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

Winston Patrick Kuo; 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

doi:10.1038/nbt1217

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

Winston Patrick Kuo
, 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

Research output: Contribution to journal › Article › peer-review

136 Scopus citations

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.

Original language	English
Pages (from-to)	832-840
Number of pages	9
Journal	Nature Biotechnology
Volume	24
Issue number	7
DOIs	https://doi.org/10.1038/nbt1217
State	Published - Jul 2006
Externally published	Yes

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Kuo, W. P., Liu, F., Trimarchi, J., Punzo, C., Lombardi, M., Sarang, J., Whipple, M. E., Maysuria, M., Serikawa, K., Lee, S. Y., McCrann, D., Kang, J., Shearstone, J. R., Burke, J., Park, D. J., Wang, X., Rector, T. L., Ricciardi-Castagnoli, P., Perrin, S., ... Jenssen, T. K. (2006). A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies. Nature Biotechnology, 24(7), 832-840. https://doi.org/10.1038/nbt1217

@article{c1d0cbb403f04d4fa8b68d48c04610dc,

title = "A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies",

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.",

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

note = "Funding Information: We would like to thank vendors, Applied Biosystems, GE Healthcare, and Mergen for providing and running microarrays as part of this large-scale evaluation. In addition, we would like to thank Applied Biosystems for running TaqMan assays and Exiqon for supplying us with the ProbeLibrary kit as well as Roche Diagnostics for allowing us to use their 480 LightCycler. We thank Robert A. Greenes for reviewing the manuscript. W.P.K. was supported by the National Institutes of Health (NIH) EY014466 grant and by the Bioinformatics Division of the Harvard Center for Neurodegeneration and Repair. C.L.C. was supported by the Howard Hughes Medical Institute. F.L. and E.H. were supported by the functional genomics program (FUGE) in the Research council of Norway. G.M.C. was supported by NIH-NHGRI-CEGS. M.W.F., B.S. and G.F.S. were supported by Programs for Genomic Applications grants HL66678 and HL72358. R.B. was supported by NIH grants HL072370 and ES011387.",

year = "2006",

month = jul,

doi = "10.1038/nbt1217",

language = "English",

volume = "24",

pages = "832--840",

journal = "Nature Biotechnology",

issn = "1087-0156",

number = "7",

}

Kuo, WP, Liu, F, Trimarchi, J, Punzo, C, Lombardi, M, Sarang, J, Whipple, ME, Maysuria, M, Serikawa, K, Lee, SY, McCrann, D, Kang, J, Shearstone, JR, Burke, J, Park, DJ, Wang, X, Rector, TL, Ricciardi-Castagnoli, P, Perrin, S, Choi, S, Bumgarner, R, Kim, JH, Short, GF, Freeman, MW, Seed, B, Jensen, R, Church, GM, Hovig, E, Cepko, CL, Park, P, Ohno-Machado, L & Jenssen, TK 2006, 'A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies', Nature Biotechnology, vol. 24, no. 7, pp. 832-840. https://doi.org/10.1038/nbt1217

TY - JOUR

T1 - A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies

AU - Kuo, Winston Patrick

AU - Liu, Fang

AU - Trimarchi, Jeff

AU - Punzo, Claudio

AU - Lombardi, Michael

AU - Sarang, Jasjit

AU - Whipple, Mark E.

AU - Maysuria, Malini

AU - Serikawa, Kyle

AU - Lee, Sun Young

AU - McCrann, Donald

AU - Kang, Jason

AU - Shearstone, Jeffrey R.

AU - Burke, Jocelyn

AU - Park, Daniel J.

AU - Wang, Xiaowei

AU - Rector, Trent L.

AU - Ricciardi-Castagnoli, Paola

AU - Perrin, Steven

AU - Choi, Sangdun

AU - Bumgarner, Roger

AU - Kim, Ju Han

AU - Short, Glenn F.

AU - Freeman, Mason W.

AU - Seed, Brian

AU - Jensen, Roderick

AU - Church, George M.

AU - Hovig, Eivind

AU - Cepko, Connie L.

AU - Park, Peter

AU - Ohno-Machado, Lucila

AU - Jenssen, Tor Kristian

N1 - Funding Information: We would like to thank vendors, Applied Biosystems, GE Healthcare, and Mergen for providing and running microarrays as part of this large-scale evaluation. In addition, we would like to thank Applied Biosystems for running TaqMan assays and Exiqon for supplying us with the ProbeLibrary kit as well as Roche Diagnostics for allowing us to use their 480 LightCycler. We thank Robert A. Greenes for reviewing the manuscript. W.P.K. was supported by the National Institutes of Health (NIH) EY014466 grant and by the Bioinformatics Division of the Harvard Center for Neurodegeneration and Repair. C.L.C. was supported by the Howard Hughes Medical Institute. F.L. and E.H. were supported by the functional genomics program (FUGE) in the Research council of Norway. G.M.C. was supported by NIH-NHGRI-CEGS. M.W.F., B.S. and G.F.S. were supported by Programs for Genomic Applications grants HL66678 and HL72358. R.B. was supported by NIH grants HL072370 and ES011387.

PY - 2006/7

Y1 - 2006/7

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/33746108159

U2 - 10.1038/nbt1217

DO - 10.1038/nbt1217

M3 - Article

C2 - 16823376

AN - SCOPUS:33746108159

SN - 1087-0156

VL - 24

SP - 832

EP - 840

JO - Nature Biotechnology

JF - Nature Biotechnology

IS - 7

ER -

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

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