edgeR_tidiers

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Tidiers for edgeR's differential expression objects

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 /

Aliases
  • augment.DGEList
  • edgeR_tidiers
  • glance.DGEExact
  • tidy.DGEExact
  • tidy.DGEList
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))
}

Documentation reproduced from package biobroom, version 1.4.2, License: LGPL

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