plotCompareP {variancePartition} | R Documentation

## Compare p-values from two analyses

### Description

Plot -log10 p-values from two analyses and color based on donor component from variancePartition analysis

### Usage

    plotCompareP(p1, p2, vpDonor, dupcorvalue, fraction = 0.2,
      xlabel = bquote(duplicateCorrelation ~ (-log[10] ~ p)),
      ylabel = bquote(dream ~ (-log[10] ~ p)))

### Arguments

`p1` | p-value from first analysis
`p2` | p-value from second analysis
`vpDonor` | donor component for each gene from variancePartition analysis
`dupcorvalue` | scalar donor component from duplicateCorrelation
`fraction` | fraction of highest/lowest values to use for best fit lines
`xlabel` | for x-axis
`ylabel` | label for y-axis

### Value

ggplot2 plot

### Examples

    # load library
    # library(variancePartition)

    # optional step to run analysis in parallel on multicore machines
    # Here, we used 4 threads
    library(doParallel)
    cl <- makeCluster(4)
    registerDoParallel(cl)
    # or by using the doSNOW package

    # load simulated data:
    # geneExpr: matrix of gene expression values
    # info: information/metadata about each sample
    data(varPartData)

    # Perform very simple analysis for demonstration

    # Analysis 1
    form <- ~ Batch
    L = getContrast( geneExpr, form, info, "Batch3")
    fit = dream( geneExpr, form, info, L)
    fitEB = eBayes( fit )
    res = topTable( fitEB, number=Inf )

    # Analysis 2
    form <- ~ Batch + (1|Tissue)
    L = getContrast( geneExpr, form, info, "Batch3")
    fit = dream( geneExpr, form, info, L)
    fitEB = eBayes( fit )
    res2 = topTable( fitEB, number=Inf )

    # Compare p-values
    plotCompareP( res$P.Value, res2$P.Value, runif(nrow(res)), .3 )

    # stop cluster
    stopCluster(cl)

[Package variancePartition version 1.10.4 Index]