fr
into K
clusters.flowClust.1d(fr, params, filterId = "", K = NULL, trans = 0,
positive = TRUE, prior = NULL, criterion = c("BIC", "ICL"),
cutpoint_method = c("boundary", "min_density", "quantile", "posterior_mean",
"prior_density"), neg_cluster = 1, cutpoint_min = NULL,
cutpoint_max = NULL, min = NULL, max = NULL, quantile = 0.99,
quantile_interval = c(0, 10), plot = FALSE, debug = FALSE, ...)
flowFrame
objectcharacter
channel to be gated oncharacter
string that identifies the filter created.flowClust
, this value cannot be 2.TRUE
, then the gate consists of the entire real
line to the right of the cutpoint. Otherwise, the gate is the entire real
line to the left of the cutpoint. (Default: TRUE
)flowClust
. If NULL
, no prior is used.K
is NULL
or if length(K) > 1
. The value selected
is passed to flowClust
.flowClust
model? See Details.neg_cluster
and neg_cluster + 1
.NULL
(default), there is no minimum
cutpoint value.NULL
(default), there is no maximum
cutpoint value.NULL
(default), no truncation is applied.NULL
(default), no truncation is applied.cutpoint_method
. If the cutpoint_method
is not set
to quantile
, this argument is ignored.cutpoint_method
is not set to quantile
, this argument is
ignored.flowClust
model should be plotted along with the cutpointlogical
indicating whether to carry the prior and posterious with the gate
for debugging purpose. Default is FALSE.flowClust
rectangleGate
object consisting of all values beyond the
cutpoint calculatedcutpoint_method
is min_density
, then the cutpoint is the point
at which the density between the first and second smallest cluster centroids
is minimum.gate <- flowClust.1d(fr, params = "APC-A", K =2) # fr is a flowFrame
Run the code above in your browser using DataLab