DRfit: a Java tool for the analysis of discrete data from multi-well plate assays

Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environ...

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Published in:	BMC bioinformatics Vol. 20; no. 1; pp. 262 - 6
Main Authors:	Hofmann, Andreas, Preston, Sarah, Cross, Megan, Herath, H. M. P. Dilrukshi, Simon, Anne, Gasser, Robin B.
Format:	Journal Article
Language:	English
Published:	London BioMed Central 21.05.2019 BioMed Central Ltd Springer Nature B.V BMC
Subjects:	Algorithms Assaying Biochemical assays Bioinformatics Biological Science Disciplines Biomedical and Life Sciences Bivariate analysis Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computer programs Data acquisition Data analysis Data Interpretation, Statistical Data points Design Dose-response experiments Drug discovery Enzyme assays Enzymes Graphical user interface Java (Programming language) Laboratories Life Sciences Methods Microarrays Multivariate analysis Pharmaceutical research Response functions Results and data Scientific software Software Software development tools Technology application User interface User-Computer Interface France Enzyme assays Biochemical assays Data analysis Drug discovery Dose-response experiments
ISSN:	1471-2105, 1471-2105
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Abstract	Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training. Results We have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function. Conclusions DRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays.
AbstractList	Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training. Results We have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function. Conclusions DRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays. Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training. We have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function. DRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays. Abstract Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training. Results We have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function. Conclusions DRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays. Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training. We have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function. DRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays. Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training. Results We have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function. Conclusions DRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays. Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training. Results We have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function. Conclusions DRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays. Keywords: Biochemical assays, Data analysis, Dose-response experiments, Drug discovery, Enzyme assays Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training.BACKGROUNDAnalyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life Sciences. The availability of accessible cross-platform data analysis tools for such fundamental tasks in varied projects and environments is an important prerequisite to ensuring a reliable and timely turnaround as well as to provide practical analytical tools for student training.We have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function.RESULTSWe have developed an easy-to-use, interactive software tool for the analysis of multiple data sets comprising replicates of discrete bivariate data points. For each dataset, the software identifies the replicate data points from a defined matrix layout and calculates their means and standard errors. The averaged values are then automatically fitted using either a linear or a logistic dose response function.DRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays.CONCLUSIONSDRfit is a practical and convenient tool for the analysis of one or multiple sets of discrete data points acquired as replicates from multi-well plate assays. The design of the graphical user interface and the built-in analysis features make it a flexible and useful tool for a wide range of different assays.
ArticleNumber	262
Audience	Academic
Author	Hofmann, Andreas Simon, Anne Cross, Megan Gasser, Robin B. Herath, H. M. P. Dilrukshi Preston, Sarah
Author_xml	– sequence: 1 givenname: Andreas orcidid: 0000-0003-4408-5467 surname: Hofmann fullname: Hofmann, Andreas email: a.hofmann@griffith.edu.au organization: Griffith Institute for Drug Discovery, Griffith University, Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne – sequence: 2 givenname: Sarah surname: Preston fullname: Preston, Sarah organization: Faculty of Science and Technology, Federation University – sequence: 3 givenname: Megan surname: Cross fullname: Cross, Megan organization: Griffith Institute for Drug Discovery, Griffith University – sequence: 4 givenname: H. M. P. Dilrukshi surname: Herath fullname: Herath, H. M. P. Dilrukshi organization: Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne – sequence: 5 givenname: Anne surname: Simon fullname: Simon, Anne organization: Université Claude Bernard Lyon 1, Bâtiment Curien, Villeurbanne and Laboratoire Chimie et Biologie des Membranes et des Nanoobjets, Université de Bordeaux – sequence: 6 givenname: Robin B. surname: Gasser fullname: Gasser, Robin B. organization: Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne
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Snippet	Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in... Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in the Life... Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary areas in... Abstract Background Analyses of replicates in sets of discrete data, typically acquired in multi-well plate formats, is a recurring task in many contemporary...
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SubjectTerms	Algorithms Assaying Biochemical assays Bioinformatics Biological Science Disciplines Biomedical and Life Sciences Bivariate analysis Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computer programs Data acquisition Data analysis Data Interpretation, Statistical Data points Design Dose-response experiments Drug discovery Enzyme assays Enzymes Graphical user interface Java (Programming language) Laboratories Life Sciences Methods Microarrays Multivariate analysis Pharmaceutical research Response functions Results and data Scientific software Software Software development tools Technology application User interface User-Computer Interface
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Title	DRfit: a Java tool for the analysis of discrete data from multi-well plate assays
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