MEB

DOI: 10.18129/B9.bioc.MEB    

A Minimum Enclosing Ball (MEB) method to detect differential expression genes for RNA-seq data

Bioconductor version: Release (3.10)

Identifying differential expression genes between the same or different species is an urgent demand for biological research. In most of cases, normalization is the first step to solve this problem, then by employing the hypothesis testing, we could detect statistically significant genes. With the development of machine learning, it gives us a new perspective on discrimination between differential expression (DE) and non-differential expression (non-DE) genes. Provided a set of training data, the procedure of distinguishing genes could be simplified as a classification problem. However, in reality, it is hard for us to get the information from both DE and non-DE genes. To solve this problem, we try to identify differential cases only in the domain of non-DE genes, and transform the problem to an outlier detection in machine learning. Given that non-DE genes have some similarities in features, we build a Minimum Enclosing Ball (MEB) to cover those non-DE genes in feature space, then those DE genes, which are enormously different from non-DE genes, being regarded as outliers and rejected outside the ball. Compared with existing methods, it is no need for the MEB method to normalize data in advance. Besides, the MEB method could be easily applied to the same or different species data and without changing too much.

Author: Yan Zhou, Jiadi Zhu

Maintainer: Jiadi Zhu <2160090406 at email.szu.edu.cn>, Yan Zhou <zhouy1016 at szu.edu.cn>

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

Installation

To install this package, start R (version "3.6") and enter:

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

BiocManager::install("MEB")

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("MEB")

 

HTML R Script MEB Tutorial
PDF   Reference Manual
Text   NEWS

Details

biocViews Classification, DifferentialExpression, GeneExpression, Normalization, Software
Version 1.0.0
In Bioconductor since BioC 3.10 (R-3.6) (< 6 months)
License GPL-2
Depends R (>= 3.6.0)
Imports e1071, SummarizedExperiment
LinkingTo
Suggests knitr, rmarkdown
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 MEB_1.0.0.tar.gz
Windows Binary MEB_1.0.0.zip
Mac OS X 10.11 (El Capitan) MEB_1.0.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/MEB
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MEB
Package Short Url https://bioconductor.org/packages/MEB/
Package Downloads Report Download Stats

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: