Literature DB >> 15161964

Increased measurement accuracy for sequence-verified microarray probes.

Brigham H Mecham1, Daniel Z Wetmore, Zoltan Szallasi, Yoel Sadovsky, Isaac Kohane, Thomas J Mariani.   

Abstract

Microarrays have been extensively used to investigate genome-wide expression patterns. Although this technology has been tremendously successful, it has suffered from suboptimal individual measurement precision. Significant improvements in this respect have been recently made. In an effort to further explore the underlying variability, we have attempted to globally assess the accuracy of individual probe sequences used to query gene expression. For mammalian Affymetrix microarrays, we identify an unexpectedly large number of probes (greater than 19% of the probes on each platform) that do not correspond to their appropriate mRNA reference sequence (RefSeq). Compared with data derived from inaccurate probes, we find that data derived from sequence-verified probes show 1) increased precision in technical replicates, 2) increased accuracy translating data from one generation microarray to another, 3) increased accuracy translating data from oligonucleotide to cDNA microarrays, and 4) improved capture of biological information in human clinical specimens. The logical conclusion of this work is that probes containing the most reliable sequence information provide the most accurate results. Our data reveal that the identification and removal of inaccurate probes can significantly improve this technology.

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Year:  2004        PMID: 15161964     DOI: 10.1152/physiolgenomics.00066.2004

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  26 in total

1.  A statistical multiprobe model for analyzing cis and trans genes in genetical genomics experiments with short-oligonucleotide arrays.

Authors:  Rudi Alberts; Peter Terpstra; Leonid V Bystrykh; Gerald de Haan; Ritsert C Jansen
Journal:  Genetics       Date:  2005-08-03       Impact factor: 4.562

Review 2.  Reliability and reproducibility issues in DNA microarray measurements.

Authors:  Sorin Draghici; Purvesh Khatri; Aron C Eklund; Zoltan Szallasi
Journal:  Trends Genet       Date:  2005-12-27       Impact factor: 11.639

3.  Exon-based mapping of microarray probes: recovering differential gene expression signal in underpowered hypoxia experiment.

Authors:  Dmitry N Grigoryev; Shwu-Fan Ma; Larissa A Shimoda; Roger A Johns; Byungkook Lee; Joe G N Garcia
Journal:  Mol Cell Probes       Date:  2006-09-19       Impact factor: 2.365

4.  Expression profiles of the mouse lung identify a molecular signature of time-to-birth.

Authors:  Alvin T Kho; Soumyaroop Bhattacharya; Brigham H Mecham; Jungha Hong; Isaac S Kohane; Thomas J Mariani
Journal:  Am J Respir Cell Mol Biol       Date:  2008-07-29       Impact factor: 6.914

Review 5.  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

6.  Use of Bayesian networks to probabilistically model and improve the likelihood of validation of microarray findings by RT-PCR.

Authors:  Sangeeta B English; Shou-Ching Shih; Marco F Ramoni; Lois E Smith; Atul J Butte
Journal:  J Biomed Inform       Date:  2008-08-26       Impact factor: 6.317

Review 7.  Gene expression arrays as a tool to unravel mechanisms of normal tissue radiation injury and prediction of response.

Authors:  Jacqueline J C M Kruse; Fiona A Stewart
Journal:  World J Gastroenterol       Date:  2007-05-21       Impact factor: 5.742

8.  Comparison of three microarray probe annotation pipelines: differences in strategies and their effect on downstream analysis.

Authors:  Pieter Bt Neerincx; Pierrot Casel; Dennis Prickett; Haisheng Nie; Michael Watson; Christophe Klopp; Jack Am Leunissen; Martien Am Groenen
Journal:  BMC Proc       Date:  2009-07-16

9.  Application of a correlation correction factor in a microarray cross-platform reproducibility study.

Authors:  Kellie J Archer; Catherine I Dumur; G Scott Taylor; Michael D Chaplin; Anthony Guiseppi-Elie; Geraldine Grant; Andrea Ferreira-Gonzalez; Carleton T Garrett
Journal:  BMC Bioinformatics       Date:  2007-11-15       Impact factor: 3.169

10.  Bioinformatic and statistical analysis of the optic nerve head in a primate model of ocular hypertension.

Authors:  Kenneth S Kompass; Olga A Agapova; Wenjun Li; Paul L Kaufman; Carol A Rasmussen; M Rosario Hernandez
Journal:  BMC Neurosci       Date:  2008-09-26       Impact factor: 3.288

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