edgeR v4: powerful differential analysis of sequencing data with expanded functionality and improved support for small counts and larger datasets

EdgeR is an R/Bioconductor software package for differential analyses of sequencing data in the form of read counts for genes or genomic features. Over the past 15 years, edgeR has been a popular choice for statistical analysis of data from sequencing technologies such as RNA-seq or ChIP-seq. edgeR pioneered the use of the negative binomial distribution to model read count data with replicates and the use of generalized linear models to analyze complex experimental designs. edgeR implements empirical Bayes moderation methods to allow reliable inference when the number of replicates is small. This article announces edgeR version 4, which includes new developments across a range of application areas.…

• CZ
  Chan Zuckerberg Initiative

  Awards: 2019-207283, 2021-237445
• DO
  Department of Health, State Government of Victoria
• SG
  State Government of Victoria
• MR
  Medical Research Council
• NH
  National Health and Medical Research Council

  Awards: 1176199, 1058892, 2025645