P-values and test-statistics from the Hedenfalk et al. (2001) gene expression dataset
The data from the breast cancer gene expression study of Hedenfalk et al. (2001) were obtained and analyzed. A comparison was made between 3,226 genes of two mutation types, BRCA1 (7 arrays) and BRCA2 (8 arrays). The data included here are p-values, test-statistics, and permutation null test-statistics obtained from a two-sample t-test analysis on a set of 3170 genes, as described in Storey and Tibshirani (2003).
A list called
Vector of 3,170 p-values of tests comparing BRCA1 to BRCA2.
Vector of 3,170 absolute two-sample t-statistics comparing BRCA1 to BRCA2.
3,170 by 100 matrix of absolute two-sample t-statistics from 100 independent
permutations of the BRCA1 and BRCA2 labels; the row
Hedenfalk I et al. (2001). Gene expression profiles in hereditary breast cancer. New England Journal of Medicine, 344: 539-548.
Storey JD and Tibshirani R. (2003). Statistical significance for genome-wide
studies. Proceedings of the National Academy of Sciences, 100: 9440-9445.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
# import data data(hedenfalk) stat <- hedenfalk$stat stat0 <- hedenfalk$stat0 #vector from null distribution p.pooled <- empPvals(stat=stat, stat0=stat0) p.testspecific <- empPvals(stat=stat, stat0=stat0, pool=FALSE) #compare pooled to test-specific p-values qqplot(p.pooled, p.testspecific); abline(0,1) # calculate q-values and view results qobj <- qvalue(p.pooled) summary(qobj) hist(qobj) plot(qobj)
Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.