Best use case
cellranger-processor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Cell Ranger skill for 10X Genomics single-cell data processing
Teams using cellranger-processor should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cellranger-processor/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cellranger-processor Compares
| Feature / Agent | cellranger-processor | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Cell Ranger skill for 10X Genomics single-cell data processing
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# CellRanger Processor Skill ## Purpose Provide Cell Ranger capabilities for 10X Genomics single-cell data processing including demultiplexing and alignment. ## Capabilities - BCL to FASTQ conversion - Cell barcode demultiplexing - UMI counting - Feature barcode processing - Aggregate sample analysis - Loupe Browser file generation ## Usage Guidelines - Configure sample sheets accurately - Validate cell counts against expectations - Review QC metrics from web summary - Aggregate samples for combined analysis - Generate Loupe files for visualization - Document reference versions ## Dependencies - Cell Ranger - STARsolo ## Process Integration - Single-Cell RNA-seq Analysis (scrnaseq-analysis) - Spatial Transcriptomics Analysis (spatial-transcriptomics)
Related Skills
markdown-processor
Specialized skill for processing Markdown and MDX documentation. Supports parsing, rendering, TOC generation, link validation, frontmatter processing, and diagram embedding.
survey-data-processor
Survey data processing skill for point clouds, DTM generation, and coordinate transformation
samtools-bam-processor
BAM/SAM file manipulation skill for sorting, indexing, filtering, and extracting alignment data
maxquant-processor
MaxQuant mass spectrometry skill for protein identification and quantification
warranty-claims-processor
Streamlined warranty claim validation and processing skill improving customer satisfaction and reducing processing time
returns-authorization-processor
Automated return authorization and routing skill optimizing return paths and customer experience
process-builder
Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
babysitter
Orchestrate via @babysitter. Use this skill when asked to babysit a run, orchestrate a process or whenever it is called explicitly. (babysit, babysitter, orchestrate, orchestrate a run, workflow, etc.)
yolo
Run Babysitter autonomously with minimal manual interruption.
user-install
Install the user-level Babysitter Codex setup.
team-install
Install the team-pinned Babysitter Codex workspace setup.
retrospect
Summarize or retrospect on a completed Babysitter run.