bio-workflows-scrnaseq-pipeline

What problem does it solve?

This workflow processes single-cell RNA-seq data from 10X Cell Ranger outputs to annotated cell types, automating QC, normalization, clustering, marker detection, and annotation to reduce manual effort and improve reproducibility.

Core Features & Use Cases

• End-to-end processing of 10X scRNA-seq data from raw counts to annotated cell types using Seurat (R) or Scanpy (Python).
• Integrated QC, doublet detection, normalization, HVG selection, dimensionality reduction, clustering, and marker-based annotation.
• Real-world use case: a lab processes multiple PBMC samples to identify cell-type composition and novel clusters across conditions.

Quick Start

Run this pipeline on your 10X Cell Ranger output to obtain annotated cell types.