ballgown

Use when performing differential gene expression analysis on RNA-seq count data using limma-voom. Covers the full workflow: count filtering with filterByExpr, TMM normalization via edgeR calcNormFacto

2 shared topics • 2 shared operations

BEASTIE (Bayesian Estimation of Allele-Specific Transcription Integrating Expression) — statistical framework for detecting allele-specific expression (ASE) from RNA-seq data. Uses a Bayesian hierarch

2 shared topics • 1 shared operation

limma-voom — linear models for differential expression analysis of RNA-seq and microarray data. The voom transformation converts RNA-seq read counts to log-CPM with precision weights derived from the

2 shared topics • 1 shared operation

Use when working with muscat — the Bioconductor R package for multi-sample multi-condition differential state (DS) analysis of single-cell RNA-seq data. Performs pseudo-bulk aggregation (aggregateData

2 shared topics • 1 shared operation

PyDESeq2 — Python implementation of DESeq2 for differential gene expression analysis from bulk RNA-seq count data. Performs size factor normalization, genewise dispersion estimation, Wald tests with B

2 shared topics • 1 shared operation