Execute single-cell RNA-seq workflows with QC, batch integration, and cell-type annotation.
npx skills add https://github.com/Minions-Land/AutOmicScience --skill omics-scrna
Please help me install this Agent Skill. Skill: omics-scrna Source: https://github.com/Minions-Land/AutOmicScience/tree/main/skills/omics/scrna Command: npx skills add https://github.com/Minions-Land/AutOmicScience --skill omics-scrna
This Skill solves the challenge of reproducible bioinformatics analysis by providing an autonomous, evidence-based framework for single-cell RNA-seq processing that eliminates hallucinated results and manual pipeline errors.
Run the omics-scrna skill to perform quality control and preprocessing on the raw h5ad file named raw_data.h5ad.
High-intent search queries and answers about installing and using this skill.
Automate single-cell RNA-seq analysis by running autonomous workflows for QC, normalization, batch integration, and clustering using pinned scverse environments. The pipeline processes raw h5ad files and performs marker-based cell-type annotation with evidence-backed biological validation.
Reproducible scRNA-seq batch integration uses a pinned Pixi environment and the omics_runtime tool registry for deterministic tool dispatch. This eliminates manual pipeline errors by recording tool-call evidence for every step executed within the scverse ecosystem.
The scverse pipeline performs cell-type labeling using marker-based evidence and LLM reasoning. It includes built-in abstention for ambiguous clusters, ensuring that only biologically validated and evidence-backed annotations are returned for your single-cell dataset.
You need a pinned Pixi environment and access to the omics_runtime tool registry for deterministic tool dispatch. This setup ensures reproducible scientific compute by enforcing a strict scverse ecosystem configuration for your scRNA-seq data processing.
Hallucinated results and manual pipeline errors occur without an evidence-based framework. This Skill eliminates them by orchestrating autonomous scverse workflows and recording tool-call evidence for every QC, integration, and annotation step to validate biological integrity.
Autonomous scRNA-seq quality control workflows require a pinned Pixi environment and omics_runtime tool registry access. Without these deterministic configurations, the scverse-based pipeline cannot guarantee reproducible tool dispatch or evidence-backed scientific compute for multi-agent research environments.
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