cepa | R Documentation |
Apply CePa algorithm on a single pathway
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)
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 |
pc |
a |
pathway |
an |
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 |
nlevel |
node level transformation, should be one of "tvalue", "tvalue_sq", "tvalue_abs". Also self-defined functions are allowed, see |
plevel |
pathway level transformation, should be one of "max", "min", "median", "sum", "mean", "rank". Also, self-defined functions are allowed, see |
iter |
number of simulations |
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.
A cepa
class object
Zuguang Gu <z.gu@dkfz.de>
cepa.all
## 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$NCI, id = 2)
# GSA extension
# P53_symbol.gct and P53_cls can be downloaded from
# http://mcube.nju.edu.cn/jwang/lab/soft/cepa/
eset = read.gct("P53_symbol.gct")
label = read.cls("P53.cls", treatment="MUT", control="WT")
# will take about 45 min
res.gsa = cepa(mat = eset, label = label, pc = PID.db$NCI, id = 2)
## End(Not run)
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