CurveCurator: a recalibrated F-statistic to assess, classify, and explore significance of dose-response curves.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
30 Nov 2023
30 Nov 2023
Historique:
received:
25
08
2023
accepted:
16
11
2023
medline:
4
12
2023
pubmed:
1
12
2023
entrez:
30
11
2023
Statut:
epublish
Résumé
Dose-response curves are key metrics in pharmacology and biology to assess phenotypic or molecular actions of bioactive compounds in a quantitative fashion. Yet, it is often unclear whether or not a measured response significantly differs from a curve without regulation, particularly in high-throughput applications or unstable assays. Treating potency and effect size estimates from random and true curves with the same level of confidence can lead to incorrect hypotheses and issues in training machine learning models. Here, we present CurveCurator, an open-source software that provides reliable dose-response characteristics by computing p-values and false discovery rates based on a recalibrated F-statistic and a target-decoy procedure that considers dataset-specific effect size distributions. The application of CurveCurator to three large-scale datasets enables a systematic drug mode of action analysis and demonstrates its scalable utility across several application areas, facilitated by a performant, interactive dashboard for fast data exploration.
Identifiants
pubmed: 38036588
doi: 10.1038/s41467-023-43696-z
pii: 10.1038/s41467-023-43696-z
pmc: PMC10689459
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7902Subventions
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 833710
Informations de copyright
© 2023. The Author(s).
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