Route natural language queries to omics analysis skills across multiple domains.
npx skills add https://github.com/TianGzlab/OmicsClaw --skill orchestrator-tiangzlab
Please help me install this Agent Skill. Skill: orchestrator Source: https://github.com/TianGzlab/OmicsClaw/tree/main/skills/orchestrator Command: npx skills add https://github.com/TianGzlab/OmicsClaw --skill orchestrator-tiangzlab
This Skill acts as a central router, translating natural language queries into specific analysis tasks across a wide range of omics data types, eliminating the need for users to memorize complex command-line tools and skill names.
Use the orchestrator skill to route the query "find spatially variable genes" to the appropriate analysis tool.
High-intent search queries and answers about installing and using this skill.
To route natural language queries for multi-omics analysis, this skill translates plain English requests into specific analysis tasks using keyword matching, LLM analysis, or a hybrid approach to select the appropriate downstream tool. It eliminates the need to memorize complex command-line tools.
The best way to analyze spatial transcriptomics without knowing specific skill names is to use a central router that accepts plain English queries like "find spatially variable genes" and automatically identifies the correct downstream analysis skill.
Yes, the multi-omics query orchestrator works with single-cell and proteomics data, alongside spatial transcriptomics, genomics, metabolomics, and bulk RNA-seq, routing queries to the correct domain-specific analysis skill.
Yes, you need scanpy installed as a dependency to route omics pipeline queries, as the orchestrator relies on it to support the underlying analysis workflows and downstream skill execution.
You should use hybrid routing instead of keyword matching for omics analysis when your natural language queries are complex or ambiguous, requiring LLM analysis combined with keyword matching to accurately identify the correct downstream skill.
dailycafiIntegrate multi-omics datasets with MOFA2 to discover shared and modality-specific latent factors.
TianGzlabPerform differential gene expression analysis on bulk RNA-seq count data.
twjarviszyra-webIndex bioinformatics reference skills and pipeline guidance for computational biology workflows.
pradyumnasagarAlign RNA-seq reads with STAR for novel junction discovery.
