An iterative multi-LLM consensus framework for accurate cell type annotation in single-cell RNA-seq data

pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.

PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.

Graph-linked unified embedding for single-cell multi-omics data integration

A tool for semi-automatic cell type classification

DANCE: a deep learning library and benchmark platform for single-cell analysis

Single cell perturbation prediction

Rapids_singlecell: A GPU-accelerated tool for scRNA analysis. Offers seamless scverse compatibility for efficient single-cell data processing and analysis.

LIANA+: an all-in-one framework for cell-cell communication

Python package to perform enrichment analysis from omics data.

Perturbation Analysis in the scverse ecosystem.

RNA velocity estimation in Python

Infer copy number variation (CNV) from scRNA-seq data. Plays nicely with Scanpy.

Multi-omic single-cell optimal transport tools

Deep neural networks for predicting CpG methylation

scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks

Convert between AnnData and SingleCellExperiment

Tools for single-cell data processing

mgatk: mitochondrial genome analysis toolkit

A tool for semi-automatic cell type harmonization and integration