Alexander Gordon

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BACKGROUND The number of genes declared differentially expressed is a random variable and its variability can be assessed by resampling techniques. Another important stability indicator is the frequency with which a given gene is selected across subsamples. We have conducted studies to assess stability and some other properties of several gene selection(More)
We introduce a nonparametric test intended for large-scale simultaneous inference in situations where the utility of distribution-free tests is limited because of their discrete nature. Such situations are frequently dealt with in microarray analysis where the number of tests is much larger than the sample size. The proposed test statistic is based on a(More)
The Bonferroni multiple testing procedure is commonly perceived as being overly conservative in large-scale simultaneous testing situations such as those that arise in microarray data analysis. The objective of the present study is to show that this popular belief is due to overly stringent requirements that are typically imposed on the procedure rather(More)
BACKGROUND To identify differentially expressed genes, it is standard practice to test a two-sample hypothesis for each gene with a proper adjustment for multiple testing. Such tests are essentially univariate and disregard the multidimensional structure of microarray data. A more general two-sample hypothesis is formulated in terms of the joint(More)
MOTIVATION Many types of genomic data are naturally represented as binary vectors. Numerous tasks in computational biology can be cast as analysis of relationships between these vectors, and the first step is, frequently, to compute their pairwise distance matrix. Many distance measures have been proposed in the literature, but there is no theory justifying(More)
Distribution-free statistical tests offer clear advantages in situations where the exact unadjusted p-values are required as input for multiple testing procedures. Such situations prevail when testing for differential expression of genes in microarray studies. The Cramér-von Mises two-sample test, based on a certain L-distance between two empirical(More)
A new procedure is proposed to balance type I and II errors in significance testing for differential expression of individual genes. Suppose that a collection, F(k), of k lists of selected genes is available, each of them approximating by their content the true set of differentially expressed genes. For example, such sets can be generated by a subsampling(More)
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