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
|
conditions. A Bayesian network is used to model the regulatory structure and
|
||||||
Markov-Chain-Monte-Carlo is applied to sample the activity states.")
|
Markov-Chain-Monte-Carlo is applied to sample the activity states.")
|
||||||
(license license:gpl2+)))
|
(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)))
|
||||||
|
|
Loading…
Reference in New Issue