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

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 various prior biological meta information.

Getting started

Package details

AuthorJunfang Chen and Emanuel Schwarz
Bioconductor views Classification GO Genetics Pathways Regression Software
MaintainerJunfang Chen <[email protected]>
LicenseGPL-3
Version0.99.12
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("transbioZI/BioMM")
transbioZI/BioMM documentation built on April 10, 2019, 7:01 p.m.