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scrna-seq-pipeline

Process 10X Genomics single-cell RNA-seq data into annotated AnnData objects.

13|5|Updated May 4, 2026
Search Tags:#bioinformatics#genomics#single-cell#anndata#scanpy#scrna-seq
One-click install
npx skills add https://github.com/awslabs/hcls-agent-skills --skill scrna-seq-pipeline
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scrna-seq-pipeline
Source: https://github.com/awslabs/hcls-agent-skills/tree/main/skills/scrna-seq-pipeline
Command: npx skills add https://github.com/awslabs/hcls-agent-skills --skill scrna-seq-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scanpy, anndata, leidenalg, python-igraph, harmonypy, scvi-tools.

What problem does it solve?

This skill automates the complex, multi-step bioinformatics workflow required to process raw single-cell RNA-seq data into actionable biological insights, reducing the risk of manual errors and reproducibility issues.

Core Features & Use Cases

  • Standardized Pipeline: Executes a complete Scanpy-based workflow including QC, normalization, dimensionality reduction, and clustering.
  • Advanced Integration: Supports batch effect correction using Harmony or scVI to integrate multi-sample datasets.
  • Use Case: A researcher can take raw 10X Genomics output and generate a fully annotated AnnData object with UMAP embeddings and marker gene lists in a single, reproducible execution.

Quick Start

Use the scrna-seq-pipeline skill to process the filtered feature matrix from the current directory and generate a result.h5ad file.

Frequently Asked Questions about scrna-seq-pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run an end-to-end single-cell RNA-seq analysis on raw 10X Genomics data?▼

Single-cell RNA-seq analysis can be executed end-to-end by processing filtered feature matrices to generate annotated AnnData objects with UMAP embeddings and marker gene lists in a single reproducible workflow.

How do I perform batch effect correction for multi-sample single-cell RNA-seq datasets?▼

Batch effect correction for multi-sample single-cell RNA-seq datasets is performed using Harmony or scVI integration to merge data variations and generate unified AnnData objects for downstream analysis.

What is the standard Scanpy pipeline for single-cell RNA-seq clustering and normalization?▼

The standard Scanpy pipeline for single-cell RNA-seq clustering automates quality control, normalization, dimensionality reduction, and clustering to transform raw genomic data into actionable biological insights.

Do I need leidenalg and python-igraph installed to run single-cell RNA-seq clustering?▼

Yes, leidenalg and python-igraph are required dependencies to execute the full analytical suite for single-cell RNA-seq clustering alongside scanpy, anndata, harmonypy, and scvi-tools.

Can I use this workflow to generate an h5ad file from a filtered feature matrix?▼

Yes, you can process the filtered feature matrix from your current directory using this workflow to automatically generate a fully annotated result.h5ad file containing your single-cell RNA-seq analysis.

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