Package: mixOmics
Type: Package
Title: Omics Data Integration Project
Version: 3.0-1
Date: 2011-04-28
Depends: R (>= 2.10), igraph, rgl, lattice
Author: Sebastien Dejean, Ignacio Gonzalez, Kim-Anh Le Cao, Pierre
        Monget and Jeff Coquery
Maintainer: Kim-Anh Le Cao <k.lecao@uq.edu.au>
Description: The package supplies two efficients methodologies:
        regularized CCA and sparse PLS to unravel relationships between
        two heterogeneous data sets of size (nxp) and (nxq) 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 CCA 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.
License: GPL (>= 2)
Repository: CRAN
Date/Publication: 2011-03-18 07:32:20
Packaged: 2011-08-04 23:10:07 UTC; j.coquery
