title: ISAC's classification results file format.
abstract: 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.
authors.affiliation: Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada.
authors.forename: Josef
authors.initials: J
authors.lastname: Spidlen
authors.forename: Chris
authors.initials: C
authors.lastname: Bray
authors.forename: Ryan R
authors.initials: RR
authors.lastname: Brinkman
mesh_terms: D000465:Algorithms; D001330:Electronic Data Processing / Q000592:standards*; D005434:Flow Cytometry / Q000592:standards*; D006801:Humans; D017410:Practice Guidelines as Topic; D012984:Software / Q000592:standards*
keywords: analysis interchange; classification; clustering; file format; flow cytometry; software interoperability; standard