README.md

In FocusPaka/MEB: A normalization-invariant minimum enclosing ball method to detect differentially expressed genes for RNA-seq data

MEB

R package for the SFMEB and scMEB methods.

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' [1]. The SFMEB method is extended to the scMEB [2] method that considering two or more potential types of cells or unknown labels scRNA-seq dataset DEGs identification.

Installation

You can install MEB from Bioconductor by running:

install.packages("BiocManager")
BiocManager::install("MEB")

You can also install the latest version of the package through devtools in R:

library("devtools")
devtools::install_github("FocusPaka/MEB")

User's Guide

Please refer to the vignetee for detailed function instructions.

Reference

1. Zhou, Y., Yang, B., Wang, J. et al. A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data. BMC Genomics 22, 479 (2021). https://doi.org/10.1186/s12864-021-07790-0
2. Zhu, J.D, Yang, Y.L. scMEB: A fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data. (2023, pending publication)

FocusPaka/MEB documentation built on April 23, 2023, 5:40 p.m.