parent
4252dace19
commit
a9fac3f4d3
|
@ -4606,3 +4606,39 @@ expression data to predict switches in regulatory activity between two
|
|||
conditions. A Bayesian network is used to model the regulatory structure and
|
||||
Markov-Chain-Monte-Carlo is applied to sample the activity states.")
|
||||
(license license:gpl2+)))
|
||||
|
||||
(define-public r-ropls
|
||||
(package
|
||||
(name "r-ropls")
|
||||
(version "1.16.0")
|
||||
(source
|
||||
(origin
|
||||
(method url-fetch)
|
||||
(uri (bioconductor-uri "ropls" version))
|
||||
(sha256
|
||||
(base32
|
||||
"099nv9dgmw3avkxv7cd27r16yj56svjlp5q4i389yp1n0r5zhyl2"))))
|
||||
(build-system r-build-system)
|
||||
(propagated-inputs `(("r-biobase" ,r-biobase)))
|
||||
(native-inputs
|
||||
`(("r-knitr" ,r-knitr))) ; for vignettes
|
||||
(home-page "https://dx.doi.org/10.1021/acs.jproteome.5b00354")
|
||||
(synopsis "Multivariate analysis and feature selection of omics data")
|
||||
(description
|
||||
"Latent variable modeling with @dfn{Principal Component Analysis} (PCA)
|
||||
and @dfn{Partial Least Squares} (PLS) are powerful methods for visualization,
|
||||
regression, classification, and feature selection of omics data where the
|
||||
number of variables exceeds the number of samples and with multicollinearity
|
||||
among variables. @dfn{Orthogonal Partial Least Squares} (OPLS) enables to
|
||||
separately model the variation correlated (predictive) to the factor of
|
||||
interest and the uncorrelated (orthogonal) variation. While performing
|
||||
similarly to PLS, OPLS facilitates interpretation.
|
||||
|
||||
This package provides imlementations of PCA, PLS, and OPLS for multivariate
|
||||
analysis and feature selection of omics data. In addition to scores, loadings
|
||||
and weights plots, the package provides metrics and graphics to determine the
|
||||
optimal number of components (e.g. with the R2 and Q2 coefficients), check the
|
||||
validity of the model by permutation testing, detect outliers, and perform
|
||||
feature selection (e.g. with Variable Importance in Projection or regression
|
||||
coefficients).")
|
||||
(license license:cecill)))
|
||||
|
|
Reference in New Issue