IPA is a web-based software application for the analysis, integration, and interpretation of data derived from 'omics experiments, such as RNAseq, small RNAseq, microarrays including miRNA and SNP, metabolomics, proteomics, and small scale experiments that generate gene and chemical lists. Powerful analysis and search tools uncover the significance of data and identify new targets or candidate biomarkers within the context of biological systems.
IPA goes beyond pathway analysis by:
- Identifying key regulators and activity to explain expression patterns.
- Predicting downstream effects on biological and disease processes.
- Providing targeted data on genes, proteins, chemicals, and drugs.
- Building interactive models of experimental systems.
Data analysis and interpretation with IPA builds on the comprehensive, manually curated content of the Ingenuity Knowledge Base. Powerful algorithms identify regulators, relationships, mechanisms, functions, and pathways relevant to changes observed in an analysed dataset. Analytics go beyond pathway analysis to understand experimental results within the context of biological systems and interactive tools allow detailed exploration of results, including comparisons across multiple analyses, discovery of novel biological connections, and generation of testable hypotheses.