Package: mixKernel
Type: Package
Title: Omics Data Integration Using Kernel Methods
Version: 0.8
Date: 2022-01-13
Depends: R (>= 3.5.0), mixOmics, ggplot2, reticulate (>= 1.14)
Imports: vegan, phyloseq, corrplot, psych, quadprog, LDRTools, Matrix, methods, markdown
Suggests: rmarkdown, knitr
Authors@R: c(person("Jerome", "Mariette", role = c("aut", "cre"), email="jerome.mariette@inrae.fr"),
             person("Celine", "Brouard", role = c("aut"), email="celine.brouard@inrae.fr"),
             person("Remi", "Flamary", role = c("aut"), email="remi.flamary@polytechnique.edu"),
             person("Nathalie", "Vialaneix", role = c("aut"), email="nathalie.vialaneix@inrae.fr"))
Maintainer: Jerome Mariette <jerome.mariette@inrae.fr>
Author: Jerome Mariette [aut, cre],
  Celine Brouard [aut],
  Remi Flamary [aut],
  Nathalie Vialaneix [aut]
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. Functions to assess and display
    important variables are also provided in the package. Ref: Jerome Mariette 
    and Nathalie Villa-Vialaneix (2018) <doi:10.1093/bioinformatics/btx682>.
License: GPL (>= 2)
Repository: CRAN
Packaged: 2022-01-13 15:38:01 UTC; nvialaneix
BugReports: https://forgemia.inra.fr/jerome.mariette/mixKernel/-/issues
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
URL: http://mixkernel.clementine.wf
LazyData: true
Config/reticulate:
  list(
    packages = list(
      list(package = "autograd", pip = TRUE),
      list(package = "numpy", pip = TRUE),
      list(package = "scipy", pip = TRUE),
      list(package = "sklearn", pip = TRUE)
    )
  )