scanpy
Category: life-sciences · License: BSD-3-Clause · Version: 1.6 · Includes scripts
Tags: single-cell RNA-seq, scRNA-seq, clustering, UMAP, bioinformatics
When to use it
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and converting R-friendly single-cell formats such as Seurat or SingleCellExperiment RDS files into h5ad for Scanpy. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.Example requests
Ask your agent in plain language, for example:- “How do I cluster my PBMC h5ad and get UMAP plots?”
- “I have a mouse cortex 10x dataset in ./filtered_feature_bc_matrix/ (3 samples, ‘sample’ column to be added). I need to run QC with mito filtering at a threshold that makes sense for brain tissue, flag doublets, normalize, integrate the samples, and find markers per cluster. Running sc.tl.louvain gives me a deprecation warning. What should I do?”
- “A collaborator sent me a Seurat object saved as pbmc_annotated.rds with cell type labels in the metadata. I want to explore it in Python and look at the clusters and make a dotplot of marker genes. How should I get started?”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole life-sciences category with /plugin install life-sciences@research-agent-skills.