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).

1 |

A list called `hendfalk`

containing:

`p` |
Vector of 3,170 p-values of tests comparing BRCA1 to BRCA2. |

`stat` |
Vector of 3,170 absolute two-sample t-statistics comparing BRCA1 to BRCA2. |

`stat0` |
A
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.

http://www.pnas.org/content/100/16/9440.full

`qvalue`

, `empPvals`

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)
``` |

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