Bioassay analysis using R

By Christian Ritz, Jens Carl Streibig. 2005

1,563 citations recorded by the source corpus.

We describe an add-on package for the language and environment R which allows simultaneous fitting of several non-linear regression models. The focus is on analysis of dose response curves, but the functionality is applicable to arbitrary non-linear regression models. Features of the package is illustrated in examples.

Subfields: Cancer Research, Genetics, Pollution

View Paper: https://www.semanticscholar.org/paper/2e941a330d287e007796386bf47fedbc2f089b8f

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Citations in the corpus

Relative potency in nonsimilar dose–response curves (2006, methodology): “Although calculation of relative potency in the case of nonsimilar dose–response curves is slightly more complicated than with similar curves, the calculation can be handled (Ritz and Streibig 2005).”
Nonlinear Regression Models and Applications in Agricultural Research (2015, background): “The choice of values will influence the convergence of the estimation algorithm, in the worst case yielding no convergence and in the best case convergence in a few iterations (Ritz and Streibig, 2005); however, there is no standard procedure for getting initial estimates.”
Control of cereal rye with a roller/crimper as influenced by cover crop phenology. (2009, methodology): “Th is is analogous to the term eff ective dose commonly used when evaluating herbicide effi cacy with dose response models (Ritz and Streibig, 2005).”
A Toolbox for Nonlinear Regression in R: The Package nlstools (2015, methodology): “Speciﬁcally for dose-response and growth curve modeling, the packages drc [Ritz and Streibig, 2005], drﬁt [Ranke, 2006], and groﬁt [Kahm et al., 2010] among others oﬀer infrastructure for automatically providing data-driven, informed starting values so that the user need not think about providing…”
Understanding the potential for resistance evolution to the new herbicide pyroxasulfone: Field selection at high doses versus recurrent selection at low doses (2012, methodology): “Biomass data were expressed as a per cent of the untreated control and analysed with the same model assuming Gaussian continuous distribution of errors in non-linear regression analysis (Ritz & Streibig, 2005).”
Glyphosate Tolerance Mechanism in Italian Ryegrass (Lolium multiflorum) from Mississippi (2008, methodology): “The regression parameters for the above equation were computed using R software (Ritz and Streibig 2005).”
Dose-Response Analysis Using R (2015, methodology): “One such specialized sub system for analysis of dose-response data is provided through the add-on package drc [2].”
Searching for Drug Synergy in Complex Dose–Response Landscapes Using an Interaction Potency Model (2015, methodology): “The CI was calculated using an R package SYNERGY [13] and the alpha score was estimated using the R package drc [12].”
qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis (2008, methodology): “The nonlinear fitting engine is based on another add-on package ( drc ; Ritz et al ., 2005).”
Toward a unified approach to dose–response modeling in ecotoxicology (2010, methodology): “Currently, this approach is being implemented through the extension package drc [55] for the open source statistical software R, which is developed by the R Project for Statistical Computing (http://www.”