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Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: Improving identification of differentially expressed genes in microarray studies using information from public databases. | Method Open Access Improving identification of differentially expressed genes in microarray studies using information from public databases Richard D Kim and Peter J Park Addresses Harvard-Partners Center for Genetics and Genomics 77 Avenue Louis Pasteur Boston MA 02115 USA. ỶChildren s Hospital Informatics Program 300 Longwood Ave Boston MA 02115 USA. Correspondence PeterJ Park. E-mail peter_park@harvard.edu Published 26 August 2004 Genome Biology 2004 5 R70 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2004 5 9 R70 Received 12 May 2004 Revised 15 July 2004 Accepted 19 July 2004 2004 Kim and Park licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract We demonstrate that the process of identifying differentially expressed genes in microarray studies with small sample sizes can be substantially improved by extracting information from a large number of datasets accumulated in public databases. The improvement comes from more reliable estimates of gene-specific variances based on other datasets. For a two-group comparison with two arrays in each group for example the result of our method was comparable to that of a t-test analysis with five samples in each group or to that of a regularized t-test analysis with three samples in each group. Our results are further improved by weighting the results of our approach with the regularized t-test results in a hybrid method. Background Microarray experiments are often used to identify potentially relevant genes in biological processes. By determining which genes are differentially expressed between different states for example hypotheses can be developed as to the role of those genes in the underlying biological mechanism
