edgeR_tidiers {biobroom} | R Documentation

## 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

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

    ## S3 method for class 'DGEList'
    tidy(x, addSamples = FALSE, ...)

    ## S3 method for class 'DGEList'
    augment(x, data = NULL, ...)

    ## S3 method for class 'DGEExact'
    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))
    }

[Package biobroom version 1.10.1 Index]