test_panel: Dispersion Test for Spatial Point Pattern in Array dPCR Based...

In michbur/dpcR: Digital PCR Analysis

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 adpcr class containing data from one or more panels.
nx	Number of quadrats in the x direction.
ny	Number of quadrats in the y direction.
alternative	character string (partially matched) specifying the alternative hypothesis.
method	character string (partially matched) specifying the test to use: either "Chisq" for the chi-squared test (the default), or "MonteCarlo" for a Monte Carlo test.
conditional	logical. Should the Monte Carlo test be conducted conditionally upon the observed number of points of the pattern? Ignored if method="Chisq".
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/

See Also

quadrat.test.

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
require(spatstat.core)
require(spatstat.geom)
ppp_data <- adpcr2ppp(many_panels)
lapply(ppp_data, function(single_panel) quadrat.test(single_panel))

michbur/dpcR documentation built on Nov. 17, 2022, 5:02 a.m.