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IncucyteDRC: An R package for the dose response analysis of live cell imaging data

We present IncucyteDRC, an R package for the analysis of data from live cell imaging cell proliferation experiments carried out on the Essen Biosciences IncuCyte ZOOM instrument. The package provides a simple workflow for summarising data into a form that can be used to calculate dose response curve...

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Detalles Bibliográficos
Autores principales: Chapman, Philip J., James, Dominic I., Watson, Amanda J., Hopkins, Gemma V., Waddell, Ian D., Ogilvie, Donald J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5031130/
https://www.ncbi.nlm.nih.gov/pubmed/27703665
http://dx.doi.org/10.12688/f1000research.8694.1
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author Chapman, Philip J.
James, Dominic I.
Watson, Amanda J.
Hopkins, Gemma V.
Waddell, Ian D.
Ogilvie, Donald J.
author_facet Chapman, Philip J.
James, Dominic I.
Watson, Amanda J.
Hopkins, Gemma V.
Waddell, Ian D.
Ogilvie, Donald J.
author_sort Chapman, Philip J.
collection PubMed
description We present IncucyteDRC, an R package for the analysis of data from live cell imaging cell proliferation experiments carried out on the Essen Biosciences IncuCyte ZOOM instrument. The package provides a simple workflow for summarising data into a form that can be used to calculate dose response curves and EC50 values for small molecule inhibitors. Data from different cell lines, or cell lines grown under different conditions, can be normalised as to their doubling time. A simple graphical web interface, implemented using shiny, is provided for the benefit of non-R users. The software is potentially useful to any research group studying the impact of small molecule inhibitors on cell proliferation using the IncuCyte ZOOM.
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spelling pubmed-50311302016-10-03 IncucyteDRC: An R package for the dose response analysis of live cell imaging data Chapman, Philip J. James, Dominic I. Watson, Amanda J. Hopkins, Gemma V. Waddell, Ian D. Ogilvie, Donald J. F1000Res Software Tool Article We present IncucyteDRC, an R package for the analysis of data from live cell imaging cell proliferation experiments carried out on the Essen Biosciences IncuCyte ZOOM instrument. The package provides a simple workflow for summarising data into a form that can be used to calculate dose response curves and EC50 values for small molecule inhibitors. Data from different cell lines, or cell lines grown under different conditions, can be normalised as to their doubling time. A simple graphical web interface, implemented using shiny, is provided for the benefit of non-R users. The software is potentially useful to any research group studying the impact of small molecule inhibitors on cell proliferation using the IncuCyte ZOOM. F1000Research 2016-05-23 /pmc/articles/PMC5031130/ /pubmed/27703665 http://dx.doi.org/10.12688/f1000research.8694.1 Text en Copyright: © 2016 Chapman PJ et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Chapman, Philip J.
James, Dominic I.
Watson, Amanda J.
Hopkins, Gemma V.
Waddell, Ian D.
Ogilvie, Donald J.
IncucyteDRC: An R package for the dose response analysis of live cell imaging data
title IncucyteDRC: An R package for the dose response analysis of live cell imaging data
title_full IncucyteDRC: An R package for the dose response analysis of live cell imaging data
title_fullStr IncucyteDRC: An R package for the dose response analysis of live cell imaging data
title_full_unstemmed IncucyteDRC: An R package for the dose response analysis of live cell imaging data
title_short IncucyteDRC: An R package for the dose response analysis of live cell imaging data
title_sort incucytedrc: an r package for the dose response analysis of live cell imaging data
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5031130/
https://www.ncbi.nlm.nih.gov/pubmed/27703665
http://dx.doi.org/10.12688/f1000research.8694.1
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