title: Challenges in secondary analysis of high throughput screening data.
abstract: Repurposing an existing drug for an alternative use is not only a cost effective method of development, but also a faster process due to the drug's previous clinical testing and established pharmokinetic profiles. A potentially rich resource for computational drug repositioning approaches is publically available high throughput screening data, available in databases such as PubChem Bioassay and ChemBank. We examine statistical and computational considerations for secondary analysis of publicly available high throughput screening (HTS) data with respect to metadata, data quality, and completeness. We discuss developing methods and best practices that can help to ameliorate these issues.
authors.affiliation: Division of Bioinformatics and Computational Biology, Oregon Health & Science University, Portland, OR 97203, USA. blucher@ohsu.edu.
authors.forename: Aurora S
authors.initials: AS
authors.lastname: Blucher
authors.forename: Shannon K
authors.initials: SK
authors.lastname: McWeeney
mesh_terms: D019295:Computational Biology; D062313:Databases, Pharmaceutical / Q000706:statistics & numerical data*; D058492:Drug Repositioning / Q000706:statistics & numerical data*; D057166:High-Throughput Screening Assays / Q000706:statistics & numerical data*; D006801:Humans