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Different solutions are provided to compute a\nmeta-kernel, in a consensus way or in a way that best preserves\nthe original topology of the data. mixKernel also integrates\nkernel PCA to visualize similarities between samples in a non\nlinear space and from the multiple source point of view\n. A method to select (as\nwell as funtions to display) important variables is also\nprovided .", "License": "GPL (>= 2)", "BugReports": "https://forgemia.inra.fr/genotoul-bioinfo/mixKernel/-/issues", "VignetteBuilder": "knitr", "Encoding": "UTF-8", "NeedsCompilation": "no", "URL": "http://mixkernel.clementine.wf", "LazyData": "true", "Config/reticulate": "list( packages = list( list(package = \"autograd\",\npip = TRUE), list(package = \"numpy\", pip = TRUE), list(package\n= \"scipy\", pip = TRUE), list(package = \"sklearn\", pip = TRUE) )\n)", "RoxygenNote": "7.3.0", "Packaged": { "Date": "2026-10-04 11:58:55 UTC", "User": "root" }, "Author": "Nathalie Vialaneix [aut, cre], Celine Brouard [aut], Remi\nFlamary [aut], Julien Henry [aut], Jerome Mariette [aut]", "Config/pak/sysreqs": "zlib1g-dev", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2025-04-19 09:10:02 UTC", "RemoteUrl": "https://github.com/cran/mixKernel", "RemoteRef": "HEAD", "RemoteSha": 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