BioMM
This package is for version 3.16 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see BioMM.
BioMM: Biological-informed Multi-stage Machine learning framework for phenotype prediction using omics data
Bioconductor version: 3.16
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("BioMM")
):
Installation
To install this package, start R (version "4.2") 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")
BioMMtutorial | HTML | R Script |
Reference Manual | ||
NEWS | Text |
Details
biocViews | Classification, GO, Genetics, Pathways, Regression, Software |
Version | 1.14.0 |
In Bioconductor since | BioC 3.9 (R-3.6) (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 |
System Requirements | |
URL |
See More
Suggests | BiocStyle, knitr, RUnit, BiocGenerics |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | BioMM_1.14.0.tar.gz |
Windows Binary | BioMM_1.14.0.zip |
macOS Binary (x86_64) | BioMM_1.14.0.tgz |
macOS Binary (arm64) | BioMM_1.14.0.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 3.16 | Source Archive |