- edgeR::cpm(wc, log = TRUE)
el <- voomWeightsFromCPM(cpm, lib.size = wc$totals)

steveped/chipExtra documentation built on May 2, 2024, 12:11 p.m.