Tidying methods for DESeq2 DESeqDataSet objects

Description

This reshapes a DESeq2 expressionset object into a tidy format. If the dataset contains hypothesis test results (p-values and estimates), this summarizes one row per gene per possible contrast.

Usage

## S3 method for class 'DESeqDataSet'
tidy(x, colData = FALSE, intercept = FALSE, ...)

## S3 method for class 'DESeqResults'
tidy(x, ...)

Arguments

Details

colDat=TRUE adds covariates from colData to the data frame.

Value

If the dataset contains results (p-values and log2 fold changes), the result is a data frame with the columns

If the dataset does not contain results (DESeq has not been run on it), tidy defaults to tidying the counts in the dataset:

If colData = TRUE, it also merges this with the columns present in colData(x).

Examples

# From DESeq2 documentation

if (require("DESeq2")) {
    dds <- makeExampleDESeqDataSet(betaSD = 1)

    tidy(dds)
    # With design included
    tidy(dds, colData=TRUE)

    # add a noise confounding effect
    colData(dds)$noise <- rnorm(nrow(colData(dds)))
    design(dds) <- (~ condition + noise)

    # perform differential expression tests
    ddsres <- DESeq(dds, test = "Wald")
    # now results are per-gene, per-term
    tidied <- tidy(ddsres)
    tidied

    if (require("ggplot2")) {
        ggplot(tidied, aes(p.value)) + geom_histogram(binwidth = .05) +
            facet_wrap(~ term, scale = "free_y")
    }
}

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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(biobroom)
Loading required package: broom
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/biobroom/DESeq2_tidiers.Rd_%03d_medium.png", width=480, height=480)
> ### Name: DESeq2_tidiers
> ### Title: Tidying methods for DESeq2 DESeqDataSet objects
> ### Aliases: DESeq2_tidiers tidy.DESeqDataSet tidy.DESeqResults
> 
> ### ** Examples
> 
> 
> # From DESeq2 documentation
> 
> if (require("DESeq2")) {
+     dds <- makeExampleDESeqDataSet(betaSD = 1)
+ 
+     tidy(dds)
+     # With design included
+     tidy(dds, colData=TRUE)
+ 
+     # add a noise confounding effect
+     colData(dds)$noise <- rnorm(nrow(colData(dds)))
+     design(dds) <- (~ condition + noise)
+ 
+     # perform differential expression tests
+     ddsres <- DESeq(dds, test = "Wald")
+     # now results are per-gene, per-term
+     tidied <- tidy(ddsres)
+     tidied
+ 
+     if (require("ggplot2")) {
+         ggplot(tidied, aes(p.value)) + geom_histogram(binwidth = .05) +
+             facet_wrap(~ term, scale = "free_y")
+     }
+ }
Loading required package: DESeq2
Loading required package: S4Vectors
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit


Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: Biobase
Welcome to Bioconductor

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

estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
Loading required package: ggplot2
Warning message:
Removed 4 rows containing non-finite values (stat_bin). 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>