biobroom (version 1.4.2)

edgeR_tidiers: Tidiers for edgeR's differential expression objects

Description

Tidy, augment and glance methods for turning edgeR objects into tidy data frames, where each row represents one observation and each column represents one column.

Usage

"tidy"(x, ...)
"tidy"(x, addSamples = FALSE, ...)
"augment"(x, data = NULL, ...)
"glance"(x, alpha = 0.05, p.adjust.method = "fdr", ...)

Arguments

x

DGEExact, DGEList object

...

extra arguments (not used)

addSamples

Merge information from samples. Default is FALSE.

data

merge data to augment. This is particularly useful when merging gene names or other per-gene information. Default is NULL.

alpha

Confidence level to test for significance

p.adjust.method

Method for adjusting p-values to determine significance; can be any in p.adjust.methods

Value

tidy defaults to tidying the counts in the dataset:

gene

gene ID

sample

sample ID

count

number of reads in this gene in this sample

If addSamples = TRUE, it also merges this with the sample information present in x$samples.augment returns per-gene information (DGEList only)glance returns one row with the columns (DGEExact only)

significant

number of significant genes using desired adjustment method and confidence level

comparison

The pair of groups compared by edgeR, delimited by /

Examples

if (require("edgeR")) {
    library(Biobase)
    data(hammer)
    hammer.counts <- exprs(hammer)[, 1:4]
    hammer.treatment <- phenoData(hammer)$protocol[1:4]

    y <- DGEList(counts=hammer.counts,group=hammer.treatment)
    y <- calcNormFactors(y)
    y <- estimateCommonDisp(y)
    y <- estimateTagwiseDisp(y)
    et <- exactTest(y)

    head(tidy(et))
    head(glance(et))
}