Package: staRgate 1.1.0

staRgate: Automated gating pipeline for flow cytometry analysis to characterize the lineage, differentiation, and functional states of T-cells

An R-based automated gating pipeline for flow cytometry data designed to mimic the manual gating strategy of defining flow biomarker positive populations relative to a unimodal background population to include cells with varying intensities of marker expression. The pipeline’s main feature is a flexible density-based gating strategy capable of capturing varying scenarios based on marker expression patterns to analyze a 29-marker flow panel that characterizes T-cell lineage, differentiation, and functional states.

Authors:Jasme Lee [aut, cre], Matthew Adamow [aut], Colleen Maher [aut], Xiyu Peng [aut], Phillip Wong [aut], Fiona Ehrich [aut], Michael A Postow [aut], Margaret K Callahan [aut], Ronglai Shen [aut], Katherine S Panageas [aut], V foundation [fnd], MSK-MIND [fnd], NIH R01CA276286 [fnd], NIH P30CA008748 [fnd]