bio-multi-omics-mixomics-analysis

What problem does it solve?

This skill enables researchers to perform both supervised and unsupervised integration of multiple omics datasets (e.g., transcriptomics, proteomics, metabolomics) using mixOmics to uncover discriminative signatures and robust cross-omics patterns.

Core Features & Use Cases

• DIABLO: multi-block discriminant analysis for predicting group labels across omics blocks.
• sPLS/sPLS-DA: pairwise and supervised integration to identify cross-omics feature signatures.
• MINT and unsupervised options (sPCA, sPLS) for cross-study robustness and dimensionality reduction.
• Example: integrate RNA, protein, and metabolite data to classify samples and extract a biomarker panel for downstream pathway analysis.

Quick Start

Load your omics matrices (RNA, protein, metabolites) and ask the agent to build a DIABLO model to classify sample groups.