cepa: Apply CePa algorithm on a single pathway

In jokergoo/CePa: Centrality-Based Pathway Enrichment

Description

Apply CePa algorithm on a single pathway

Usage

cepa(dif = NULL, bk = NULL, mat = NULL, label = NULL, pc, pathway = NULL,
    id = NULL, cen = "equal.weight",
    cen.name = if(is.function(cen)) deparse(substitute(cen))
    else if(mode(cen) == "name") deparse(cen) else cen,
    nlevel = "tvalue_abs", plevel = "mean", iter = 1000)

Arguments

dif	differential gene list
bk	background gene list. If background gene list are not specified, use whole human genes
mat	expression matrix in which rows are genes and columns are samples
label	a sampleLabel object identify the design of the microarray experiment
pc	a pathway.catalogue object storing information of pathways
pathway	an igraphtest object or edge list
id	identify which pathway should be analysis in the pathway catalogue
cen	centrality measuments, it can ce a string, or function has been quote
cen.name	centrality measurement names. This argument should be set if the cen is a function.
nlevel	node level transformation, should be one of "tvalue", "tvalue_sq", "tvalue_abs". Also self-defined functions are allowed, see cepa.univariate for detail.
plevel	pathway level transformation, should be one of "max", "min", "median", "sum", "mean", "rank". Also, self-defined functions are allowed, see cepa.univariate for detail.
iter	number of simulations

Details

The function is a wrapper of cepa.ora and cepa.univariate. Selection of which function depends on the arguments specified.

If dif, bk, pc, pathway, id, cen, cen.name and iter are specified, the arguments are passed to cepa.ora. The centrality-extension of over-representation analysis (ORA) will be applied on the list of differential genes.

If mat, label, pc, pathway, id, cen, cen.name, nlevel, plevel and iter are specified, the arguments are passed to cepa.univariate. The centrality-extension of gene-set analysis (GSA) will be applied on the whole gene expressions.

This function is always called by cepa.all. But you can still use it if you want to analysis a single pathway under a specific centrality.

Value

A cepa class object

Author(s)

Zuguang Gu <[e-mail]>

See Also

cepa.all

Examples

## Not run: 

data(PID.db)

# ORA extension
data(gene.list)
# will spend about 20 min
res.ora = cepa(dif = gene.list$dif, bk = gene.list$bk, pc = PID.db$NCI, id = 2)

# GSA extension
# P53_symbol.gct and P53_cls can be downloaded from
# https://mcube.nju.edu.cn/jwang/lab/soft/cepa/
eset = read.gct("P53_symbol.gct")
label = read.cls("P53.cls", treatment="MUT", control="WT")
# will take about 45 min
res.gsa = cepa(mat = eset, label = label, pc = PID.db$NCI, id = 2)

## End(Not run)

jokergoo/CePa documentation built on July 2, 2021, 10:28 p.m.