Guide Scanpy workflows for single-cell analysis on AnnData objects.
npx skills add https://github.com/Ketomihine/my_skills --skill scanpy-complete
Please help me install this Agent Skill. Skill: scanpy-complete Source: https://github.com/Ketomihine/my_skills/tree/main/scanpy-complete Command: npx skills add https://github.com/Ketomihine/my_skills --skill scanpy-complete
This Skill provides a comprehensive, ready-to-use reference and workflow guide for Scanpy, enabling users to perform end-to-end single-cell analysis from preprocessing to visualization with minimal setup.
Install Scanpy and load a sample dataset, then run a minimal pipeline:
High-intent search queries and answers about installing and using this skill.
Run a complete single-cell analysis pipeline by filtering cells and genes, normalizing counts, applying log1p, computing PCA and neighbors, then generating UMAP and Leiden clusters on AnnData objects.
Yes, you can perform trajectory inference and differential expression analysis directly on AnnData objects using the provided workflow guidance and API references for single-cell data.
Scanpy supports spatial transcriptomics and multi-omics contexts by providing step-by-step pipelines and reference guides for data integration on AnnData objects.
The standard PBMC workflow involves loading the dataset, filtering cells and genes, normalizing total counts to 1e4, applying log1p, computing PCA, building neighbors, and running UMAP and Leiden clustering.
Preprocess raw single-cell RNA counts by filtering low-quality cells and genes, normalizing total counts to a target sum like 1e4, and applying log1p before computing PCA for dimensionality reduction.
Yes, the reference provides rich tutorials and code snippets to recreate single-cell analyses and produce high-quality, publication-ready figures for workflows like PBMC analysis.
AlterLab-IEUAnalyze RNA velocity to infer cell state transitions from spliced and unspliced counts.
zongtingweiPreprocess single-cell RNA-seq data into analysis-ready AnnData objects.
sanand0Analyze single-cell omics data using probabilistic deep generative models.
K-Dense-AIAnalyze single-cell RNA-seq splicing dynamics to infer cell state transitions.
