Aristotle
Official@aristoteleo · United States of America
Foundational software ecosystem for predictive genomics
Agent Skills by Aristotle
Showing 15 vetted skills indexed across 2 GitHub repositories.
Paper Writing Skills
Convert Markdown manuscripts into styled HTML or PDF using Pandoc themes.
Figure Styling Skills Index
Define standardized palettes, typography, and layout for scientific figures.
Upstream Processing Skills Index
Coordinate upstream single-cell and spatial omics workflows from raw sequencing data to count matrices.
Single-Cell Analysis Skills Index
Combine single-cell RNA-seq workflows for QC, annotation, and trajectory inference.
Single-Cell Foundation Models Skills Index
Locate SCFM workflow and model reference resources for single-cell experiments.
General Data Analysis Skills Index
Configure reproducible Python data-analysis environments and parallel compute pipelines.
Database Access Skills Index
Organize a catalog of genomics data access skills with linked sub-skills.
Spatial Omics Skills
Index spatial omics analysis skills for discovery and reuse.
Gene Panel Selection Workflow
Develop and evaluate gene panels for single-cell analyses with ARI/NMI/SI benchmarking.
SC Best Practices Skills Index
Index single-cell RNA-seq best practice skills with YAML frontmatter.
nf-core Pipelines Skills Index
Identify and access nf-core pipelines for omics analysis workflows.
OpenST Skills Index
Map Open-ST data processing into an end-to-end pipeline from BCL/FASTQ to h5ad objects.
dynamo-preprocess
Convert notebook preprocessing workflows into configurable dynamo Preprocessor agent skills.
skill-quality-scorer
Score Skill Units against a structured rubric and output Markdown and YAML reports.
skill-authoring
Convert notebook-driven workflows into triggerable Codex skills with defined input contracts.
Frequently Asked Questions About Aristotle
FAQPage SchemaWhat specific genomics tasks does Aristotle enable?▼
Aristotle enables end-to-end processing of single-cell and spatial omics data, including raw sequencing conversion, count matrix generation, and trajectory inference. It further supports scientific output by providing standardized figure styling and manuscript generation from structured research data.
Which research personas benefit from these genomics capabilities?▼
Bioinformaticians, computational biologists, and genomics researchers benefit from these capabilities. The ecosystem is designed for those managing complex sequencing pipelines who require reproducible environments, standardized metadata, and rigorous benchmarking for gene panel selection and single-cell foundation model integration.
What are the prerequisites for implementing these genomics pipelines?▼
Implementation requires familiarity with nf-core pipeline structures, YAML-based metadata configuration, and standard genomics file formats like BCL, FASTQ, and h5ad. Users should also have access to parallel compute environments capable of executing reproducible data-analysis configurations.