Gene expression dataset from Rodwell et al. (2004)
Gene expression measurements from kidney samples were obtained from 72 human subjects ranging in age from 27 to 92 years. Only one array was obtained per individual, and the age and sex of each individual were recorded.
kidcov: A 133 rows by 6 columns data frame detailing the study design.
kidexpr: A 500 rows by 133 columns matrix of gene expression values, where each row corresponds to a different probe-set and each column to a different tissue sample.
age: A vector of length 133 giving the age of each sample.
sex: A vector of length 133 giving the sex of each sample.
These data are a random subset of 500 probe-sets from the total number of
probe-sets in the original data set. To download the full data set, go to
sex are contained
kidcov data frame.
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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# import data data(kidney) sex <- kidney$sex age <- kidney$age kidexpr <- kidney$kidexpr # create model de_obj <- build_study(data = kidexpr, adj.var = sex, tme = age, sampling = "timecourse", basis.df = 4) # use the ODP/lrt method to determine significant genes de_odp <- odp(de_obj, bs.its=10) de_lrt <- lrt(de_obj, nullDistn = "bootstrap", bs.its = 10) # summarize significance results summary(de_odp)
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