BioRssay: an R package for analyses of bioassays and probit graphs

Piyal Karunarathne,Pierrick Labbé,Pascal Milesi,Nicolas Pocquet

doi:10.1186/s13071-021-05146-x

Abstract

Dose–response relationships reflect the effects of a substance on organisms, and are widely used in broad research areas, from medicine and physiology, to vector control and pest management in agronomy. Furthermore, reporting on the response of organisms to stressors is an essential component of many public policies (e.g. public health, environment), and assessment of xenobiotic responses is an integral part of World Health Organization recommendations. Building upon an R script that we previously made available, and considering its popularity, we have now developed a software package in the R environment, BioRssay, to efficiently analyze dose–response relationships. It has more user-friendly functions and more flexibility, and proposes an easy interpretation of the results. The functions in the BioRssay package are built on robust statistical analyses to compare the dose/exposure–response of various bioassays and effectively visualize them in probit-graphs.Graphical

Highlights

Bioassays aim at evaluating the potency of a compound
They usually consist in measuring the response of a “population” to increasing doses of a stimulus to quantify specific dose–response relationships
Despite bioassays being used in many fields, there has been a substantial lack of accessible statistical infrastructure for their analysis

Summary

Introduction

Bioassays aim at evaluating the potency of a compound. They usually consist in measuring the response of a “population” (e.g. organisms, populations, tissues, cells lines, strains, etc.) to increasing doses (or intensities or exposure times) of a stimulus (most of the time a xenobiotic or a chemical) to quantify specific dose–response relationships ( known as exposure–response relationships). Uu.se †Pierrick Labbé and Pascal Milesi contributed to the work and are listed in alphabetic order 1 Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE‐752 36, Uppsala, Sweden 3 Institut Universitaire de France, 1 Rue Descartes, 75231 Cedex 05 Paris, France Full list of author information is available at the end of the article xenobiotics.

Results

Conclusion