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Analysis of High-Throughput Flow Cytometry Data Using plateCore
Author(s) -
Errol Strain,
Florian Hahne,
Ryan R. Brinkman,
Perry D. Haaland
Publication year - 2009
Publication title -
advances in bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.33
H-Index - 20
eISSN - 1687-8035
pISSN - 1687-8027
DOI - 10.1155/2009/356141
Subject(s) - bioconductor , computer science , software , flow cytometry , data set , throughput , data mining , cytometry , set (abstract data type) , artificial intelligence , medicine , operating system , immunology , biology , programming language , wireless , biochemistry , gene
Flow cytometry (FCM) software packages from R/Bioconductor, such as flowCore and flowViz, serve as an open platform for development of new analysis tools and methods. We created plateCore, a new package that extends the functionality in these core packages to enable automated negative control-based gating and make the processing and analysis of plate-based data sets from high-throughput FCM screening experiments easier. plateCore was used to analyze data from a BD FACS CAP screening experiment where five Peripheral Blood Mononucleocyte Cell (PBMC) samples were assayed for 189 different human cell surface markers. This same data set was also manually analyzed by a cytometry expert using the FlowJo data analysis software package (TreeStar, USA). We show that the expression values for markers characterized using the automated approach in plateCore are in good agreement with those from FlowJo, and that using plateCore allows for more reproducible analyses of FCM screening data.

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