OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis.

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🔗 View Article (PMC 4148203)

Published in PLoS Comput Biol on August 28, 2014

Authors

Greg Finak1, Jacob Frelinger1, Wenxin Jiang1, Evan W Newell2, John Ramey1, Mark M Davis3, Spyros A Kalams4, Stephen C De Rosa5, Raphael Gottardo6

Author Affiliations

1: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
2: Agency for Science Technology and Research, Singapore Immunology Network, Singapore.
3: Department of Microbiology and Immunology, Stanford University, Stanford, California, United States of America; Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, California, United States of America; The Howard Hughes Medical Institute, Stanford University, Stanford, California, United States of America.
4: Infectious Diseases Division, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America; Department of Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
5: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America; Department of Laboratory Medicine, University of Washington, Seattle, Washington, United States of America.
6: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America; Department of Statistics, University of Washington, Seattle, Washington, United States of America.

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