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Automated analysis of flow cytometry data comes of age

Automated analysis of flow cytometry data comes of age Editorial Automated Analysis of Flow Cytometry Data Comes of Age 1,2 3 4 4 Ryan R. Brinkman, Nima Aghaeepour, Greg Finak, Raphael Gottardo, 5 6,7 Tim Mosmann, Richard H. Scheuermann THIS is the second of two Special Issues focused on the Com- FlowReMi, for Flow Density Survival Regression Using Mini- putational Analysis of Flow Cytometry Data. These Special mal Feature Redundancy, combined two previously developed Issues were built around the FlowCAP project, run under the algorithms, an automated cell population identification direction of an open consortium of immunologists, bioinfor- method [flowDensity (5)], and flowType (6) which uses cell maticians, statisticians, and clinical scientists who share the partitions provided for each marker by either manual analysis goal of advancing the development of computational methods or by clustering to enumerate all cell types in a sample, with a for the identification of cell populations of interest in flow feature selection algorithm to identify informative, non- cytometry data (1). Three new algorithms that participated in redundant features predictive of time to AIDS in a survival the FlowCAP-IV challenge were highlighted in the previous model. The authors evaluated three survival time prediction Special Issue (2–4). Aghaeepour and members of the Flow- algorithms using http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Cytometry Part A Wiley

Automated analysis of flow cytometry data comes of age

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References (7)

Publisher
Wiley
Copyright
© 2016 International Society for Advancement of Cytometry
ISSN
1552-4922
eISSN
1552-4930
DOI
10.1002/cyto.a.22810
pmid
26812230
Publisher site
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Abstract

Editorial Automated Analysis of Flow Cytometry Data Comes of Age 1,2 3 4 4 Ryan R. Brinkman, Nima Aghaeepour, Greg Finak, Raphael Gottardo, 5 6,7 Tim Mosmann, Richard H. Scheuermann THIS is the second of two Special Issues focused on the Com- FlowReMi, for Flow Density Survival Regression Using Mini- putational Analysis of Flow Cytometry Data. These Special mal Feature Redundancy, combined two previously developed Issues were built around the FlowCAP project, run under the algorithms, an automated cell population identification direction of an open consortium of immunologists, bioinfor- method [flowDensity (5)], and flowType (6) which uses cell maticians, statisticians, and clinical scientists who share the partitions provided for each marker by either manual analysis goal of advancing the development of computational methods or by clustering to enumerate all cell types in a sample, with a for the identification of cell populations of interest in flow feature selection algorithm to identify informative, non- cytometry data (1). Three new algorithms that participated in redundant features predictive of time to AIDS in a survival the FlowCAP-IV challenge were highlighted in the previous model. The authors evaluated three survival time prediction Special Issue (2–4). Aghaeepour and members of the Flow- algorithms using

Journal

Cytometry Part A – Wiley

Published: Jan 1, 2016

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