Description Usage Arguments Details Value Note Author(s) References See Also Examples
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
.
1 2 3 | test_panel(X, nx = 5, ny = 5, alternative = c("two.sided", "regular",
"clustered"), method = c("Chisq", "MonteCarlo"), conditional = TRUE,
nsim = 1999)
|
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". |
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.
A list
of objects of class "htest"
with the length equal to the
number of plates (minimum 1).
A similar result can be achived by using adpcr2ppp
and
quadrat.test
. See Examples.
Adrian Baddeley, Rolf Turner, Michal Burdukiewcz, Stefan Roediger.
http://www.spatstat.org/
1 2 3 4 5 6 7 8 9 10 11 | 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
require(spatstat)
ppp_data <- adpcr2ppp(many_panels)
lapply(ppp_data, function(single_panel) quadrat.test(single_panel))
|
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