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cytetype-annotation

Annotate cell types in clustered Seurat objects using the CyteTypeR API.

Updated May 28, 2026
Search Tags:#bioinformatics#r#single-cell#seurat#scrna-seq#cell type annotation#cytetyper
One-click install
npx skills add https://github.com/cpanse/skills --skill cytetype-annotation-cpanse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cytetype-annotation
Source: https://github.com/cpanse/skills/tree/main/single-cell-ml/skills/cytetype-annotation
Command: npx skills add https://github.com/cpanse/skills --skill cytetype-annotation-cpanse

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Manually assigning cell types to single-cell RNA-seq clusters is slow, subjective, and hard to reproduce across samples. This Skill automates cluster-level cell type annotation by submitting marker genes from Seurat objects to the Nygen Analytics CyteType API and mapping the returned ontology-based annotations back to individual cells. ## Core Features & Use Cases - Automated Annotation Workflow: Prepares Seurat objects and marker genes with PrepareCyteTypeR, submits jobs to the CyteType API, and retrieves cluster-level annotations with ontology terms, granular subtypes, and supporting/conflicting markers. - FGCZ Infrastructure Integration: Provides SBATCH batch scripts, qs2 object storage, gstore transfer commands, and R Markdown report templates following FGCZ standards (polychrome colors, 300 DPI output). - Quality Inspection & Visualization: Generates UMAP plots, cell type distribution bar charts, and annotation tables with justifications for review. - Use Case: A bioinformatician has a clustered PBMC Seurat object with markers from FindAllMarkers and needs reproducible, ontology-based cell type labels across multiple donor samples for a project report. ## Quick Start Ask the agent to run CyteTypeR cell type annotation on your clustered Seurat object with its FindAllMarkers results and produce UMAP visualizations of the annotated cell types.

Frequently Asked Questions about cytetype-annotation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I annotate cell types in a Seurat object automatically?▼

Run FindAllMarkers on your clustered Seurat object, filter for positive markers with avg_log2FC > 1, then use PrepareCyteTypeR to package the data and CyteTypeR to submit it to the Nygen Analytics API. Results return as cluster-level annotations mapped back to cells.

What is CyteTypeR and how does it annotate scRNA-seq data?▼

CyteTypeR is an R package that submits cluster marker genes to the Nygen Analytics CyteType API, which uses large language models to assign cell type labels. It returns ontology terms, granular subtypes, justifications, and supporting or conflicting markers per cluster.

Can I use CyteTypeR with an OpenRouter or OpenAI API key?▼

No, CyteTypeR requires credentials for the Nygen Analytics CyteType API specifically. OpenRouter or other generic LLM provider keys will cause job submission failures, so you must obtain access from Nygen Analytics.

Why are some clusters missing from CyteTypeR annotation results?▼

Clusters are skipped when they lack sufficient marker genes after filtering. Lower the avg_log2FC threshold, increase n_top_genes in PrepareCyteTypeR, or verify marker counts per cluster with table(cluster_markers$cluster).

What are the limitations of LLM-based cell type annotation?▼

CyteTypeR works best for well-characterized populations like immune cells, PBMCs, and neurons, and requires completed clustering and marker discovery beforehand. It depends on an external cloud API, so jobs take 5-15 minutes and need internet access.

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