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PrInCE

Predicting Interactomes from Co-Elution

Bioconductor version: 3.23 · Package version: 1.28.0

Other Bioconductor versions

devel is the development version; release is the current stable one.

3.24 (devel), 3.23 (release)

PrInCE (Predicting Interactomes from Co-Elution) uses a naive Bayes classifier trained on dataset-derived features to recover protein-protein interactions from co-elution chromatogram profiles. This package contains the R implementation of PrInCE.

DOI: 10.18129/B9.bioc.PrInCE

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("PrInCE")

Details

MaintainerMichael Skinnider <michael.skinnider@msl.ubc.ca>
AuthorMichael Skinnider [aut, trl, cre], R. Greg Stacey [ctb], Nichollas Scott [ctb], Anders Kristensen [ctb], Leonard Foster [aut, led]
LicenseGPL-3 + file LICENSE
Bug Reportshttps://github.com/fosterlab/PrInCE/issues
Source branchRELEASE_3_23
Build report Bioconductor build system, r-universe
biocViewsNetworkInference, Proteomics, Software, SystemsBiology
Package Short Url https://bioconductor.org/packages/PrInCE/

Citation

From within R, enter citation("PrInCE"):

Michael Skinnider, Leonard Foster. PrInCE: Predicting Interactomes from Co-Elution. doi:10.18129/B9.bioc.PrInCE, R package version 1.28.0, https://bioconductor.org/packages/PrInCE.

Generated from the package metadata; it may differ from the package's own citation.

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagePrInCE_1.28.0.tar.gz
Windows binary (x86_64)PrInCE_1.28.0.zip
macOS binary (arm64)PrInCE_1.28.0.tgz
macOS binary (x86_64)PrInCE_1.28.0.tgz
Dependencies

Depends: R (>= 3.6.0)

Imports: purrr (>= 0.2.4), dplyr (>= 0.7.4), tidyr (>= 0.8.99), forecast (>= 8.2), progress (>= 1.1.2), Hmisc (>= 4.0), naivebayes (>= 0.9.1), robustbase (>= 0.92-7), ranger (>= 0.8.0), LiblineaR (>= 2.10-8), speedglm (>= 0.3-2), tester (>= 0.1.7), magrittr (>= 1.5), Biobase (>= 2.40.0), MSnbase (>= 2.8.3), stats, utils, methods, Rdpack (>= 0.7)

Suggests: BiocStyle, knitr, rmarkdown