dpcR (version 0.1.4.0)

test_counts: Test counts

Description

The test for comparing counts from two or more digital PCR experiments.

Usage

test_counts(input, model = "binomial", conf.level = 0.95)

Arguments

input

adpcr or dpcr object with with "nm" type.

model

may have one of following values: binomial, poisson, prop, ratio.

conf.level

confidence level of the intervals and groups.

Value

• an object of class count_test.

Details

test_counts fits counts data from different digital PCR experiments to Generalized Linear Model (using quasibinomial or quasipoisson family). Comparisions between single experiments utilize Tukey's contrast and multiple t-tests (as provided by function glht).

References

Bretz F, Hothorn T, Westfall P, Multiple comparisons using R. Boca Raton, Florida, USA: Chapman & Hall/CRC Press (2010).

See Also

Functions used by test_counts:

• glm,
• glht,
• cld,
• prop.test,
• rateratio.test

GUI presenting capabilities of the test: test_counts_gui.

Examples

adpcr1 <- sim_adpcr(m = 10, n = 765, times = 1000, pos_sums = FALSE, n_panels = 3)
adpcr2 <- sim_adpcr(m = 60, n = 550, times = 1000, pos_sums = FALSE, n_panels = 3)
adpcr3 <- sim_adpcr(m = 10, n = 600, times = 1000, pos_sums = FALSE, n_panels = 3)

#compare experiments using binomial regression
two_groups_bin <- test_counts(bind_dpcr(adpcr1, adpcr2), model = "binomial")
summary(two_groups_bin)
plot(two_groups_bin)
#plot aggregated results
plot(two_groups_bin, aggregate = TRUE)
#get coefficients
coef(two_groups_bin)

#this time use Poisson regression
two_groups_pois <- test_counts(bind_dpcr(adpcr1, adpcr2), model = "poisson")
summary(two_groups_pois)
plot(two_groups_pois)

#see how test behaves when results aren't significantly different
one_group <- test_counts(bind_dpcr(adpcr1, adpcr3))
summary(one_group)
plot(one_group)