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We note that the median t method is a special case of the ChipStat algorithm.
In contrast, for probe set 153041-at, the combined p method ranks this probe set as 603 while the median t method ranks it as 1822.
The Affymetrix Latin Square data provides an exception – the median t method does not agree well with combined p for the initial group of genes selected.
For probe set 151862-at, the median t method ranks this probe set as 698 while the combined p method ranks it as 1173.
Using three spike-in datasets and array data from a biological study, we compare the combined p method to the ANOVA method [ 8], Cyber-T [ 6], median t method [ 10], moderated t-test [ 4] and the original t-test.
Based on the rankings of known true positives and power by intensity we see that the combined p method offers slightly improved power as compared to the median t method for the Golden Spike and Gene Logic Tonsil datasets.
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This demonstrates that although the combined p and median t methods perform similarly, they weight evidence in different ways.
However, the main difference between the combined p and median t methods lies in how they weight evidence.
The combined p and median t methods are both based on probe level tests of significance and seem to rank genes similarly in many cases.
To examine the instances when the combined p and median t methods diverge, we consider probe sets 151862-at and 153401-at from the Golden Spike data.
With the goal of ranking genes in order of differential expression in mind, the combined p and median t methods perform well for all three datasets considered.
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