amptester.Rd

\name{amptester}
\alias{amptester}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Amplification test
}
\description{
The function \code{\link[chipPCR]{amptester}} can be used to test if an 
amplification is significant.
}
\usage{
amptester(y, manual = FALSE, noiselevel = 0.08, background = NULL)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
  \item{y}{
        is a vector containing the fluorescence values.
}
  \item{manual}{
	switches between a statistical test (based on a Student's t-test) or 
	manual test for a positive amplification signal.
}
  \item{noiselevel}{
	can be set to a user defined value as threshold for a significant 
	amplification signal.
}
  \item{background}{
	is the range of the background signal in the amplification curve. The 
	values can be added by 	the used or taken from the 
	\code{\link[chipPCR]{bg.max}} function.
}
}
\details{
  The function tries to estimate if a amplification process is taking place. 
  To do so a several instances of tests are includes. The first involves a 
  semiautomatic test if the range of the background is lower than the range of 
  the assumed signal. To differ between the ranges an instance of 
  \code{\link[chipPCR]{bg.max}} is used. Herein, the function assumes that an 
  amplification takes place in case the signal of the amplification is larger 
  than the mean + 5SD than the background. The automatic test uses a Student's 
  t-Test \code{\link[stats]{t.test}} to compare the the beginning and the end 
  of the data. The input values are delivered by \code{\link[utils]{head}} 
  and \code{\link[utils]{tail}}, respectively. For other methods please refer 
  to the references listed below. Instead of assigning a zero to negative 
  amplification reaction uses the current implementation of 
  \code{\link[chipPCR]{amptester}} very small random values. This is because 
  some post function might fail in case all values are set to zero.
}

\references{

Frank, D. N. BARCRAWL and BARTAB: software tools for the design and 
implementation of barcoded primers for highly multiplexed DNA sequencing 
\emph{BMC bioinformatics}, 2009, Vol. 10, pp. 362

Peirson, S. N., Butler, J. N. and Foster, R. G. Experimental validation of 
novel and conventional approaches to quantitative real-time PCR data analysis 
\emph{Nucleic Acids Research}, 2003, Vol. 31(14), pp. e73-e73

Rao, X., Lai, D. and Huang, X. A New Method for Quantitative Real-Time 
Polymerase Chain Reaction Data Analysis \emph{Journal of Computational 
Biology}, 2013, Vol. 20(9), pp. 703-711

Ruijter, J. M., Ramakers, C., Hoogaars, W. M. H., Karlen, Y., Bakker, O., 
Hoff, M. J. B. v. d. and Moorman, A. F. M. Amplification efficiency: linking 
baseline and bias in the analysis of quantitative PCR data, \emph{Nucleic 
Acids Research}, 2009, Vol. 37(6), pp. e45-e45

Rutledge, R. G. and Stewart, D. A kinetic-based sigmoidal model for the 
polymerase chain reaction and its application to high-capacity absolute 
quantitative real-time PCR \emph{BMC biotechnology}, 2008, Vol. 8, pp. 47

Tichopad, A., Dilger, M., Schwarz, G. and Pfaffl, M. W. Standardized 
determination of real-time PCR efficiency from a single reaction set-up 
\emph{Nucleic Acids Research}, 2003, Vol. 31(20), pp. e122

Wilhelm, J., Pingoud, A. and Hahn, M. SoFAR: software for fully automatic 
evaluation of real-time PCR data \emph{BioTechniques}, 2003, Vol. 34(2), 
pp. 324-332

Zhao, S. and Fernald, R. D. Comprehensive Algorithm for Quantitative Real-Time 
Polymerase Chain Reaction \emph{Journal of computational biology: a journal of 
computational molecular cell biology}, 2005, Vol. 12(8), pp. 1047-1064

}
\author{
Stefan Roediger, Michal Burdukiewicz
}

\examples{
# Example to test an amplification reaction.
# Simulate first a positive amplification curve with 35 cycles and than a 
# negative amplification curve with 35 cycles. The negative amplification
# curve is created from a normal distribution
cyc <- seq(1, 35, 1)
# Coefficients of a 5 parameter sigmoid model. 
b <- -14.29; c <- 0.18; d <- 39.18; e <- 19.14
fluo.pos <- c + (d - c)/(1 + exp(b * (log(cyc) - log(e))))
fluo.neg <- rnorm(35)

plot(NA, NA, xlim = c(1, 35), ylim = c(-1, 40), xlab = "Cycles", 
     ylab = "Fluorescence", 
     main = "Simulation of a qPCR with 35 Cycles", type = "b")
points(amptester(fluo.pos), type = "b", pch = 20)
points(amptester(fluo.neg), type = "b", col = "red", pch = 20)

legend(1,40, c("Positive", "Negative Control (noise)"), 
	pch = 20, col = c(1,2), lwd = 2)
}

% Add one or more standard keywords, see file 'KEYWORDS' in the
% R documentation directory.
\keyword{ amplification }
\keyword{ threshold }