Methods for Function summary

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Description

Expands function summary allowing printing summaries objects of the class adpcr to or ddpcr.

Arguments

object

object of class adpcr, ddpcr or qdpcr.

print

if FALSE, no output is printed.

Details

The function prints a summary of the dPCR reaction, including k (number of positive chambers), n (total number of chambers), estimated lambda and m (number of molecules per plate), as well as confidence intervals for the last two variables.

Value

The data frame with estimated values of lambda, m and corresponding confidence intervals.

Note

If summary is used on an object containing results of many experiments, all experiments would be independently summarized. Currently supported only for objects of class adpcr.

Author(s)

Michal Burdukiewicz, Stefan Roediger.

References

Bhat S, Herrmann J, Corbisier P, Emslie K, Single molecule detection in nanofluidic digital array enables accurate measurement of DNA copy number. Analytical and Bioanalytical Chemistry 2 (394), 2009.

Dube S, Qin J, Ramakrishnan R, Mathematical Analysis of Copy Number Variation in a DNA Sample Using Digital PCR on a Nanofluidic Device. PLoS ONE 3(8), 2008.

Examples

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# array dpcr
# Simulates a chamber based digital PCR with m total number of template molecules  
# and n number of chambers per plate and assigns it as object ptest of the class 
# adpcr for a single panel. The summary function on ptest gets assigned to summ 
# and the result with statistics according to Dube et al. 2008 and Bhat et al. 2009 
# gets printed.
ptest <- sim_adpcr(m = 400, n = 765, times = 5, dube = FALSE, n_panels = 1)
summ <- summary(ptest) #save summary
print(summ)

# multiple experiments
# Similar to the previous example but with five panels
ptest <- sim_adpcr(m = 400, n = 765, times = 5, dube = FALSE, n_panels = 5)
summary(ptest)

# droplet dpcr - fluorescence
# Simulates a droplet digital PCR with m = 7 total number of template molecules 
# and n = 20 number of  droplets. The summary function on dropletf gives the 
# statistics according to Dube et al. 2008 and Bhat et al. 2009. The fluo parameter 
# is used to change the smoothness of the fluorescence curve and the space between
#  two consecutive measured peaks (droplets).
dropletf <- sim_ddpcr(m = 7, n = 20, times = 5, fluo = list(0.1, 0))
summary(dropletf)

# droplet dpcr - number of molecules
# Similar to the previous example but with five panels but without and modifications
#  to the peaks.
droplet <- sim_ddpcr(m = 7, n = 20, times = 5)
summary(droplet)

# Visualize the results of dropletf and dropletf
# The curves of dropletf are smoother.
par(mfrow = c(1,2))
plot(dropletf, main = "With fluo parameter", type = "l")
plot(droplet, main = "Without fluo parameter", type = "l")

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