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

A Multi-Modal AI Copilot for Single-Cell Analysis with Instruction Following

Unbiased single-cell transcriptomic data cell type identification

The official implementation for "SANGO".

OTMODE: An Optimal Transport-Based Framework for Differential Feature Identification in Single-Cell Multi-Omics

cRegulon is an optimization model to identify combinatorial regulon from single cell expression and chromatin accessibility data.

A curated list of tools and methods for scRNA-seq cell type annotation

cRegulon is an optimization model to identify combinatorial regulon from single cell expression and chromatin accessibility data.

graph-based cell type annotation toolkit for single-cell RNA-seq, ATAC-seq, and spatial omics

Hierarchical and high-resolution cell-type identification for single-cell RNA-seq data based on ScType.

Source code for the study "Marker Gene Identification Algorithm of Precision Clustering for Single-Cell Sequencing," conducted at the Institute of Biomedical Informatics, National Yang Ming Chiao Tung University (NYCU BMI) by Zhe-Yuan Li, published in January 2025.

scLearn：Learning for single cell assignment

This repository contains an analysis pipeline for processing and visualizing single-cell RNA sequencing (scRNA-seq) data using the Seurat package in R. The dataset used is the Peripheral Blood Mononuclear Cells (PBMC) 3K dataset from 10X Genomics.