Your browser doesn't support javascript.
loading
tcpl: the ToxCast pipeline for high-throughput screening data.
Filer, Dayne L; Kothiya, Parth; Setzer, R Woodrow; Judson, Richard S; Martin, Matthew T.
Affiliation
  • Filer DL; Oak Ridge Institute for Science Education Fellow at National Center for Computational Toxicology.
  • Kothiya P; Oak Ridge Institute for Science Education Fellow at National Center for Computational Toxicology.
  • Setzer RW; National Center for Computational Toxicology, US EPA, Research Triangle Park, NC, USA.
  • Judson RS; National Center for Computational Toxicology, US EPA, Research Triangle Park, NC, USA.
  • Martin MT; National Center for Computational Toxicology, US EPA, Research Triangle Park, NC, USA.
Bioinformatics ; 33(4): 618-620, 2017 02 15.
Article in En | MEDLINE | ID: mdl-27797781
Motivation: Large high-throughput screening (HTS) efforts are widely used in drug development and chemical toxicity screening. Wide use and integration of these data can benefit from an efficient, transparent and reproducible data pipeline. Summary: The tcpl R package and its associated MySQL database provide a generalized platform for efficiently storing, normalizing and dose-response modeling of large high-throughput and high-content chemical screening data. The novel dose-response modeling algorithm has been tested against millions of diverse dose-response series, and robustly fits data with outliers and cytotoxicity-related signal loss. Availability and Implementation: tcpl is freely available on the Comprehensive R Archive Network under the GPL-2 license. Contact: martin.matt@epa.gov.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Toxicity Tests / Drug Evaluation, Preclinical / High-Throughput Screening Assays / Models, Biological Type of study: Diagnostic_studies / Screening_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2017 Document type: Article Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Toxicity Tests / Drug Evaluation, Preclinical / High-Throughput Screening Assays / Models, Biological Type of study: Diagnostic_studies / Screening_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2017 Document type: Article Country of publication: Reino Unido