tailieunhanh - Báo cáo y học: "Statistical tools for synthesizing lists of differentially expressed features in related experiments"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: Statistical tools for synthesizing lists of differentially expressed features in related experiments. | Open Access Method Statistical tools for synthesizing lists of differentially expressed features in related experiments Marta Blangiardo and Sylvia Richardson Address Centre for Biostatistics Imperial College St Mary s Campus Norfolk Place London W2 1PG UK. Correspondence Marta Blangiardo. Email Published II April 2007 Genome Biology 2007 8 R54 doi I86 gb-2007-8-4-r54 The electronic version of this article is the complete one and can be found online at http 2007 8 4 R54 Received 7 July 2006 Revised I3 November 2006 Accepted II April 2007 2007 Blangiardo and Richardson licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract We propose a novel approach for finding a list of features that are commonly perturbed in two or more experiments quantifying the evidence of dependence between the experiments by a ratio. We present a Bayesian analysis of this ratio which leads us to suggest two rules for choosing a cutoff on the ranked list of p values. We evaluate and compare the performance of these statistical tools in a simulation study and show their usefulness on two real datasets. Background In the microarray framework researchers are often interested in the comparison of two or more similar experiments that involve different treatments exposures tissues or species. The aim is to find common denominators between these experiments in the form of a parsimonious list of features for example genes biological processes for which there is strong evidence that the listed features are commonly perturbed in both all the experiments and from which to start further investigations. For example finding common perturbation of a known pathway in several tissues will indicate that this pathway