combi

combi combines quasi-likelihood estimation, compositional regression models and latent variable models for integrative visualization of several omics datasets.

Key Features:

• Unconstrained integration: Explorative ordination enables integrative visualization of multiple omics datasets without predefined constraints.
• Constrained integration: The method supports constrained integration for directed analysis of multi-omics data.
• Compositional multiplots: Results are displayed as interpretable, compositional multiplots that facilitate biological interpretation.

Scientific Applications:

• Multi-omics data integration: Integrative visualization of several omics datasets enables joint analysis of heterogeneous molecular data types.
• Exploratory data analysis: The ordination approach supports unsupervised exploration of complex multi-omics relationships.

Methodology:

The method combines quasi-likelihood estimation, compositional regression models and latent variable models in an explorative ordination framework.