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Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates

BACKGROUND: High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, con...

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Autores principales: Liu, Fang, Jenssen, Tor-Kristian, Trimarchi, Jeff, Punzo, Claudio, Cepko, Connie L, Ohno-Machado, Lucila, Hovig, Eivind, Patrick Kuo, Winston
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1899500/
https://www.ncbi.nlm.nih.gov/pubmed/17555589
http://dx.doi.org/10.1186/1471-2164-8-153
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author Liu, Fang
Jenssen, Tor-Kristian
Trimarchi, Jeff
Punzo, Claudio
Cepko, Connie L
Ohno-Machado, Lucila
Hovig, Eivind
Patrick Kuo, Winston
author_facet Liu, Fang
Jenssen, Tor-Kristian
Trimarchi, Jeff
Punzo, Claudio
Cepko, Connie L
Ohno-Machado, Lucila
Hovig, Eivind
Patrick Kuo, Winston
author_sort Liu, Fang
collection PubMed
description BACKGROUND: High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing). RESULTS: The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. CONCLUSION: Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling.
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spelling pubmed-18995002007-06-27 Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates Liu, Fang Jenssen, Tor-Kristian Trimarchi, Jeff Punzo, Claudio Cepko, Connie L Ohno-Machado, Lucila Hovig, Eivind Patrick Kuo, Winston BMC Genomics Research Article BACKGROUND: High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing). RESULTS: The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. CONCLUSION: Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling. BioMed Central 2007-06-07 /pmc/articles/PMC1899500/ /pubmed/17555589 http://dx.doi.org/10.1186/1471-2164-8-153 Text en Copyright © 2007 Liu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Liu, Fang
Jenssen, Tor-Kristian
Trimarchi, Jeff
Punzo, Claudio
Cepko, Connie L
Ohno-Machado, Lucila
Hovig, Eivind
Patrick Kuo, Winston
Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
title Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
title_full Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
title_fullStr Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
title_full_unstemmed Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
title_short Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
title_sort comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1899500/
https://www.ncbi.nlm.nih.gov/pubmed/17555589
http://dx.doi.org/10.1186/1471-2164-8-153
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