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ISAC's classification results file format
Author(s) -
Spidlen Josef,
Bray Chris,
Brinkman Ryan R.
Publication year - 2015
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.22586
Subject(s) - computer science , pairwise comparison , sorting , event (particle physics) , visualization , process (computing) , class (philosophy) , data mining , gating , artificial intelligence , pattern recognition (psychology) , information retrieval , programming language , biology , physics , quantum mechanics , physiology
Identifying homogenous sets of cell populations in flow cytometry is an important process for sorting and selecting populations of interests for further data acquisition and analysis. Many computational methods are now available to automate this process, with several algorithms partitioning cells based on high‐dimensional separation versus the traditional pairwise two‐dimensional visualization approach of manual gating. ISAC's classification results file format was developed to exchange the results of both manual gating and algorithmic classification approaches in a standardized way based on per event based classifications, including the potential for soft classifications expressed as the probability of an event being a member of a class. © 2014 International Society for Advancement of Cytometry