gateR-package {gateR}

The gateR Package: Flow/Mass Cytometry Gating via Spatial Kernel Density Estimation

Description

Estimates statistically significant fluorescent marker combination values within which one immunologically distinctive group (i.e., disease case) is more associated than another group (i.e., healthy control), successively, using various combinations (i.e., "gates") of fluorescent markers to examine features of cells that may be different between groups.

Details

For a two-group comparison, the 'gateR' package uses the spatial relative risk function estimated using the sparr package. Details about the sparr package methods can be found in the tutorial: Davies et al. (2018) doi:10.1002/sim.7577. Details about kernel density estimation can be found in J. F. Bithell (1990) doi:10.1002/sim.4780090616. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) doi:10.1002/sim.4780101112.

This package provides a function to perform a gating strategy for flow cytometry data. The 'gateR' package also provides basic visualization for each gate.

Key content of the 'gateR' package include:

Gating Strategy

gating Extracts cells within statistically significant combinations of fluorescent markers, successively, for a set of markers. Statistically significant combinations are identified using two-tailed p-values of a relative risk surface assuming asymptotic normality. This function is currently available for two-level comparisons of a single condition (e.g., case/control) or two conditions (e.g., case/control at time 1 and time 2). Provides functionality for basic visualization and multiple testing correction.

rrs Estimates a relative risk surface and computes the asymptotic p-value surface for a single gate with a single condition, including features for basic visualization. This function is used internally within the gating function to extract the points within the significant areas. This function can also be used as a standalone function.

lotrrs Estimates a ratio of relative risk surfaces and computes the asymptotic p-value surface for a single gate with two conditions, including features for basic visualization. This function is used internally within the gating function to extract the points within the significant areas. This function can also be used as a standalone function.

Flow Cytometry Data

randCyto A sample dataset containing information about flow cytometry data with two binary categorical variables. The data are a random subset of the 'extdata' data in the 'flowWorkspaceData' package found on Bioconductor https://bioconductor.org/packages/release/data/experiment/html/flowWorkspaceData.html and formatted for 'gateR' input.

Dependencies

The 'gateR' package relies heavily upon sparr, spatstat.geom, and terra. For a two-level comparison, the spatial relative risk function uses the risk function. The calculation of a Bonferroni correction for multiple testing accounting for the spatial correlation of the estimated surface uses the modified.ttest function. Basic visualizations rely on the image.plot function.

Author(s)

Ian D. Buller
Social & Scientific Systems, Inc., a division of DLH Corporation, Silver Spring, Maryland, USA (current); Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA (former); Environmental Health Sciences, James T. Laney School of Graduate Studies, Emory University, Atlanta, Georgia, USA. (original)

Maintainer: I.D.B. [e-mail]