%0 Journal Article %1 Leek:2008:Proc-Natl-Acad-Sci-U-S-A:19033188 %A Leek, J T %A Storey, J D %D 2008 %J Proc Natl Acad Sci U S A %K batch-effect bayes fulltext normalization rna-seq shouldread software %N 48 %P 18718-18723 %R 10.1073/pnas.0808709105 %T A general framework for multiple testing dependence %U https://www.ncbi.nlm.nih.gov/pubmed/19033188 %V 105 %X We develop a general framework for performing large-scale significance testing in the presence of arbitrarily strong dependence. We derive a low-dimensional set of random vectors, called a dependence kernel, that fully captures the dependence structure in an observed high-dimensional dataset. This result shows a surprising reversal of the "curse of dimensionality" in the high-dimensional hypothesis testing setting. We show theoretically that conditioning on a dependence kernel is sufficient to render statistical tests independent regardless of the level of dependence in the observed data. This framework for multiple testing dependence has implications in a variety of common multiple testing problems, such as in gene expression studies, brain imaging, and spatial epidemiology.

@article{Leek:2008:Proc-Natl-Acad-Sci-U-S-A:19033188, abstract = {We develop a general framework for performing large-scale significance testing in the presence of arbitrarily strong dependence. We derive a low-dimensional set of random vectors, called a dependence kernel, that fully captures the dependence structure in an observed high-dimensional dataset. This result shows a surprising reversal of the "curse of dimensionality" in the high-dimensional hypothesis testing setting. We show theoretically that conditioning on a dependence kernel is sufficient to render statistical tests independent regardless of the level of dependence in the observed data. This framework for multiple testing dependence has implications in a variety of common multiple testing problems, such as in gene expression studies, brain imaging, and spatial epidemiology.}, added-at = {2019-09-03T12:08:53.000+0200}, author = {Leek, J T and Storey, J D}, biburl = {https://www.bibsonomy.org/bibtex/22a3fa7c7f8e246c123ccb146c98b80cf/marcsaric}, description = {A general framework for multiple testing dependence. - PubMed - NCBI}, doi = {10.1073/pnas.0808709105}, interhash = {ae98ae621a6fe5697b76598988a13d07}, intrahash = {2a3fa7c7f8e246c123ccb146c98b80cf}, journal = {Proc Natl Acad Sci U S A}, keywords = {batch-effect bayes fulltext normalization rna-seq shouldread software}, month = dec, number = 48, pages = {18718-18723}, pmid = {19033188}, timestamp = {2019-09-03T12:08:53.000+0200}, title = {A general framework for multiple testing dependence}, url = {https://www.ncbi.nlm.nih.gov/pubmed/19033188}, volume = 105, year = 2008 }