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Single cell

Skill BioTender-max/awesome-bio-agent-skills/skills/pantheon/single_cell

A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.

Install
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill single_cell

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Core skills for single-cell RNA-seq analysis: quality control, cell type annotation, and trajectory inference. These are high-priority actionable workflows — load them first for common single-cell tasks.

SKILL.md

1.6 KB, 266 tokens by cl100k_base, as published. Nobody here has run it

Core Single-Cell Analysis Skills

High-priority, actionable workflows for the most common single-cell analysis tasks. For deeper background and alternative methods, see the supplementary SC Best Practices reference.

Available Skills

Quality Control

Standard QC workflow: filtering low-quality cells, doublet detection, normalization, and QC metric visualization.

Skill file: quality_control.md

When to use:

  • Starting analysis of a new single-cell dataset
  • Need to filter low-quality cells
  • Assessing data quality metrics

Cell Type Annotation

Marker-based and reference-based approaches for assigning cell type labels.

Skill file: cell_type_annotation.md

When to use:

  • After clustering, need to assign cell type labels
  • Using marker genes for annotation
  • Using reference-based methods (CellTypist, scArches)

Trajectory Inference

Pseudotime analysis and trajectory inference for cell differentiation, lineage tracing, and RNA velocity.

Skill file: trajectory_inference.md

When to use:

  • Studying cell differentiation paths
  • Neurogenesis or developmental trajectory analysis
  • RNA velocity for directional dynamics

What ships with it: 3 files

37.3 KB alongside SKILL.md

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