enrichment: Enrichment analysis for codon usage (CU) data.

Description Usage Arguments Value Examples

Description

Performs enrichment analysis, given a contongency table of codon counts. p values are calculated by binomial test, adjustment for multiple testing can be performed by any of the p.adjust.methods.

Usage

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enrichment(x, pvalueCutoff = numeric(), pAdjustMethod = "BH",
  padjCutoff = numeric())

## S4 method for signature 'crossTab'
enrichment(x, pvalueCutoff = numeric(),
  pAdjustMethod = "BH", padjCutoff = numeric())

Arguments

x

A crossTab object

pvalueCutoff

Numeric, discard categories with p value below this threshold. By default, no threshold is set (numeric()).

pAdjustMethod

Character, one of the p.adjust.methods.

padjCutoff

Numeric, discard categories with adjusted p value below this threshold. By default, no threshold is set (numeric()).

Value

An AnnotatedDataFrame object, or a list of those; data in each object has category values in rows, and the following columns:

Examples

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require(Biobase)

# create contingency table
s <- getKO(HD59)
v <- as.numeric(MELP(HD59, ribosomal = TRUE))
ct <- crossTab(s, v)

# enrichment analysis
enr <- enrichment(ct)
enr # for help, see `?Biobase::AnnotatedDataFrame`
head(pData(enr))

enr <- enrichment(ct, pAdjustMethod = "holm")
head(pData(enr))

enr <- enrichment(ct, pvalueCutoff = 0.05)
head(pData(enr))

enr <- enrichment(ct, padjCutoff = 0.05)
head(pData(enr))

BioinfoHR/coRdon documentation built on May 6, 2019, 8:35 p.m.