FIND: A new software tool and development platform for enhanced multicolor flow analysis

摘要: Flow Cytometry is a process by which cells, and other microscopic particles, can be identified, counted, sorted mechanically through the use of hydrodynamic pressure laser-activated fluorescence labeling. As immunostained cells pass individually flow chamber instrument, laser pulses cause emissions that are recorded digitally for later analysis as multidimensional vectors. Current, widely adopted software limits users to manual separation events based on viewing two or three simultaneous dimensions. While this may adequate experiments using four fewer colors, advances have lead cytometers capable recording 20 different colors simultaneously. In addition, mass-spectrometry machines at least 100 separate channels being developed. Analysis such high-dimensional data visual exploration alone error-prone susceptible unnecessary bias. Fortunately, field Data Mining provides many tools automated group classification multi-dimensional data, algorithms been adapted created cytometry. However, majority research has not made available packages and, such, in wide use. We developed new application multi-color cytometry data. The main goals effort were provide user-friendly tool gating (classification) well platform development dissemination tools. With software, easily load single multiple sets, perform event classification, graphically compare results within between experiments. also make simple plugin system enables researchers implement share their classification/population discovery algorithms. FIND (Flow Investigation N-Dimensions) presented here powerful, environment providing common implementation distribution techniques around world.