flowFrame and
identify the two largest peaks. We then
select as the cutpoint the value at which the minimum density is attained
between the two peaks of interest.mindensity(fr, channel, filterId = "", positive = TRUE, pivot = FALSE,
gate_range = NULL, min = NULL, max = NULL, peaks = NULL, ...)flowFrame objectTRUE, 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)TRUE, we choose as the two peaks the
largest peak and its neighboring peak. See details.positive is TRUE and the
maximum value of the range otherwise.numeric vector. If not given , then perform peak detection first by .find_peaksrectangleGate object based on the minimum density cutpointlink{density} function. However, if pivot is
TRUE, we choose the largest peak and its neighboring peak as the two
peaks of interest. In this case, the neighboring peak is the peak immediately
to the left of the largest peak if positive is TRUE. Otherwise,
the neighboring peak is selected as the peak to the right.In the special case that there is only one peak, we are conservative and set
the cutpoint as the min(x) if positive is TRUE, and the
max(x) otherwise.
gate <- mindensity(fr, channel = "APC-A") # fr is a flowFrameRun the code above in your browser using DataLab