Single-cell RNA-seq analysis project for learning purposes.

This toolkit provides Python code for preprocessing, quality control, clustering, and visualization of single-cell RNA sequencing data using Scanpy. Ideal for deep insights into cell populations and gene expression.

TeeSnee is an algorithm designed to take high-dimensional gene expression data and represent it in low-dimensional space.

This repository contains a robust, end-to-end pipeline for single-cell RNA sequencing (scRNA-seq) analysis using the Python library Scanpy. It demonstrates quality control, dimensionality reduction (PCA, UMAP), and cell type identification on 10x Genomics PBMC 3k data, resulting in 6 distinct cell clusters.

Interactive web application for analyzing scRNA-seq data using Scanpy

Single-cell RNA data analysis using R (Seurat) , Python (Scanpy), and Julia.

collab | DFC

A Python web application for automating RNA sequencing workflow management with interactive parameter collection, automated processing, and AI-powered chatbot support.

A complete single-cell RNA-seq analysis pipeline implemented in Python/Scanpy, following the sc-best-practices guide up to Section 10: Clustering.

Use the Scanpy read 10X dataset and LightGBM run the model

IGFBPL1 Retinal Microglia Project | Dong Feng Chen Lab collaboration | Schepens Eye Research Institute, Mass General Hospital, Harvard Medical School

Interactive diffusion map for Single-Cell Data Analysis

A complete single-cell RNA-seq analysis pipeline using Scanpy on 10x Genomics PBMC data, including clustering, UMAP visualization, and marker gene detection.

circrna single-cell bioinformatics genomics rna-seq cli python anndata scanpy nanopore

Advanced scanpy environment with R support (rpy2)

Snakemake workflow for a basic single-cell RNA-Seq analysis.

Single-cell RNA-seq analysis of mouse gastrulation using data from Argelaguet and Pijuan-Sala. The project includes preprocessing, SCVI-based dataset integration, differential gene expression analysis, and a no-code interface powered by Chatmol for natural language interaction with the pipeline.

Single-Cell RNA-seq Analysis of Bone Marrow Dataset Using Scanpy: This repository reproduces a complete scRNA-seq analysis pipeline using the Scanpy library on a modified bone marrow dataset (originally from CZI). The workflow includes preprocessing, normalization, clustering, marker-based annotation, and biological interpretation.

Lightweight, GPU-accelerated single-cell RNA-seq workflow for exploring the colorectal tumor microenvironment (CRC-TME) using Scanpy and scVI.