OR1Expt.R

Our Perl scripts. {{#security: Sven,Goldfinger}}

1. ------------------------- OR1 dataset analysis ------------------------------ #

if (.Platform$OS.type == 'unix' ) {

 sourceDir <- "/Volumes/HD2/Clinton/Data"

} else {

 sourceDir <- "H:\\AllRealtime\\Concentrationsexpts\\Stats"

} filename <- dir(sourceDir, pattern="OR1.+\.txt")

1. Check file path

cat("Filename is:" ,sep="\n") cat(filename, sep="\n") cat("Full path is:", sep="\n") cat(file.path(sourceDir, filename), sep="\n")

dset <- read.table(file.path(sourceDir, filename), sep="\t", header=TRUE)

dim(dset) summary(dset)

1. ----------------------------- Dataset variables ----------------------------- #
2. Amount = 1,2,5 mu/g ingestion/injection (3)
3. Timepoint = 1,2,3,4 days (4)
4. Treatment OR1 gene/Sucrose control (2)
5. AM = Administration method; feeding or injection (2)
6. Response = RE (relative expression)

1. Took each treatment, prescribed an amount and feed/injected catapillars at
2. time 0. Adult moths were distructively assessed 1,2,3,4 days after emergence.
3. No catapillars were harmed during this experiment!
4. ~.~.~ Note: Sucrose control was only administered at Amount=1 ~.~.~

1. Convert names

colnames(dset)[4:5] <- c("AM","RE")

library(lattice)

1. Formulas
2. y ~ x
3. y ~ x | z
4. y ~ x | (z * w)

1. help(xyplot), help(panel.superpose)

xyplot( RE ~ AM, data=dset)#, key=mykey)

1. help(simpleKey)

mykey <- simpleKey(text=paste("Amount =",unique(dset$Amount)), space="top", columns=3) xyplot( RE ~ Timepoint| Treatment * AM, data=dset, panel.superpose=dset$Amount, groups=Amount, key=mykey)

1. An example

xyplot( RE ~ Treatment| Timepoint , data=dset, panel.superpose=dset$Amount, groups=Amount, key=mykey, layout=c(4,1), between=list(x=0.3), aspect=1)

1. Anova example
2. help(aov), help(summary), help(formula)
3. Formulas
4. y ~ x
5. y ~ x * z
6. y ~ x/z conditional should example to y ~ x + x:z
7. y ~ x %in%z is the same as y ~ x:z
8. see also terms(formula(y~x/z)) etc

dset2 <- dset dset2$Amount <- factor(dset2$Amount) dset2$Timepoint <- factor(dset2$Timepoint) dset2$Treatment <- factor(dset2$Treatment) dset2$AM <- factor(dset2$AM)

1. Df wrong for Timepoint need to se factors

aovobj <- aov(RE ~ Treatment * Timepoint, data=dset2) summary(aovobj)

aovobj <- aov(RE ~ Treatment %in% Timepoint, data=dset) summary(aovobj)