Package: mixOmics
Type: Package
Title: Omics Data Integration Project
Version: 5.1.2
Date: 2015-07-30
Depends: R (>= 2.10), MASS, lattice, ggplot2
Imports: igraph, rgl, pheatmap, ellipse
Author: Kim-Anh Le Cao,  Ignacio Gonzalez, Sebastien Dejean with key contributors Florian Rohart, Benoit Gautier
and contributions from Pierre Monget, Jeff Coquery, FangZou Yao, Benoit Liquet.
Maintainer: Kim-Anh Le Cao <k.lecao@uq.edu.au>
Description: We provide statistical integrative techniques and
variants to analyse highly dimensional data sets: regularized
Canonical Correlation Analysis ('rCCA') and sparse Partial Least Squares variants ('sPLS')
to unravel relationships between two heterogeneous data sets of size (n times p) and (n times q) where the p and
q variables are measured on the same samples or individuals n. These data may come from high throughput
technologies, such as 'omics' data (e.g. transcriptomics, metabolomics or proteomics
data) that require an integrative or joint analysis. However, 'mixOmics' can also be applied to any other
large data sets where p + q >> n. 'rCCA' is a regularized version of Canonical Correlation Analysis to deal with
the large number of variables. 'sPLS' allows variable selection in a one step procedure and two frameworks
are proposed: regression and canonical analysis. Numerous graphical outputs are provided to help interpreting
the results. Recent methodological developments include: sparse PLS-Discriminant Analysis ('sPLS-DA'), Independent
Principal Component Analysis ('IPCA'), multilevel analysis using variance decomposition of the data and integration
of multiple data sets with regularized Generalised Canonical Correlation Analysis ('rGCCA') and variants (sparse 'GCCA'). More details  can be found
on our website.
License: GPL (>= 2)
URL: http://www.mixOmics.org
BugReports: mixomics@math.univ-toulouse.fr or
https://bitbucket.org/klecao/package-mixomics/issues
Repository: CRAN
Date/Publication: 2015-08-29 09:26:37
Packaged: 2015-08-29 00:12:30 UTC; klecao
NeedsCompilation: no