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Scanpy

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davila7·vlatest·other·MIT

Scanpy analyzes single-cell RNA sequencing data to reveal cellular heterogeneity and gene expression patterns, aiding in biological discovery.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add davila7/claude-code-templates --skill scanpy -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

davila7

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Live repository

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About this skill

What it does

This skill provides access to scanpy, a powerful Python library used for analyzing single-cell gene expression data. It enables users to perform tasks such as dimensionality reduction, clustering, and visualization of high-dimensional datasets. The tool facilitates the exploration and understanding of cellular heterogeneity in biological samples.

When to use it

  • Analyzing single-cell RNA sequencing (scRNA-seq) data to identify cell types and states.
  • Performing quality control and preprocessing steps on scRNA-seq datasets, like filtering cells or genes.
  • Creating visualizations such as t-SNE plots or UMAP embeddings to explore cellular relationships.
  • Generating reports summarizing the results of single-cell analysis workflows.

Key capabilities

  • Data loading and preprocessing for single-cell data.
  • Dimensionality reduction techniques (e.g., PCA, t-SNE, UMAP).
  • Clustering algorithms to identify cell populations.
  • Visualization tools for exploring high-dimensional data.

Example prompts

  • "Run scanpy to cluster the provided single-cell RNA sequencing data."
  • "Generate a UMAP plot of this scRNA-seq dataset using scanpy."
  • "Perform PCA on this AnnData object and visualize the top principal components with scanpy."

Tips & gotchas

  • Requires familiarity with Python and basic bioinformatics concepts.
  • The skill's effectiveness depends on the quality and preprocessing of the input data.