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k-dense-ai avatar

Cellxgene Census

k-dense-ai/scientific-agent-skills
1.1k installs33k stars
Summary

This gives you programmatic access to 61+ million standardized single cells from the CELLxGENE Census, the largest curated single-cell atlas available. You can query expression data by cell type, tissue, or disease across thousands of datasets without downloading everything. The API handles both small queries that fit in memory with get_anndata() and massive out-of-core processing with iterative batching. It integrates cleanly with scanpy for standard analysis workflows and includes PyTorch dataloaders for training models on cell data. Worth noting that you should always filter for is_primary_data to avoid counting duplicate cells. If you're analyzing your own data rather than querying reference atlases, stick with scanpy or scvi-tools instead.

Install to Claude Code

npx -y skills add k-dense-ai/scientific-agent-skills --skill cellxgene-census --agent claude-code

Installs into .claude/skills of the current project.

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CodeScene MCP ServerCodeScene MCP Server
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Files
SKILL.md

Select a file.

Featured
CodeRabbit
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AI writes the code. CodeRabbit catches the slop.
Try For Free →
inference shell
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create and run specialised agents in minutes
build now →
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Plug Mailtrap into your AI workflow and let it handle the email.
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Install now →
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CodeScene MCP ServerCodeScene MCP Server
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Categories
AI & Agent Building
First SeenJun 3, 2026
View on GitHub

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k-dense-ai avatar
fluidsim

k-dense-ai/scientific-agent-skills

Plan, configure, inspect, restart, and analyze bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. Use for FluidSim solver selection, parameter review, FFT/MPI setup, output diagnostics, or restart compatibility.
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k-dense-ai/scientific-agent-skills

Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.
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sergiodxa avatar
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sergiodxa/agent-skills

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k-dense-ai avatar
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k-dense-ai/scientific-agent-skills

Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
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k-dense-ai avatar
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k-dense-ai/scientific-agent-skills

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dhdna-profiler

k-dense-ai/scientific-agent-skills

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