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.
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.
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.
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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)