batch-correction

Reference mapping for single-cell genomics

R package for the joint analysis of multiple single-cell RNA-seq datasets

🏃 The go-to single-cell Foundation Model

Bayesian mixed-effect model to test differences in cell type proportions from single-cell data, in R

Harmony framework for connecting scRNA-seq data from discrete time points

Calculation of Reference/Cluster Similarity Spectrum (RSS/CSS)

Digital Cell Sorter (DCS): single cell RNA-seq analysis toolkit. Documentation:

Clone of the Bioconductor repository for the batchelor package.

Detecting and dissecting anomalous anatomic regions in spatial transcriptomics with STANDS

MAAPster is a comprehensive tool to perform transcriptome analysis of human or mouse Affymetrix gene expression data

ConDo: confounded domain adaptation via generative modeling (TMLR, 2024)

A similarity-assisted variational autoencoder (saVAE) is a new method that adopts similarity information in the framework of the VAE.

Batch-harmonized ML framework for cross-cohort RNA biomarker discovery in pancreatic adenocarcinoma — bioRxiv 2025 (doi:10.1101/2025.11.14.688421)

Methylation array preprocessing.

Batch Effect Correction framework for metagenomic data

A comparison of data integration methods for single-cell RNA sequencing of cancer samples

An R tool to detect and correct batch-effects in gene-expression data (Microarray and bulk-RNAseq))

Fast, out-of-core single-cell analysis in Python for RNA, ATAC, protein, and multi-omic data, scaling to 100M+ cells. Mount remote datasets, work within a memory budget, and trace every result through built-in provenance.

A Python tool for performing downstream analysis on Single-Cell RNA-seq datasets

Batman: Batch effect correction via minimum weight MAtchiNg