Difference between revisions of "OR1Expt.R"

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dim(dset)
 
dim(dset)
 
summary(dset)
 
summary(dset)
 +
 +
# ----------------------------- Dataset variables ----------------------------- #
 +
# Amount = 1,2,5 mu/g ingestion/injection
 +
# Timepoint = 1,2,3,4 days
 +
# Treatment OR1 gene/Sucrose control
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# AM = Administration method; feeding or injection
 +
# Response = RE (relative expression)
 +
 +
# 11:12, 8 May 2007 (NZST)~ Note: Sucrose control was only administered at Amount=1 11:12, 8 May 2007 (NZST)~
 +
 
# Convert names
 
# Convert names
 
colnames(dset)[4:5] <- c("AM","RE")
 
colnames(dset)[4:5] <- c("AM","RE")

Revision as of 23:12, 7 May 2007

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

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

sourceDir <- "/Volumes/HD2/Clinton/Data" filename <- dir(sourceDir, pattern="OR1.+\.txt")

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. Timepoint = 1,2,3,4 days
  4. Treatment OR1 gene/Sucrose control
  5. AM = Administration method; feeding or injection
  6. Response = RE (relative expression)
  1. 11:12, 8 May 2007 (NZST)~ Note: Sucrose control was only administered at Amount=1 11:12, 8 May 2007 (NZST)~
  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) xyplot( RE ~ Timepoint| AM * Treatment, data=dset, panel.superpose=dset$Amount, groups=Amount)

  1. Anova example
  2. help(aov), help(summary)

aovobj <- aov(RE ~ AM*Treatment, data=dset) summary(aovobj)