Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

drda: An R package for dose-response data analysis

View ORCID ProfileAlina Malyutina, View ORCID ProfileJing Tang, View ORCID ProfileAlberto Pessia
doi: https://doi.org/10.1101/2021.06.07.447323
Alina Malyutina
1Research Program in Systems Oncology (ONCOSYS), Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland, E-mail: , , , URL:
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alina Malyutina
  • For correspondence: alina.malyutina@helsinki.fi jing.tang@helsinki.fi academic@albertopessia.com
Jing Tang
1Research Program in Systems Oncology (ONCOSYS), Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland, E-mail: , , , URL:
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jing Tang
  • For correspondence: alina.malyutina@helsinki.fi jing.tang@helsinki.fi academic@albertopessia.com
Alberto Pessia
1Research Program in Systems Oncology (ONCOSYS), Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland, E-mail: , , , URL:
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alberto Pessia
  • For correspondence: academic@albertopessia.com alina.malyutina@helsinki.fi jing.tang@helsinki.fi academic@albertopessia.com
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Analysis of dose-response data is an important step in many scientific disciplines, including but not limited to pharmacology, toxicology, and epidemiology. The R package drda is designed to facilitate the analysis of dose-response data by implementing efficient and accurate functions with a familiar interface. With drda, it is possible to fit models by the method of least squares, perform goodness of fit tests, and conduct model selection. Compared to other similar packages, drda provides, in general, more accurate estimates in the least-squares sense. This result is achieved by a smart choice of the starting point in the optimization algorithm and by implementing the Newton method with a trust region with analytical gradients and Hessian matrices. In this article, drda is presented through the description of its methodological components and examples of its user-friendly functions. Performance is finally evaluated using a real, large-scale drug sensitivity screening dataset.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted June 07, 2021.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
drda: An R package for dose-response data analysis
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
drda: An R package for dose-response data analysis
Alina Malyutina, Jing Tang, Alberto Pessia
bioRxiv 2021.06.07.447323; doi: https://doi.org/10.1101/2021.06.07.447323
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
drda: An R package for dose-response data analysis
Alina Malyutina, Jing Tang, Alberto Pessia
bioRxiv 2021.06.07.447323; doi: https://doi.org/10.1101/2021.06.07.447323

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4115)
  • Biochemistry (8818)
  • Bioengineering (6522)
  • Bioinformatics (23466)
  • Biophysics (11792)
  • Cancer Biology (9212)
  • Cell Biology (13326)
  • Clinical Trials (138)
  • Developmental Biology (7439)
  • Ecology (11416)
  • Epidemiology (2066)
  • Evolutionary Biology (15155)
  • Genetics (10439)
  • Genomics (14045)
  • Immunology (9173)
  • Microbiology (22160)
  • Molecular Biology (8814)
  • Neuroscience (47582)
  • Paleontology (350)
  • Pathology (1429)
  • Pharmacology and Toxicology (2492)
  • Physiology (3731)
  • Plant Biology (8082)
  • Scientific Communication and Education (1437)
  • Synthetic Biology (2221)
  • Systems Biology (6039)
  • Zoology (1253)