DIABLO (Data Integration Analysis for Biomarker discovery using Latent cOmponents) — supervised multi-omics integration method from the mixOmics R package. Performs sparse generalized canonical correl
Use with AI
Install the MCP server or CLI to instantly fetch DIABLO documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/diablo
mixOmics — R/Bioconductor package for multi-omics data integration using multivariate projection methods. Provides PCA, PLS, sPLS, PLS-DA, sPLS-DA, DIABLO (multi-block sPLS-DA), and MINT (multi-study
3 shared topics • 1 shared operation
Use when working with OmicsIntegrator or OmicsIntegrator2 — a network-based multi-omics data integration framework from the Fraenkel Lab (MIT). Applies the Prize-Collecting Steiner Forest (PCSF) algor
3 shared topics
Use when inferring mechanistic causal links across multiple omics layers with COSMOS (Causal Oriented Search of Multi-Omics Space). Integrates metabolomics, transcriptomics, and signaling pathway data
2 shared topics • 1 shared operation
spatialdata is the scverse Python framework for managing, analyzing, and visualizing multi-modal spatial omics datasets. Provides a unified SpatialData object that stores images, segmentation labels,
2 shared topics • 1 shared operation
Trinotate — comprehensive functional annotation suite for transcriptome assemblies. Integrates BLAST/DIAMOND homology searches against SwissProt, HMMER/Pfam protein domain identification, SignalP sign
2 shared topics • 1 shared operation