test_panel {dpcR} | R Documentation |
Dispersion Test for Spatial Point Pattern in Array dPCR Based on Quadrat Counts
Description
Performs a test of Complete Spatial Randomness for each
plate. This function is a wrapper around quadrat.test
function working directly on the objects of adpcr
.
Usage
test_panel(X, nx = 5, ny = 5, alternative = c("two.sided", "regular",
"clustered"), method = c("Chisq", "MonteCarlo"), conditional = TRUE,
nsim = 1999)
Arguments
X |
Object of the |
nx |
Number of quadrats in the x direction. |
ny |
Number of quadrats in the y direction. |
alternative |
|
method |
|
conditional |
|
nsim |
The number of simulated samples to generate when method="MonteCarlo". |
Details
Under optimal conditions, the point pattern of dPCR events (e.g., positive droplet & negative droplets) should be randomly distrubuted over a planar chip. This function verifies this assumption using chi-square or Monte Carlo test. Arrays with non-random patterns should be checked for integrity.
Value
A list
of objects of class "htest"
with the length equal to the
number of plates (minimum 1).
Note
A similar result can be achived by using adpcr2ppp
and
quadrat.test
. See Examples.
Author(s)
Adrian Baddeley, Rolf Turner, Michal Burdukiewcz, Stefan Roediger.
References
http://www.spatstat.org/
Examples
many_panels <- sim_adpcr(m = 400, n = 765, times = 1000, pos_sums = FALSE,
n_panels = 5)
test_panel(many_panels)
#test only one plate
test_panel(extract_run(many_panels, 3))
#do test_panel manually
library(spatstat.explore)
ppp_data <- adpcr2ppp(many_panels)
lapply(ppp_data, function(single_panel) quadrat.test(single_panel))