Supported data types

Omics Studio supports three omics data types, each with its own identifier standards and database integrations. They can be analyzed individually or combined into multiomics studies.

Proteomics

Protein-level abundance data. Omics Studio maps features using UniProt or Protein Name identifiers, and connects to UniProt, Reactome, and the Human Protein Atlas for annotation and pathway analysis.

Transcriptomics

Gene expression data at the transcript level. Features are mapped using Ensembl or Gene Name identifiers, with Reactome and Gene Ontology available for enrichment analysis.

Metabolomics

Small molecule abundance data. Omics Studio supports ChEBI, InChI, and Metabolite Name identifiers, enabling pathway mapping via Reactome and clinical context via ClinicalTrials.gov.

Multiomics

Any combination of the above data types can be brought together into a single study, enabling cross-omics comparison and integrated interpretation.