Improving the Utility of the Tox21 Dataset by Deep Metadata Annotations and Constructing Reusable Benchmarked Chemical Reference Signatures
| Autor: | Daniel J. Cooper, Stephan C. Schürer |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Interoperability Pharmaceutical Science Datasets as Topic 010501 environmental sciences computer.software_genre Toxicology 01 natural sciences high-throughput screening Article Analytical Chemistry Xenobiotics lcsh:QD241-441 03 medical and health sciences Annotation Tox21 lcsh:Organic chemistry Genes Reporter Drug Discovery Controlled vocabulary Humans ontologies Physical and Theoretical Chemistry Data Curation 030304 developmental biology 0105 earth and related environmental sciences 0303 health sciences FAIR data Metadata Gene Expression Profiling Organic Chemistry Aggregate (data warehouse) Signature (logic) High-Throughput Screening Assays Benchmarking Data point Gene Expression Regulation Chemistry (miscellaneous) Pharmacogenetics signatures Molecular Medicine Data mining data standards computer |
| Zdroj: | Molecules Volume 24 Issue 8 Molecules, Vol 24, Iss 8, p 1604 (2019) |
| ISSN: | 1420-3049 |
| Popis: | The Toxicology in the 21st Century (Tox21) project seeks to develop and test methods for high-throughput examination of the effect certain chemical compounds have on biological systems. Although primary and toxicity assay data were readily available for multiple reporter gene modified cell lines, extensive annotation and curation was required to improve these datasets with respect to how FAIR (Findable, Accessible, Interoperable, and Reusable) they are. In this study, we fully annotated the Tox21 published data with relevant and accepted controlled vocabularies. After removing unreliable data points, we aggregated the results and created three sets of signatures reflecting activity in the reporter gene assays, cytotoxicity, and selective reporter gene activity, respectively. We benchmarked these signatures using the chemical structures of the tested compounds and obtained generally high receiver operating characteristic (ROC) scores, suggesting good quality and utility of these signatures and the underlying data. We analyzed the results to identify promiscuous individual compounds and chemotypes for the three signature categories and interpreted the results to illustrate the utility and re-usability of the datasets. With this study, we aimed to demonstrate the importance of data standards in reporting screening results and high-quality annotations to enable re-use and interpretation of these data. To improve the data with respect to all FAIR criteria, all assay annotations, cleaned and aggregate datasets, and signatures were made available as standardized dataset packages (Aggregated Tox21 bioactivity data, 2019). |
| Databáze: | OpenAIRE |
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