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C85.Rd
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\name{C85}
\alias{C85}
\docType{data}
\title{
Helicase Dependent Amplification of Vimentin using the VideoScan Platform
}
\description{
A Helicase Dependent Amplification (HDA) of Vimentin (Vim) was performed. The
VideoScan Platform (Roediger et al. (2013)) was used to monitor the
amplification. The HDA was performed at 65 degree Celsius. Three
concentrations of input DNA (D1, D2, D3) were used.
}
\usage{data(C85)}
\format{
A data frame with 301 observations on the following 5 variables.
\describe{
\item{\code{Cycle}}{Cycles HDA measurements.}
\item{\code{t.D1}}{Dilution 1, elapsed time during HDA in seconds.}
\item{\code{MFI.D1}}{Dilution 1, fluorescence.}
\item{\code{t.D2}}{Dilution 2, elapsed time during HDA in seconds.}
\item{\code{MFI.D2}}{Dilution 2, fluorescence.}
\item{\code{t.D3}}{Dilution 3, elapsed time during HDA in seconds.}
\item{\code{MFI.D3}}{Dilution 3, fluorescence.}
}
}
\details{
To perform an isothermal amplification in VideoScan, standard conditions for
the IsoAmp(R) III Universal tHDA Kit (Biohelix) were used. Primers and
templates are described in Roediger et al. (2013). The reaction was composed
of reaction mix A)10 micro L A. bidest, 1.25 micro L 10xbuffer, 0.75 micro L
primer(150nM final), 0.5 micro L template plasmid. Preincubation: This mixture
was incubated for 2 min at 95 degree. Celsius and immediately placed on ice.
Reaction mix B) 5 micro L A. bidest., 1.25 micro L 10x buffer, 2 micro L NaCl,
1.25 micro L MgSO4, 1,75 micro L dNTPs, 0.25 micro L EvaGreen, 1 micro L
enzyme mix. The mix was covered with 50 micro L mineral oil. The fluorescence
measurement in VideoScan HCU started directly after adding buffer B at 65
degree Celsius. A 1x (D1), a 1:10 dilution (D2) and a 1:100 (D3) dilution were
tested.
Temperature profile (after Preincubation):
- 60 seconds at 65 degree Celsius
- 11 seconds at 55 degree Celsius && Measurement
}
\source{
Claudia Deutschmann & Stefan Roediger, BTU Cottbus - Senftenberg, Senftenberg,
Germany
}
\references{
A Highly Versatile Microscope Imaging Technology Platform for the Multiplex
Real-Time Detection of Biomolecules and Autoimmune Antibodies. S. Roediger,
P. Schierack, A. Boehm, J. Nitschke, I. Berger, U. Froemmel, C. Schmidt,
M. Ruhland, I. Schimke, D. Roggenbuck, W. Lehmann and C. Schroeder.
\emph{Advances in Biochemical Bioengineering/Biotechnology}. 133:33--74, 2013.
\url{http://www.ncbi.nlm.nih.gov/pubmed/22437246}
}
\examples{
data(C85)
# First example
plot(NA, NA, xlim = c(0,85), ylim = c(0,1), xlab = "Time [min]",
ylab = "Fluorescence", main = "HDA amplification")
points(C85[, 2]/60, C85[, 3], type = "b", col = 1, pch = 20)
points(C85[, 4]/60, C85[, 5], type = "b", col = 2, pch = 20)
points(C85[, 6]/60, C85[, 7], type = "b", col = 3, pch = 20)
legend(40, 0.5, c("D1, 1x", "D2, 1:10", "D3, 1:100"), col = c(1:3),
pch = rep(20,3))
# Second example
plot(NA, NA, xlim = c(0,30), ylim = c(0,0.8), xlab = "Time [min]",
ylab = "Fluorescence", main = "HDA amplification")
points(C85[, 2]/60, C85[, 3], type = "b", col = 1, pch = 20)
points(C85[, 2]/60, smoother(C85[, 2]/60, C85[, 3],
method = "savgol"), type = "b", col = 2, pch = 20)
points(C85[, 2]/60, smoother(C85[, 2]/60, C85[, 3],
method = "smooth"), type = "b", col = 3, pch = 20)
points(C85[, 2]/60, smoother(C85[, 2]/60, C85[, 3],
method = "mova"), type = "b", col = 4, pch = 20)
legend(1, 0.8, c("D1, raw", "D1, savgol", "D1, smooth", "D1, mova"),
col = c(1:4), pch = rep(20,4))
# Third example
# Comparison of Lowess, Moving average and splines to smooth amplification
# curve data of
# a HDA using the VideoScan HCU for amplification and monitoring.
xrange <- 2:2400
plot(NA, NA, xlim = c(0,85), ylim = c(0,1), xlab = "Time [min]",
ylab = "Fluorescence", main = "VideoScan HCU HDA amplification - Raw data")
points(C85[, 2]/60, C85[, 3], type = "b", col = 1, pch = 20)
points(C85[, 4]/60, C85[, 5], type = "b", col = 2, pch = 20)
points(C85[, 6]/60, C85[, 7], type = "b", col = 3, pch = 20)
legend(40, 0.5, c("D1, 1x", "D2, 1:10", "D3, 1:100"), col = c(1:3),
pch = rep(20,3))
text(1,0.9, "A)", cex = 3)
plot(NA, NA, xlim = c(0,40), ylim = c(-0.05,0.3), xlab = "time [min]",
ylab = "RFI", main = "VideoScan HCU HDA amplification - Moving average")
movaww <- seq(1,17,4)
for (i in 1:length(movaww)) {
for (j in c(2,4,6)) {
tmp <- data.frame(na.omit(C85[xrange, j])/60, na.omit(C85[xrange, j+1]))
tmp.out <- smoother(tmp[, 1], tmp[, 2], method = "mova", movaww = movaww[i],
bg.outliers = TRUE)
lines(data.frame(tmp[, 1], tmp.out), type = "l", pch = 20, cex = 0.5,
col = i)
}
}
text(1,0.28, "B)", cex = 3)
legend(2, 0.2, c("D1, 1x", "D2, 1:10", "D3, 1:100"), col = c(1:3),
pch = rep(20,3))
legend(25,0.18, paste("movaww : ", movaww), pch = 20, lwd = 2,
col = 1:length(movaww))
plot(NA, NA, xlim = c(0,40), ylim = c(-0.05,0.3), xlab = "time [min]",
ylab = "RFI", main = "VideoScan HCU HDA amplification - Cubic Spline")
df.fact <- seq(0.5,0.9,0.1)
for (i in 1:length(df.fact)) {
for (j in c(2,4,6)) {
tmp <- data.frame(na.omit(C85[xrange, j])/60, na.omit(C85[xrange, j+1]))
tmp.out <- smoother(tmp[, 1], tmp[, 2], method = "smooth",
df.fact = df.fact[i], bg.outliers = TRUE)
lines(data.frame(tmp[, 1], tmp.out), type = "l", pch = 20,
cex = 0.5, col = i)
}
}
text(1,0.28, "C)", cex = 3)
legend(2, 0.2, c("D1, 1x", "D2, 1:10", "D3, 1:100"), col = c(1:3),
pch = rep(20,3))
legend(25,0.18, paste("df.fact : ", df.fact), pch = 20, lwd = 2,
col = 1:length(df.fact))
plot(NA, NA, xlim = c(0,40), ylim = c(-0.05,0.3), xlab = "time [min]",
ylab = "RFI", main = "VideoScan HCU HDA amplification - Lowess")
f <- seq(0.01,0.2,0.04)
for (i in 1:length(f)) {
for (j in c(2,4,6)) {
tmp <- data.frame(na.omit(C85[xrange, j])/60, na.omit(C85[xrange, j+1]))
tmp.out <- smoother(tmp[, 1], tmp[, 2], method = "lowess", f = f[i],
bg.outliers = TRUE)
lines(data.frame(tmp[, 1], tmp.out), type = "l", pch = 20, cex = 0.5,
col = i)
}
}
text(1,0.28, "D)", cex = 3)
legend(2, 0.2, c("D1, 1x", "D2, 1:10", "D3, 1:100"), col = c(1:3),
pch = rep(20,3))
legend(25,0.18, paste("f : ", f), pch = 20, lwd = 2, col = 1:length(f))
plot(NA, NA, xlim = c(0,40), ylim = c(-0.05,0.3), xlab = "time [min]",
ylab = "RFI", main = "VideoScan HCU HDA amplification -
Friedman's ''super smoother''")
span <- seq(0.01,0.05,0.01)
for (i in 1:length(span)) {
for (j in c(2,4,6)) {
tmp <- data.frame(na.omit(C85[xrange, j])/60, na.omit(C85[xrange, j+1]))
tmp.out <- smoother(tmp[, 1], tmp[, 2], method = "supsmu", span = span[i],
bg.outliers = TRUE)
lines(data.frame(tmp[, 1], tmp.out), type = "l", pch = 20, cex = 0.5,
col = i)
}
}
text(1,0.28, "E)", cex = 3)
legend(2, 0.2, c("D1, 1x", "D2, 1:10", "D3, 1:100"), col = c(1:3),
pch = rep(20,3))
legend(25,0.18, paste("span : ", span), pch = 20, lwd = 2, col = 1:length(span))
}
\keyword{ datasets }
\keyword{ HDA }
\keyword{ EvaGreen }
\keyword{ HCU }
\keyword{ VIM }
\keyword{ VideoScan }