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 <doi:10.1093/bioinformatics/btx682>. A method to select (as well as funtions to display) important variables is also provided <doi:10.1093/nargab/lqac014>.
Version: 0.9-2 Depends: R (≥ 3.5.0), mixOmics, ggplot2, reticulate (≥ 1.14) Imports: vegan, phyloseq, corrplot, psych, quadprog, LDRTools, Matrix, methods, markdown Suggests: rmarkdown, knitr Published: 2025-04-19 DOI: 10.32614/CRAN.package.mixKernel Author: Nathalie Vialaneix [aut, cre], Celine Brouard [aut], Remi Flamary [aut], Julien Henry [aut], Jerome Mariette [aut] Maintainer: Nathalie Vialaneix <nathalie.vialaneix at inrae.fr> BugReports: https://forgemia.inra.fr/genotoul-bioinfo/mixKernel/-/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: http://mixkernel.clementine.wf NeedsCompilation: no Citation: mixKernel citation info Materials: NEWS CRAN checks: mixKernel results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=mixKernel to link to this page.
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