Does this skill include quality control (QC) procedures?

Yes, it enforces critical QC rules such as filtering low-quality cells, removing mitochondrial noise, and performing proper normalization before analysis.

Does the skill support batch effect correction?

Yes, the skill provides guidance on integrating multiple datasets and using tools like Harmony to correct for technical batch effects.

What is the primary use of the Scanpy skill in Claude Code?

It provides Claude with the specialized patterns and best practices needed to analyze single-cell gene expression data using the Scanpy library and AnnData objects.

Can I use this skill for developmental biology research?

Absolutely. It contains advanced patterns for trajectory inference using PAGA and Diffusion Pseudotime to map how cells differentiate over time.

What data format does this skill prioritize?

The skill focuses on the AnnData format, which is the industry standard for storing high-dimensional genomic data along with its associated metadata.

Scanpy Single-Cell Analysis

Name: Scanpy Single-Cell Analysis
Author: tondevrel

bytondevrel

•

Data Science & ML

Analyzes high-dimensional single-cell gene expression data to identify cell types, states, and developmental trajectories.

This skill equips Claude with specialized knowledge for processing large-scale single-cell RNA sequencing (scRNA-seq) datasets using the Scanpy toolkit. It provides structured guidance through the entire bioinformatics pipeline, including loading AnnData objects, performing rigorous quality control, executing dimensionality reduction via PCA and UMAP, and performing advanced clustering. Whether you are identifying rare cell populations or reconstructing complex developmental lineages, this skill ensures implementation follows industry-standard best practices for normalization, batch correction, and differential expression analysis.

Key Features

01Automated cell clustering and rare population identification via Leiden

02Trajectory inference and lineage reconstruction using PAGA and DPT

03Comprehensive scRNA-seq workflows from raw counts to visualization

041 GitHub stars

05Advanced dimensionality reduction using PCA, UMAP, and t-SNE

06AnnData object management for integrated metadata and expression storage

Use Cases

01Comparing gene expression profiles across different experimental conditions or batches

02Characterizing cellular heterogeneity and identifying cell types in tissue samples

03Mapping developmental pathways and cell fate transitions in biological systems

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add tondevrel/scientific-agent-skills scanpy

For use in Claude.ai and ChatGPT

Download Skill