iODA

iODA performs integrated analysis of heterogeneous multi-omics datasets to assess pathway-level consistency in cancer.

Key Features:

• Multi-Omics Integration: Integrates transcriptomic profiles, including mRNA and microRNA (miRNA) expression, with protein–DNA interaction data from ChIP-Seq for systems-level interpretation.
• Statistical Analysis Flexibility: Compares six different statistical algorithms to perform differential analysis on selected sample data for identifying dysfunctional mRNA or miRNA molecules.
• Pathway-Level Consistency: Enriches identified dysfunctional molecules onto KEGG pathways and extracts consistent items as key pathway components to emphasize pathway-level consistency over gene-level analysis.
• Next-Generation Sequencing Data: Leverages next-generation sequencing (NGS)–derived datasets to enhance the resolution of carcinogenesis studies.

Scientific Applications:

• Prostate cancer multi-omics analysis: Demonstrated on single- and cross-level omics datasets of prostate cancer to investigate molecular alterations.
• Cancer pathogenesis investigation: Facilitates systematic exploration of molecular mechanisms underlying cancer development and progression via integrated multi-omics and pathway enrichment.

Methodology:

Integrates mRNA, microRNA expression and ChIP-Seq protein–DNA interaction data; compares six statistical algorithms for differential analysis on selected samples; performs enrichment of dysfunctional molecules onto KEGG pathways and extracts consistent pathway components.