MOTIVATION: Flow cytometry is a widely used technique among biologists to study the abundances of populations of microscopic algae living in aquatic environments. A new generation of high-frequency flow cytometers collects up to several hundred samples per day and can run continuously for several weeks. Automated computational methods are needed to analyze the different phytoplankton populations present in each sample. Software packages in the programming environment R provide powerful tools for conducting such analyses. RESULTS: We introduce flowPhyto, an R package that performs aggregate statistics on virtually unlimited collections of raw flow cytometry files and provides a memory efficient, parallelized solution for analyzing high-throughput flow cytometric data. AVAILABILITY: Freely accessible at http://www.bioconductor.org.
MOTIVATION: Flow cytometry is a widely used technique among biologists to study the abundances of populations of microscopic algae living in aquatic environments. A new generation of high-frequency flow cytometers collects up to several hundred samples per day and can run continuously for several weeks. Automated computational methods are needed to analyze the different phytoplankton populations present in each sample. Software packages in the programming environment R provide powerful tools for conducting such analyses. RESULTS: We introduce flowPhyto, an R package that performs aggregate statistics on virtually unlimited collections of raw flow cytometry files and provides a memory efficient, parallelized solution for analyzing high-throughput flow cytometric data. AVAILABILITY: Freely accessible at http://www.bioconductor.org.
Authors: Francois Ribalet; Jarred Swalwell; Sophie Clayton; Valeria Jiménez; Sebastian Sudek; Yajuan Lin; Zackary I Johnson; Alexandra Z Worden; E Virginia Armbrust Journal: Proc Natl Acad Sci U S A Date: 2015-06-15 Impact factor: 11.205