This is the development version of consICA; for the stable release version, see consICA.
consensus Independent Component AnalysisBioconductor version: Development (3.22)
consICA implements a data-driven deconvolution method â consensus independent component analysis (ICA) to decompose heterogeneous omics data and extract features suitable for patient diagnostics and prognostics. The method separates biologically relevant transcriptional signals from technical effects and provides information about the cellular composition and biological processes. The implementation of parallel computing in the package ensures efficient analysis of modern multicore systems.
Author: Petr V. Nazarov [aut, cre] ORCID: 0000-0003-3443-0298 , Tony Kaoma [aut] ORCID: 0000-0002-1269-4826 , Maryna Chepeleva [aut] ORCID: 0000-0003-3036-4916
Maintainer: Petr V. Nazarov <petr.nazarov at lih.lu>
Citation (from within R, entercitation("consICA")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("consICA")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("consICA")Follow Installation instructions to use this package in your R session.
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