tailieunhanh - Báo cáo y học: " Correction of technical bias in clinical microarray data improves concordance with known biological information"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Critical Care giúp cho các bạn có thêm kiến thức về ngành y học đề tài: Correction of technical bias in clinical microarray data improves concordance with known biological information. | Method Open Access Correction of technical bias in clinical microarray data improves concordance with known biological information Aron C Eklund and Zoltan Szallasi Addresses Children s Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology CHIP@HST Harvard Medical School Boston MA 02115 USA. Center for Biological Sequence Analysis Department of Systems Biology Technical University of Denmark DK-2800 Lyngby Denmark. Correspondence Zoltan Szallasi. Email zszallasi@ Published 4 February 2008 Genome Biology 2008 9 R26 doi 186 gb-2008-9-2-r26 The electronic version of this article is the complete one and can be found online at http 2008 9 2 R26 Received 1 October 2007 Revised 7 December 2007 Accepted 4 February 2008 2008 Eklund and Szallasi 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 The performance of gene expression microarrays has been well characterized using controlled reference samples but the performance on clinical samples remains less clear. We identified sources of technical bias affecting many genes in concert thus causing spurious correlations in clinical data sets and false associations between genes and clinical variables. We developed a method to correct for technical bias in clinical microarray data which increased concordance with known biological relationships in multiple data sets. Background The introduction of massively parallel measurement techniques such as gene expression microarrays has led to a much disputed paradigm shift in experimental design 1 . When a single biochemical entity is quantified it is customary and expected to include replicates and carefully selected controls such as calibration curves which increase the .

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