Work

Database integration of 4923 publicly-available samples of breast cancer molecular and clinical data.

Year: 2013

Type: article

Abstract: We outline a paradigm for meta-microarray database creation and integration with clinical variables. We use as our implementation example a breast cancer database linking RNA expression measurements (by microarray) and clinical variables, such as survival metrics and tumor size. Such an endeavor involves integrating across different microarray datasets as well as clinical parameters. To this end, we created a data curation and processing pipeline, formal database ontology, and SQL schema to optimally query, analyze and visualize data from over 30 publicly available breast cancer microarray studies listed in the Gene Expression Omnibus (GEO). We demonstrate several pilot examples using this database. This methodology serves as a model for future meta-analyses of complex public clinical datasets, in particular those in the field of cancer.

Source: Europe PMC (PubMed Central)

Authors: Catherine R Planey, Atul J Butte

Institutions: Stanford Medicine, Stanford University

Language: English

Topic: Gene expression and cancer classification

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funder: U.S. National Library of Medicine

Award: Biomedical Informatics Training Program at Stanford