bio-workflows-multi-omics-pipeline

Integrate multi-omics datasets with MOFA2, mixOmics, and SNF to discover shared biological signals.

Updated Mar 30, 2026
One-click install
npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-workflows-multi-omics-pipeline
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bio-workflows-multi-omics-pipeline
Source: https://github.com/ya-way/cytoclaw-skills/tree/main/workspace/skills/bio-wf-multi-omics-pipeline
Command: npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-workflows-multi-omics-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Integrates multiple omics datasets (transcriptomics, proteomics, metabolomics) to uncover shared biology, enabling cross-modal biomarker discovery and patient stratification.

Core Features & Use Cases

  • End-to-end multi-omics integration using MOFA2, DIABLO, and SNF for both unsupervised discovery and supervised analyses.
  • Data harmonization, feature selection, factor interpretation, and downstream analyses across modalities.
  • Use Case: Discover shared biological signals and stratify patients using integrated omics signatures.

Quick Start

Load transcriptomics, proteomics, and metabolomics data and run the end-to-end multi-omics pipeline to discover shared signals across modalities.

Frequently Asked Questions about bio-workflows-multi-omics-pipeline

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

FAQPage Schema
How do I integrate multi-omics data for patient stratification and biomarker discovery?▼

Integrate multi-omics data for patient stratification by loading transcriptomics, proteomics, and metabolomics datasets into an end-to-end pipeline that discovers shared biological signals across modalities.

What is the best way to run unsupervised and supervised multi-omics integration together?▼

Run unsupervised and supervised multi-omics integration together using a workflow that applies MOFA2, DIABLO, and SNF to handle data harmonization, feature selection, and cross-modality factor interpretation.

Can I use MOFA2 and mixOmics for cross-modal pathway interpretation?▼

Yes, you can use MOFA2 and mixOmics for cross-modal pathway interpretation by applying their factor interpretation and feature selection capabilities to uncover shared biology across multiple omics layers.

How does SNF work for integrating transcriptomics and proteomics datasets?▼

SNF integrates transcriptomics and proteomics datasets by fusing similarity networks across modalities, enabling the discovery of shared biological signals and accurate patient stratification.

Do I need to perform data harmonization before running multi-omics integration workflows?▼

Data harmonization is handled within the multi-omics integration workflow itself, ensuring cross-modality datasets are properly aligned before feature selection and downstream analyses are executed.