tcplfit2: an R-language general purpose concentration-response modeling package.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
27 01 2022
27 01 2022
Historique:
received:
09
08
2021
revised:
14
10
2021
accepted:
09
11
2021
pubmed:
19
11
2021
medline:
3
2
2023
entrez:
18
11
2021
Statut:
ppublish
Résumé
Many applications of chemical screening are performed in concentration or dose-response mode, and it is necessary to extract appropriate parameters, including whether the chemical/assay pair is active and if so, what are concentrations where activity is seen. Typically, multiple mathematical models or curve shapes are tested against the data to assess the best fit. There are several commercial programs used for this purpose as well as open-source libraries. A widely used system for managing high-throughput screening (HTS) concentration-response data is tcpl (ToxCast Pipeline). The current implementation of tcpl has the concentration-response modeling code tightly integrated with the data management and databasing aspects of HTS data processing. Tcplfit2 is a stand-alone version of the curve-fitting and hitcalling core of tcpl that has been extended to include a large number of standard curve classes and to use benchmark dose modeling. This package will be useful for HTS concentration-response data such as high-throughput whole genome transcriptomics. tcplfit2 is written in R and is available from CRAN.
Identifiants
pubmed: 34791027
pii: 6428656
doi: 10.1093/bioinformatics/btab779
pmc: PMC10202035
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
1157-1158Subventions
Organisme : US EPA.
Informations de copyright
Published by Oxford University Press 2021. This work is written by US Government employees and is in the public domain in the US.
Références
Toxicol Sci. 2007 Jul;98(1):240-8
pubmed: 17449896
Bioinformatics. 2019 May 15;35(10):1780-1782
pubmed: 30329029
Bioinformatics. 2017 Feb 15;33(4):618-620
pubmed: 27797781
PLoS One. 2015 Dec 30;10(12):e0146021
pubmed: 26717316
BMC Genomics. 2007 Oct 25;8:387
pubmed: 17961223
Toxicol Sci. 2021 Apr 27;181(1):68-89
pubmed: 33538836