Description Usage Arguments Value See Also Examples
A binomial version of GSEA, unified as much as possible with nea.render
. Given the altered gene sets (AGS) and functional gene sets (FGS), calculates no. of members (genes/protein IDs) shared by each AGS-FGS pair as well as respective enrichment statistics. Returns matrices of size length(FGS) x length(AGS) (see "Value"). Each of these two parameters can be submitted as either a text file or as an R list which have been preloaded with import.gs
.
1 2 3 | gsea.render(AGS, FGS, Lowercase = 1, ags.gene.col = 2, ags.group.col = 3,
fgs.gene.col = 2, fgs.group.col = 3, echo = 1, Ntotal = 20000,
Parallelize = 1)
|
AGS |
Either a text file or a list of members of each AGS (see Details). Group IDs should be found in |
FGS |
Either a text file or a list of members of each FGS (see Details). Group IDs should be found in |
Lowercase |
render node and group IDs lower-case (Default:1, i.e. 'yes'). |
ags.gene.col |
number of the column containing AGS genes (only needed if AGS is submitted as a text file). |
ags.group.col |
number of the column containing group IDs (only needed if AGS is submitted as a text file). |
fgs.gene.col |
number of the column containing FGS genes (only needed if FGS is submitted as a text file). |
fgs.group.col |
number of the column containing group IDs (only needed if FGS is submitted as a text file). |
echo |
if messages about execution progress should appear. |
Ntotal |
The important parameter for precise calculation of the Fisher's statistics: how big is the whole gene universe? Defaults to 20000 but should be changed depending on the hypothesis and genome/proteome size. |
Parallelize |
The number of CPU cores to be used for calculating the gene set overlap. The other steps are sufficiently fast. The option is not supported in Windows. |
A list of entries estimate
, p
, q
, and n
, each of which is a matrix of size length(FGS)
x length(AGS)
. The two former ones contain respective output of fisher.test
: p.value
and estimate
, whereas q
is produced by p.adjust(p.value, method="BH")
and n
is the no. of shared members. Input to fisher.test
is matrix(c(<no. of shared members>, <no. of solely FGS members>, <no. of solely AGS members>, <no. of non-members>), nrow=2)
.
1 2 3 4 5 6 7 8 9 10 11 | ags.list <- samples2ags(fantom5.43samples, Ntop=20, method="topnorm")
data(can.sig.go)
fpath <- can.sig.go
fgs.list <- import.gs(fpath)
g1 <- gsea.render(AGS=ags.list, FGS=fgs.list, Lowercase = 1,
ags.gene.col = 2, ags.group.col = 3, fgs.gene.col = 2, fgs.group.col = 3,
echo=1, Ntotal = 20000, Parallelize=1)
hist(g1$estimate, breaks=100)
hist(g1$n, breaks=100)
hist(g1$p, breaks=100)
hist(g1$q, breaks=100)
|
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