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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...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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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. |
format | Text |
id | pubmed-1899500 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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