MEB

A normalization-invariant minimum enclosing ball method to detect differentially expressed genes for RNA-seq and scRNA-seq data


Bioconductor version: Release (3.19)

This package provides a method to identify differential expression genes in the same or different species. Given that non-DE genes have some similarities in features, a scaling-free minimum enclosing ball (SFMEB) model is built 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. The method on this package is described in the article 'A minimum enclosing ball method to detect differential expression genes for RNA-seq data'. The SFMEB method is extended to the scMEB method that considering two or more potential types of cells or unknown labels scRNA-seq dataset DEGs identification.

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 "4.4") and enter:


if (!require("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")
MEB Tutorial HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Classification, DifferentialExpression, GeneExpression, Normalization, Sequencing, Software
Version 1.18.0
In Bioconductor since BioC 3.10 (R-3.6) (5 years)
License GPL-2
Depends R (>= 3.6.0)
Imports e1071, edgeR, scater, stats, wrswoR, SummarizedExperiment, SingleCellExperiment
System Requirements
URL
See More
Suggests knitr, rmarkdown, BiocStyle
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 MEB_1.18.0.tar.gz
Windows Binary (x86_64) MEB_1.18.0.zip
macOS Binary (x86_64) MEB_1.18.0.tgz
macOS Binary (arm64) MEB_1.18.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/MEB
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MEB
Bioc Package Browser https://code.bioconductor.org/browse/MEB/
Package Short Url https://bioconductor.org/packages/MEB/
Package Downloads Report Download Stats