Estimation of proportion of differentially expressed genes

Description

Estimation of proportion of differentially expressed genes. This estimation is based on a histogram of the p-values. More specifically, based on the horizontal line representing a uniform distribution based on the p value distribution between 0.5 and 1. This represents the hypothetical p value distribution arising just by chance. All genes with small p-values above this line reflect the expected number of differentially expressed genes not by chance.

Usage

propdegenescalculation(pValue)

Arguments

Author(s)

Willem Talloen and Tobias Verbeke

See Also

histPvalue

Examples

if (require(ALL)){
  data(ALL, package = "ALL")
  ALL <- addGeneInfo(ALL)
  ALL$BTtype <- as.factor(substr(ALL$BT,0,1))

  tTestResult <- tTest(ALL, "BTtype")
  histPvalue(tTestResult[,"p"], addLegend = TRUE)
  propDEgenesRes <- propDEgenes(tTestResult[,"p"])
}

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(a4Base)
Loading required package: grid
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Attaching package: 'BiocGenerics'

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    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

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  deprecated and future versions of Bioconductor may not have it
  available.  Users who want more current data are encouraged to look
  at the KEGGREST or reactome.db packages

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a4Base version 1.20.0

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/a4Base/propdegenescalculation.Rd_%03d_medium.png", width=480, height=480)
> ### Name: propdegenescalculation
> ### Title: Estimation of proportion of differentially expressed genes
> ### Aliases: propdegenescalculation
> 
> ### ** Examples
> 
> if (require(ALL)){
+   data(ALL, package = "ALL")
+   ALL <- addGeneInfo(ALL)
+   ALL$BTtype <- as.factor(substr(ALL$BT,0,1))
+ 
+   tTestResult <- tTest(ALL, "BTtype")
+   histPvalue(tTestResult[,"p"], addLegend = TRUE)
+   propDEgenesRes <- propDEgenes(tTestResult[,"p"])
+ }
Loading required package: ALL
Loading required package: hgu95av2.db
Loading required package: org.Hs.eg.db


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