mixKernel (0.3)

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Omics Data Integration Using Kernel Methods.


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. Jerome Mariette and Nathalie Villa-Vialaneix (2017) .

Maintainer: Jerome Mariette
Author(s): Jerome Mariette [aut, cre], Nathalie Villa-Vialaneix [aut]

License: GPL (>= 2)

Uses: corrplot, ggplot2, LDRTools, Matrix, mixOmics, psych, quadprog, vegan

Released about 1 year ago.

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