plotAllTwoSampleDistributionCounts {pathVar} | R Documentation

## Compares the distribution of genes in clusters for every gene in your data set for two groups of samples that you define and plot the counts.

### Description

Compares the distribution of genes for every gene in your data set for two groups of samples that you define and plot the counts of each gene.

### Usage

    plotAllTwoSampleDistributionCounts(dat,pvalue_results,perc=c(1/3,2/3),pvalue,plotName)

### Arguments

`dat` | `matrix` with the genes on the rows and the samples on the columns.
`pvalue_results` | output of `pathVarTwoSamples` step.
`perc` | numeric `vector` of probabilities with values between 0 and 1. Used to put genes into clusters
`pvalue` | the significance level to test.
`plotName` | a string specifying the file name of the output plot. Default value is NULL which prints, but does not save the graph in a pdf.

### Details

This function looks at the gene counts in each category of 2 groups previously defined in the `pathVarTwoSamples` step and compare the 2 samples to each other with all the genes from the data set. Then it plots the counts for each group.

### Value

A plot of results returned.

### Author(s)

Laurence de Torrente, Samuel Zimmerman, Jessica Mar

### Examples

    # we run the 2 samples analysis on the first 10 pathways from kegg
    pways.kegg.10pways <- lapply(pways.kegg, function(x) x[1:10])
    results_2samples=pathVarTwoSamplesDisc(bock,pways.kegg.10pways,groups=as.factor(c(rep(1,10),rep(2,10))),perc=c(1/3,2/3),test="exact",varStat="sd")
    plotAllTwoSampleDistributionCounts(bock, results_2samples, perc=c(1/3,2/3), pvalue=0.05, "bock.group1.group2.pdf")

[Package pathVar version 1.12.0 Index]