Literature DB >> 16823376

A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies.

Winston Patrick Kuo1, Fang Liu, Jeff Trimarchi, Claudio Punzo, Michael Lombardi, Jasjit Sarang, Mark E Whipple, Malini Maysuria, Kyle Serikawa, Sun Young Lee, Donald McCrann, Jason Kang, Jeffrey R Shearstone, Jocelyn Burke, Daniel J Park, Xiaowei Wang, Trent L Rector, Paola Ricciardi-Castagnoli, Steven Perrin, Sangdun Choi, Roger Bumgarner, Ju Han Kim, Glenn F Short, Mason W Freeman, Brian Seed, Roderick Jensen, George M Church, Eivind Hovig, Connie L Cepko, Peter Park, Lucila Ohno-Machado, Tor-Kristian Jenssen.   

Abstract

Over the last decade, gene expression microarrays have had a profound impact on biomedical research. The diversity of platforms and analytical methods available to researchers have made the comparison of data from multiple platforms challenging. In this study, we describe a framework for comparisons across platforms and laboratories. We have attempted to include nearly all the available commercial and 'in-house' platforms. Using probe sequences matched at the exon level improved consistency of measurements across the different microarray platforms compared to annotation-based matches. Generally, consistency was good for highly expressed genes, and variable for genes with lower expression values as confirmed by quantitative real-time (QRT)-PCR. Concordance of measurements was higher between laboratories on the same platform than across platforms. We demonstrate that, after stringent preprocessing, commercial arrays were more consistent than in-house arrays, and by most measures, one-dye platforms were more consistent than two-dye platforms.

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Year:  2006        PMID: 16823376     DOI: 10.1038/nbt1217

Source DB:  PubMed          Journal:  Nat Biotechnol        ISSN: 1087-0156            Impact factor:   54.908


  64 in total

1.  Power of deep sequencing and agilent microarray for gene expression profiling study.

Authors:  Lin Feng; Hang Liu; Yu Liu; Zhike Lu; Guangwu Guo; Suping Guo; Hongwei Zheng; Yanning Gao; Shujun Cheng; Jian Wang; Kaitai Zhang; Yong Zhang
Journal:  Mol Biotechnol       Date:  2010-06       Impact factor: 2.695

2.  The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Authors:  Leming Shi; Laura H Reid; Wendell D Jones; Richard Shippy; Janet A Warrington; Shawn C Baker; Patrick J Collins; Francoise de Longueville; Ernest S Kawasaki; Kathleen Y Lee; Yuling Luo; Yongming Andrew Sun; James C Willey; Robert A Setterquist; Gavin M Fischer; Weida Tong; Yvonne P Dragan; David J Dix; Felix W Frueh; Frederico M Goodsaid; Damir Herman; Roderick V Jensen; Charles D Johnson; Edward K Lobenhofer; Raj K Puri; Uwe Schrf; Jean Thierry-Mieg; Charles Wang; Mike Wilson; Paul K Wolber; Lu Zhang; Shashi Amur; Wenjun Bao; Catalin C Barbacioru; Anne Bergstrom Lucas; Vincent Bertholet; Cecilie Boysen; Bud Bromley; Donna Brown; Alan Brunner; Roger Canales; Xiaoxi Megan Cao; Thomas A Cebula; James J Chen; Jing Cheng; Tzu-Ming Chu; Eugene Chudin; John Corson; J Christopher Corton; Lisa J Croner; Christopher Davies; Timothy S Davison; Glenda Delenstarr; Xutao Deng; David Dorris; Aron C Eklund; Xiao-hui Fan; Hong Fang; Stephanie Fulmer-Smentek; James C Fuscoe; Kathryn Gallagher; Weigong Ge; Lei Guo; Xu Guo; Janet Hager; Paul K Haje; Jing Han; Tao Han; Heather C Harbottle; Stephen C Harris; Eli Hatchwell; Craig A Hauser; Susan Hester; Huixiao Hong; Patrick Hurban; Scott A Jackson; Hanlee Ji; Charles R Knight; Winston P Kuo; J Eugene LeClerc; Shawn Levy; Quan-Zhen Li; Chunmei Liu; Ying Liu; Michael J Lombardi; Yunqing Ma; Scott R Magnuson; Botoul Maqsodi; Tim McDaniel; Nan Mei; Ola Myklebost; Baitang Ning; Natalia Novoradovskaya; Michael S Orr; Terry W Osborn; Adam Papallo; Tucker A Patterson; Roger G Perkins; Elizabeth H Peters; Ron Peterson; Kenneth L Philips; P Scott Pine; Lajos Pusztai; Feng Qian; Hongzu Ren; Mitch Rosen; Barry A Rosenzweig; Raymond R Samaha; Mark Schena; Gary P Schroth; Svetlana Shchegrova; Dave D Smith; Frank Staedtler; Zhenqiang Su; Hongmei Sun; Zoltan Szallasi; Zivana Tezak; Danielle Thierry-Mieg; Karol L Thompson; Irina Tikhonova; Yaron Turpaz; Beena Vallanat; Christophe Van; Stephen J Walker; Sue Jane Wang; Yonghong Wang; Russ Wolfinger; Alex Wong; Jie Wu; Chunlin Xiao; Qian Xie; Jun Xu; Wen Yang; Liang Zhang; Sheng Zhong; Yaping Zong; William Slikker
Journal:  Nat Biotechnol       Date:  2006-09       Impact factor: 54.908

3.  Gene expression profiling by massively parallel sequencing.

Authors:  Tatiana Teixeira Torres; Muralidhar Metta; Birgit Ottenwälder; Christian Schlötterer
Journal:  Genome Res       Date:  2007-11-21       Impact factor: 9.043

4.  Ratio adjustment and calibration scheme for gene-wise normalization to enhance microarray inter-study prediction.

Authors:  Chunrong Cheng; Kui Shen; Chi Song; Jianhua Luo; George C Tseng
Journal:  Bioinformatics       Date:  2009-05-04       Impact factor: 6.937

5.  Using cell engineering and omic tools for the improvement of cell culture processes.

Authors:  Darrin Kuystermans; Britta Krampe; Halina Swiderek; Mohamed Al-Rubeai
Journal:  Cytotechnology       Date:  2007-02-24       Impact factor: 2.058

Review 6.  Technical variables in high-throughput miRNA expression profiling: much work remains to be done.

Authors:  Peter T Nelson; Wang-Xia Wang; Bernard R Wilfred; Guiliang Tang
Journal:  Biochim Biophys Acta       Date:  2008-04-07

7.  ChIP-Seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells.

Authors:  Zhengqing Ouyang; Qing Zhou; Wing Hung Wong
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-07       Impact factor: 11.205

8.  Assessing the validity and reproducibility of genome-scale predictions.

Authors:  Lauren A Sugden; Michael R Tackett; Yiannis A Savva; William A Thompson; Charles E Lawrence
Journal:  Bioinformatics       Date:  2013-09-17       Impact factor: 6.937

Review 9.  Review of the literature examining the correlation among DNA microarray technologies.

Authors:  Carole L Yauk; M Lynn Berndt
Journal:  Environ Mol Mutagen       Date:  2007-06       Impact factor: 3.216

10.  Meta Analysis of Gene Expression Data within and Across Species.

Authors:  Ana C Fierro; Filip Vandenbussche; Kristof Engelen; Yves Van de Peer; Kathleen Marchal
Journal:  Curr Genomics       Date:  2008-12       Impact factor: 2.236

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