mixKernel: Omics Data Integration Using Kernel Methods
Version 0.1

Kernel-based methods are powerful methods for integrating heterogeneous types of data. mixKernel aims at providing methods to combine kernel for unsupervised exploratory analysis. Different solutions are provided to compute a meta-kernel, in a consensus way or in a way that best preserves the original topology of the data. mixKernel also integrates kernel PCA to visualize similarities between samples in a non linear space and from the multiple source point of view. Functions to assess and display important variables are also provided in the package.

Getting started

Package details

Authorc(person("Jerome", "Mariette", role = c("aut", "cre"), email="[email protected]"), person("Nathalie", "Villa-Vialaneix", role = c("aut"), email="[email protected]"))
Date of publication2017-05-18 03:50:57 UTC
MaintainerJerome Mariette <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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mixKernel documentation built on May 29, 2017, 3:35 p.m.