endotoxin: Gene expression dataset from Calvano et al. (2005) Nature
In jdstorey/edge: Extraction of Differential Gene Expression

Description Usage Format Value Note References Examples

The data provide gene expression measurements in an endotoxin study where four subjects were given endotoxin and four subjects were given a placebo. Blood samples were collected and leukocytes were isolated from the samples before infusion and at times 2, 4, 6, 9, 24 hours.

1	data(endotoxin)

endoexpr: A 500 rows by 46 columns data frame containing expression values.
class: A vector of length 46 containing information about which individuals were given endotoxin.
ind: A vector of length 46 providing indexing measurements for each individual in the experiment.
time: A vector of length 46 indicating time measurements.

endotoxin dataset

The data is a random subset of 500 genes from the full dataset. To download the full data set, go to http://genomine.org/edge/.

Storey JD, Xiao W, Leek JT, Tompkins RG, and Davis RW. (2005) Significance analysis of time course microarray experiments. PNAS, 102: 12837-12842.
http://www.pnas.org/content/100/16/9440.full

library(splines)
# import data
data(endotoxin)
ind <- endotoxin$ind
class <- endotoxin$class
time <- endotoxin$time
endoexpr <- endotoxin$endoexpr
cov <- data.frame(individual = ind, time = time, class = class)

# formulate null and full models in experiement
# note: interaction term is a way of taking into account group effects
mNull <- ~ns(time, df=4, intercept = FALSE) + class
mFull <- ~ns(time, df=4, intercept = FALSE) +
          ns(time, df=4, intercept = FALSE):class + class

# create deSet object
de_obj <- build_models(endoexpr, cov = cov, full.model = mFull,
                       null.model = mNull, ind = ind)

# Perform ODP/lrt statistic to determine significant genes in study
de_odp <- odp(de_obj, bs.its = 10)
de_lrt <- lrt(de_obj, nullDistn = "bootstrap", bs.its = 10)

# summarize significance results
summary(de_odp)