ProcessResults: Retrieve significant gene-metabolite pairs, based on adjusted...

In Mathelab/IntLIM: Integration of Omics Data Using Linear Modeling

Retrieve significant gene-metabolite pairs, based on adjusted p-values. For each gene-metabolite pair that is statistically significant, calculate the correlation within group1 (e.g. cancer) and the correlation within group2 (e.g. non-cancer). Users can then remove pairs with a difference in correlations between groups 1 and 2 less than a user-defined threshold.

Description

Retrieve significant gene-metabolite pairs, based on adjusted p-values. For each gene-metabolite pair that is statistically significant, calculate the correlation within group1 (e.g. cancer) and the correlation within group2 (e.g. non-cancer). Users can then remove pairs with a difference in correlations between groups 1 and 2 less than a user-defined threshold.

Usage

ProcessResults(inputResults, inputData, pvalcutoff = 0.05,
  diffcorr = 0.5, corrtype = "spearman", treecuts = 0)

Arguments

inputResults	IntLimResults object with model results (output of RunIntLim())
inputData	MultiDataSet object (output of ReadData()) with gene expression, metabolite abundances, and associated meta-data
pvalcutoff	cutoff of FDR-adjusted p-value for filtering (default 0.05)
diffcorr	cutoff of differences in correlations for filtering (default 0.5)
corrtype	spearman or pearson or other parameters allowed by cor() function (default spearman)
treecuts	user-selected number of clusters (of gene-metabolite pairs) to cut the tree into

Value

IntResults object with model results (now includes correlations)

Examples

## Not run: 
dir <- system.file("extdata", package="IntLIM", mustWork=TRUE)
csvfile <- file.path(dir, "NCItestinput.csv")
mydata <- ReadData(csvfile,metabid='id',geneid='id')
myres <- RunIntLim(mydata,stype="PBO_vs_Leukemia")
myres <- ProcessResults(myres,mydata,treecuts=2)

## End(Not run)

Mathelab/IntLIM documentation built on July 9, 2022, 5:10 p.m.