tailieunhanh - Báo cáo y học: "Correlating measurements across samples improves accuracy of large-scale expression profile experiments"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: Correlating measurements across samples improves accuracy of large-scale expression profile experiments. | Method Open Access Correlating measurements across samples improves accuracy of large-scale expression profile experiments Mariano Javier Alvarez Pavel Sumazin Presha Rajbhandari and Andrea Califano Addresses Joint Centers for Systems Biology Columbia University 2960 Broadway New York NY 10027-6900 USA. Department of Biomedical Informatics and Institute for Cancer Genetics and Herbert Irving Comprehensive Cancer Center Columbia University 2960 Broadway New York NY 10027-6900 USA. These authors contributed equally to this work. Correspondence Andrea Califano. Email califano@ Published 30 December 2009 Genome Biology 2009 10 Rl43 doi gb-2009-l0-l2-rl43 The electronic version of this article is the complete one and can be found online at http 2009 l0 l2 Rl43 Received 17 July 2009 Revised 15 December 2009 Accepted 30 December 2009 2009 Alvarez et al. 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 Gene expression profiling technologies suffer from poor reproducibility across replicate experiments. However when analyzing large datasets probe-level expression profile correlation can help identify flawed probes and lead to the construction of truer probe sets with improved reproducibility. We describe methods to eliminate uninformative and flawed probes account for dependence between probes and address variability due to transcript-isoform mixtures. We test and validate our approach on Affymetrix microarrays and outline their future adaptation to other technologies. Background Gene expression profiling is a valuable technique for studying cell phenotype at the molecular level. Microarray gene expression profiling in particular is unquestionably the most widely adopted molecular .

TÀI LIỆU LIÊN QUAN
TỪ KHÓA LIÊN QUAN
crossorigin="anonymous">
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.