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COPASutils: An R Package for Reading, Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers

The R package COPASutils provides a logical workflow for the reading, processing, and visualization of data obtained from the Union Biometrica Complex Object Parametric Analyzer and Sorter (COPAS) or the BioSorter large-particle flow cytometers. Data obtained from these powerful experimental platfor...

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Detalles Bibliográficos
Autores principales: Shimko, Tyler C., Andersen, Erik C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4203834/
https://www.ncbi.nlm.nih.gov/pubmed/25329171
http://dx.doi.org/10.1371/journal.pone.0111090
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author Shimko, Tyler C.
Andersen, Erik C.
author_facet Shimko, Tyler C.
Andersen, Erik C.
author_sort Shimko, Tyler C.
collection PubMed
description The R package COPASutils provides a logical workflow for the reading, processing, and visualization of data obtained from the Union Biometrica Complex Object Parametric Analyzer and Sorter (COPAS) or the BioSorter large-particle flow cytometers. Data obtained from these powerful experimental platforms can be unwieldy, leading to difficulties in the ability to process and visualize the data using existing tools. Researchers studying small organisms, such as Caenorhabditis elegans, Anopheles gambiae, and Danio rerio, and using these devices will benefit from this streamlined and extensible R package. COPASutils offers a powerful suite of functions for the rapid processing and analysis of large high-throughput screening data sets.
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spelling pubmed-42038342014-10-27 COPASutils: An R Package for Reading, Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers Shimko, Tyler C. Andersen, Erik C. PLoS One Research Article The R package COPASutils provides a logical workflow for the reading, processing, and visualization of data obtained from the Union Biometrica Complex Object Parametric Analyzer and Sorter (COPAS) or the BioSorter large-particle flow cytometers. Data obtained from these powerful experimental platforms can be unwieldy, leading to difficulties in the ability to process and visualize the data using existing tools. Researchers studying small organisms, such as Caenorhabditis elegans, Anopheles gambiae, and Danio rerio, and using these devices will benefit from this streamlined and extensible R package. COPASutils offers a powerful suite of functions for the rapid processing and analysis of large high-throughput screening data sets. Public Library of Science 2014-10-20 /pmc/articles/PMC4203834/ /pubmed/25329171 http://dx.doi.org/10.1371/journal.pone.0111090 Text en © 2014 Andersen http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Shimko, Tyler C.
Andersen, Erik C.
COPASutils: An R Package for Reading, Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers
title COPASutils: An R Package for Reading, Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers
title_full COPASutils: An R Package for Reading, Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers
title_fullStr COPASutils: An R Package for Reading, Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers
title_full_unstemmed COPASutils: An R Package for Reading, Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers
title_short COPASutils: An R Package for Reading, Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers
title_sort copasutils: an r package for reading, processing, and visualizing data from copas large-particle flow cytometers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4203834/
https://www.ncbi.nlm.nih.gov/pubmed/25329171
http://dx.doi.org/10.1371/journal.pone.0111090
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