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GateFinder: projection-based gating strategy optimization for flow and mass cytometry
- Aghaeepour, Nima;
- Simonds, Erin F;
- Knapp, David JHF;
- Bruggner, Robert V;
- Sachs, Karen;
- Culos, Anthony;
- Gherardini, Pier Federico;
- Samusik, Nikolay;
- Fragiadakis, Gabriela K;
- Bendall, Sean C;
- Gaudilliere, Brice;
- Angst, Martin S;
- Eaves, Connie J;
- Weiss, William A;
- Fantl, Wendy J;
- Nolan, Garry P
- Editor(s): Wren, Jonathan
- et al.
Published Web Location
https://doi.org/10.1093/bioinformatics/bty430Abstract
Motivation
High-parameter single-cell technologies can reveal novel cell populations of interest, but studying or validating these populations using lower-parameter methods remains challenging.Results
Here, we present GateFinder, an algorithm that enriches high-dimensional cell types with simple, stepwise polygon gates requiring only two markers at a time. A series of case studies of complex cell types illustrates how simplified enrichment strategies can enable more efficient assays, reveal novel biomarkers and clarify underlying biology.Availability and implementation
The GateFinder algorithm is implemented as a free and open-source package for BioConductor: https://nalab.stanford.edu/gatefinder.Supplementary information
Supplementary data are available at Bioinformatics online.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
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