ISA (data, flist = filterfun(function(x) IQR(x) > 0.5), uniqueEntrez = TRUE, thr.gene = seq(2, 4, by = 0.5), thr.cond = seq(1, 3, by = 0.5), no.seeds = 100)
genefilter
function without touching it. Supply NA
here if you don't
want to filter the expression set before running ISA on it.thr.gene
and thr.cond
will be used to run ISA.thr.gene
and thr.cond
will be used to run ISA.ISAModules-class
object.
isa2-package
manual page in the
isa2
package is also useful. The ISA
function performs the ISA algorithm on the supplied
expression data. This involves the following steps:
genefilter
package for
this. The default filtering function keeps the features that have
an IQR
of 0.5 or more. See
genefilter
for details on how to create
filtering functions. If NA
is given as the flist
argument, then no filtering is performed.
isa
function in the
isa2
package to perform the Iterative Signature
Algorithm. This itself performs the following steps:
isa.normalize
.
generate.seeds
.
isa.iterate
.
isa.unique
.
isa.filter.robust
in the isa2
package.
ISAModules
object from the ISA
results.
Ihmels J, Bergmann S, Barkai N: Defining transcription modules using large-scale gene expression data Bioinformatics 2004 Sep 1;20(13):1993-2003. Epub 2004 Mar 25.
eisa
package.
library(ALL)
data(ALL)
modules <- ISA(ALL, thr.gene=2.7, thr.cond=1.4)
modules
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