Polly curates and harmonizes datasets from public repositories- processes measurements, links to ontology-backed metadata and transforms them into a unified data model to deliver pristine quality data for faster insights.
Polly curates datasets of your choice from public repositories, harmonizes them, and delivers in a pristine-quality, ML-ready format, fit for downstream analysis.
Polly retrieves datasets from public repositories and curates and harmonizes data of choice. Polly's powerful harmonization engine processes measurements, links to ontology-backed metadata and transforms them into a Unified Data Model. Datasets are mapped with 6 standard fields (can be customized for up to ~30 fields) to ontologies at dataset and sample level. Commonly used ontologies are MeSH, BRENDA Tissue Ontology, NCBI Taxonomy, Cellosaurus, Cell Ontology and PubChem, for disease, tissue, organism, cell line, cell type, drug respectively.
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Biomedical data harmonized every month.
Data types supported across multi-omics, assay and clinical.
Data sources supported including GEO, PRIDE, CPTAC and more.
Diseases across oncology, metabolic, immunology and more.
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