Gene expression dataset from Rodwell et al. (2004)

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Description

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.

Usage

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Format

  • 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.

Value

kidney dataset

Note

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 http://genomine.org/edge/. The age and sex are contained in kidcov data frame.

References

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

Examples

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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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