A Multi-Modal AI Copilot for Single-Cell Analysis with Instruction Following
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Updated
Jan 15, 2025 - Jupyter Notebook
A Multi-Modal AI Copilot for Single-Cell Analysis with Instruction Following
An iterative multi-LLM consensus framework for accurate cell type annotation in single-cell RNA-seq data
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.
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
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.
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.
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