R Development Page
Contributed R Packages
Below is a list of all packages provided by project mixOmics.
Important note for package binaries: R-Forge provides these binaries only for the most recent version of R, but not for older versions. In order to successfully install the packages provided on R-Forge, you have to switch to the most recent version of R or, alternatively, install from the package sources (.tar.gz).
Packages
| mixOmics | Omics Data Integration Project | |||||||||
| 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. | ||||||||||
| Version: 3.0-1 | Last change: 2011-08-15 04:08:02+02 | Rev.: 95 | ||||||||||
Download:
 (.tar.gz) |
 (.zip) |
Build status: Current | Stable Release: Get mixOmics 6.3.2 from CRAN | ||||||||||
R install command:
install.packages("mixOmics", repos="http://R-Forge.R-project.org") | ||||||||||
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Build status codes
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