Linear independence of pairwise comparisons of DNA microarray data.

MOTIVATION: For DNA microarrays, the gain in certainty by performing multiple experimental repeats is offset by the high cost of each experiment. In a typical experiment, two independent measurements (that is, data from two separate arrays) are combined to yield a single comparative index per gene. Thus, although one uses 2n arrays and performs 2n independent measurements, one obtains only n comparative measurements. We addressed the question: how many of the potential n2 comparisons derivable from such data are actually independent, and what effect do these additional comparisons have on the false positive rate.
RESULTS: We show there are precisely 2n - 1 independent comparisons available from among the n2 possibilities. Applying these additional n - 1 independent comparisons to experimental and simulated data reduced the false positive rate by as much as 10-fold, with excellent agreement between experimental and theoretical false positive rates.