BioMM

DOI: 10.18129/B9.bioc.BioMM  

BioMM: Biological-informed Multi-stage Machine learning framework for phenotype prediction using omics data

Bioconductor version: Release (3.17)

The identification of reproducible biological patterns from high-dimensional omics data is a key factor in understanding the biology of complex disease or traits. Incorporating prior biological knowledge into machine learning is an important step in advancing such research. We have proposed a biologically informed multi-stage machine learing framework termed BioMM specifically for phenotype prediction based on omics-scale data where we can evaluate different machine learning models with prior biological meta information.

Author: Junfang Chen and Emanuel Schwarz

Maintainer: Junfang Chen <junfang.chen33 at gmail.com>

Citation (from within R, enter citation("BioMM")):

Installation

To install this package, start R (version "4.3") and enter:

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

BiocManager::install("BioMM")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("BioMM")

 

HTML R Script BioMMtutorial
PDF   Reference Manual
Text   NEWS

Details

biocViews Classification, GO, Genetics, Pathways, Regression, Software
Version 1.15.0
In Bioconductor since BioC 3.9 (R-3.6) (4.5 years)
License GPL-3
Depends R (>= 3.6)
Imports stats, utils, grDevices, lattice, BiocParallel, glmnet, rms, precrec, nsprcomp, ranger, e1071, ggplot2, vioplot, CMplot, imager, topGO, xlsx
LinkingTo
Suggests BiocStyle, knitr, RUnit, BiocGenerics
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package BioMM_1.15.0.tar.gz
Windows Binary BioMM_1.15.0.zip
macOS Binary (x86_64)
macOS Binary (arm64) BioMM_1.15.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/BioMM
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/BioMM
Bioc Package Browser https://code.bioconductor.org/browse/BioMM/
Package Short Url https://bioconductor.org/packages/BioMM/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.17 Source Archive

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