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mixKernel
View on CRAN: Click
here
Download and install mixKernel package within the R console
Install from CRAN:
install.packages("mixKernel")
Install from Github:
library("remotes")
install_github("cran/mixKernel") Install by package version:
library("remotes")
install_version("mixKernel", "0.9-2") Attach the package and use:
library("mixKernel")
Maintained by
Nathalie Vialaneix
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-18
Latest Update: 2025-04-19
Description:
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
. A method to select (as well as
funtions to display) important variables is also provided
.
How to cite:
Nathalie Vialaneix (2017). mixKernel: Omics Data Integration Using Kernel Methods. R package version 0.9-2, https://cran.r-project.org/web/packages/mixKernel. Accessed 29 Oct. 2026.
Previous versions and publish date:
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Other R packages that mixKernel depends,
imports, suggests or enhances
Complete documentation for mixKernel
Functions, R codes and Examples using
the mixKernel R package
Some associated functions: TARAoceans . center.scale . cim.kernel . combine.kernels . compute.kernel . kernel.pca . kernel.pca.permute . mixKernel.users.guide . plotVar.kernel.pca . select.features .
Some associated R codes: TARAoceans.R . center.scale.R . cim.kernel.R . combine.kernels.R . compute.kernel.R . kernel.pca.R . kernel.pca.permute.R . kernels.R . mixKernel-package.R . plot.kernel.pca.R . plotVar.kernel.pca.R . select.features.R . user.guide.R . zzz.R . Full mixKernel package functions and examples
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