Flow/Mass Cytometry Gating via Spatial Kernel Density Estimation
c(person(given = "Ian D.",
family = "Buller",
role = c("aut", "cre", "cph"),
email = "ian.buller@nih.gov",
comment = c(ORCID = "0000-0001-9477-8582")),
person(given = "Elena",
family = "Hsieh",
role = "ctb",
email = "elena.hsieh@cuanschutz.edu",
comment = c(ORCID = "0000-0003-3969-6597")),
person(given = "Debashis",
family = "Ghosh",
role = "ctb",
email = "debashis.ghosh@cuanschutz.edu",
comment = c(ORCID = "0000-0001-6618-1316")),
person(given = "Lance A.",
family = "Waller",
role = "ctb",
email = "lwaller@emory.edu",
comment = c(ORCID = "0000-0001-5002-8886")),
person(given = "NCI",
role = "cph"))
Estimates statistically significant 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 markers to examine features of cells that may be different between
groups. For a two-group comparison, the 'gateR' package uses the spatial relative risk
function that is 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>.
fields, graphics, grDevices, lifecycle, raster, rlang, sparr,
SpatialPack, spatstat.geom, stats, tibble, tools, utils
dplyr, flowWorkspaceData, ncdfFlow, R.rsp, spelling,
testthat, usethis

Estimates statistically significant 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 markers to examine features of cells that may be different between
groups. 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>.
fields, graphics, grDevices, lifecycle, raster, rlang, sparr,
SpatialPack, spatstat.geom, stats, tibble
dplyr, R.rsp, spelling, testthat, usethis, utils