runIHW: Function runIHW

In jrthompson54/DGE.Tools2: A function library to facilitate Differential Gene Expression Analysis

Description

This is a wrapper around the independent hypothesis weighting package that takes a list of topTable dataframes and applies Independent Hypothesis Weighting (IHW) to each topTable dataframe in the list.

Usage

runIHW(contrastList, alpha = 0.1, FDRthreshold = 0.1, ...)

Arguments

contrastList	A list of topTable dataframes.
alpha	The alpha value is the FDR level you wish to interogate (range 0-1; default = 0.1)
...	other arguments are passed directly to the ihw function (see ?ihw).

Details

IHW is a method developed by N. Ignatiadis (http://dx.doi.org/10.1101/034330) to weight FDR values based on a covariate (AveExpr in this case).

The IHW FDR values are added as additional columns to the topTable dataframes.

Note that it is impractical to run IHW on a list of genes less than ~5000 because operationally, it breaks the data into bins of 1500 genes for the analysis if bins = 1, IHW converges on the BH FDR value and there's no point. So we run IHW on the complete set of detected genes from topTable results (not topTreat).

Value

A list of lists. The first element is the original contrastList with additional IHW columns added to each dataframe. The TopTable dataframes will contain additional columns added by the ihw analysis and prefixed with "ihw." The second list element is the IHW result dataframe.

Author(s)

John Thompson, [e-mail]

Examples

IHWresults <- runIHW(MyContrastList)
MyContrastList <- IHWresults[[1]]
IHWdf <- IHWresults[[2]]

jrthompson54/DGE.Tools2 documentation built on May 12, 2021, 8:47 p.m.