qtlc (version 1.0)

summat2D: Summarize matrices

Description

The function summarize matrices areas of the located spot matrices.

Usage

summat2D(object)

Arguments

object

S3 object of working TLC

Value

Returns S3 object with new values object$spot_sums.

Examples

# This interactive example shows the most
# common usage of the qtlc library.
fname01 <- system.file("extdata", "test025to100sp.tiff", package="qtlc")
testTLC <- createTLC(fname01, RGB=FALSE)
print(testTLC)

# now using mouse select the spots with testTLC <- spot2D(testTLC)
# but, for automatic tests, we'll imitate that step...
testTLC$spots$x <- c(40.93354, 83.18687, 121.59899, 160.01111, 203.54485,
                     239.39616, 280.36909, 320.06161, 362.31494, 399.44666,
                     439.13919, 480.11211, 518.52423, 559.49716, 599.18969)
testTLC$spots$y <- c(198.3160, 198.3160, 199.2833, 198.3160, 198.3160,
                     198.3160, 198.3160, 198.3160, 197.3487, 198.3160,
                     199.2833, 198.3160, 199.2833, 199.2833, 199.2833)

# and now the select2D selects 30x30 pixels areas around spots
testTLC <- select2D(testTLC, 30, 30)

# forming spots matrices
testTLC <- matrices2D(testTLC)

# and finaly sumarizing spots areas
testTLC <- summat2D(testTLC)

#eventually we'll examine the linear model
C <- rep(c(0.25, 1, 6.25, 25, 100), each=3) #imaginative concentrations
#now creates data frame with values
testTLC.df <- data.frame(C, testTLC$spot_sums)
names(testTLC.df) <- c("Concentration", "Signal")
# now the linear model
testTLC.lm <- with(testTLC.df, lm(Signal ~ Concentration))
# and finaly the plot
plot(testTLC.df)
abline(testTLC.lm)
summary(testTLC.lm)