PMC:514539 / 14834-16919 JSONTXT

{"project":"2_test","denotations":[{"id":"15307894-16323966-8142008","span":{"begin":1248,"end":1250},"obj":"16323966"},{"id":"15307894-12702575-8142009","span":{"begin":1683,"end":1685},"obj":"12702575"},{"id":"15307894-12937144-8142010","span":{"begin":1686,"end":1688},"obj":"12937144"},{"id":"15307894-12702575-8142011","span":{"begin":1779,"end":1781},"obj":"12702575"},{"id":"15307894-12937144-8142012","span":{"begin":1908,"end":1910},"obj":"12937144"}],"text":"Test for ABA patterns (ABA Test)\nGenes that exhibit both significant s1 and s2 scores in this comparison may be considered 'ABA pattern genes' (Fig. 1); however, for stronger inference, permutation tests are also used to calculate s3, to determine, for a given gene, the number of samples from one group (A) that can expected to be distributed both in the upper and lower nth percentile tails of the intensity distribution of that gene in the other group (B); i.e., in the ABA (s3) or BAB (s4) pattern. These scores are not redundant to but rather allow for exploration of distribution-wise (upper and lower) false discovery rates. The application of the PPST test to find ABA patterns is called the 'ABA' test. Under the ABA test, differential expression of a gene may be deemed to be significant in both directions at once, i.e., simultaneously significantly over-expressed and under-expressed in a surprising number of patients in the case population. Both the PPST test and the ABA test will perform optimally when the variation in expression intensities in the normal sample population is well characterized.\nA collection of published microarray data sets we have placed 'on-tap' in the caGEDA (Gene Expression Data Analysis) web application [51] were subjected to the PPST test and the ABA test. To avoid idiosyncracies that can result from the study of extreme values, we ran the tests at a fairly relaxed Type 1 error risk (α = 0.05 in both tails, or α = 0.10 overall). To compare the self-consistency of the parametric t-test, the nonparametric t-test, the PPST test and the ABA test, we re-analyzed two published data sets from independent astrocytoma progression studies [52,53]. Details of these studies are available in the original papers. In brief, Khatua et al. [52] studied global gene expression profiles from 6 early stage and 7 late-stage astrocytoma patients, while van den boom et al. [53] studied global gene expression profiles from 8 early stage and 8 late-stage astrocytoma patients. We calculated the overlap in the gene lists using our online Overlap tool ."}