tailieunhanh - báo cáo khoa học: " Overcoming bias and systematic errors in next generation sequencing data"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Overcoming bias and systematic errors in next generation sequencing data | Taub et al. Genome Medicine 2010 2 87 http content 2 12 87 Genome Medicine COMMENTARY L__ Overcoming bias and systematic errors in next generation sequencing data Margaret A Taub 1 Hector Corrada Bravo2 and Rafael A Irizarry 1 Abstract Considerable time and effort has been spent in developing analysis and quality assessment methods to allow the use of microarrays in a clinical setting. As is the case for microarrays and other high-throughput technologies data from new high-throughput sequencing technologies are subject to technological and biological biases and systematic errors that can impact downstream analyses. Only when these issues can be readily identified and reliably adjusted for will clinical applications of these new technologies be feasible. Although much work remains to be done in this area we describe consistently observed biases that should be taken into account when analyzing high-throughput sequencing data. In this article we review current knowledge about these biases discuss their impact on analysis results and propose solutions. Background clinical applications of microarrays While microarrays were rapidly accepted in research applications incorporating them in clinical settings has required over a decade of benchmarking standardization and the development of appropriate analysis methods. Extensive cross-platform and cross-laboratory analyses demonstrated the importance of low-level processing choices 1-3 including data summarization normalization and adjustment for laboratory or batch effects 4 on outcome accuracy. Some of this work was done under the auspices of the Food and Drug Administration FDA most notably the Microarray Quality Control MAQC studies which were developed specifically in order to determine the utility of microarray technologies in a clinical setting 5 6 . Microarray-measured gene expression signatures now form the basis of several Correspondence mtaub@ ririzarr@ department of .