Home News About Us Contact Contributors Disclaimer Privacy Policy Help FAQ

Home
Search
Quick Search
Advanced
Fulltext
Browse
Collections
Persons
My eDoc
Session History
Login
Name:
Password:
Documentation
Help
Support Wiki
Direct access to
document ID:


          Institute: MPI für molekulare Genetik     Collection: Department of Human Molecular Genetics     Display Documents



  history
ID: 472089.0, MPI für molekulare Genetik / Department of Human Molecular Genetics
Estimating accuracy of RNA-Seq and microarrays with proteomics
Authors:Fu, Xing; Fu, Ning; Guo, Song; Yan, Zheng; Xu, Ying; Hu, Hao; Menzel, Corinna; Chen, Wei; Li, Yixue; Zeng, Rong; Khaitovich, Philipp
Language:English
Date of Publication (YYYY-MM-DD):2009-04-10
Title of Journal:BMC Genomics
Volume:10
Start Page:161
End Page:161
Copyright:© 2009 Fu et al
Review Status:not specified
Audience:Experts Only
Abstract / Description:Background
Microarrays revolutionized biological research by enabling gene expression comparisons on a transcriptome-wide scale. Microarrays, however, do not estimate absolute expression level accurately. At present, high throughput sequencing is emerging as an alternative methodology for transcriptome studies. Although free of many limitations imposed by microarray design, its potential to estimate absolute transcript levels is unknown.

Results
In this study, we evaluate relative accuracy of microarrays and transcriptome sequencing (RNA-Seq) using third methodology: proteomics. We find that RNA-Seq provides a better estimate of absolute expression levels.

Conclusion
Our result shows that in terms of overall technical performance, RNA-Seq is the technique of choice for studies that require accurate estimation of absolute transcript levels.
External Publication Status:published
Document Type:Article
Communicated by:Hans-Hilger Ropers
Affiliations:MPI für molekulare Genetik
External Affiliations:Key lab of Systems Biology, Shanghai Institutes for Biological Sciences, China Academy of Sciences, Shanghai, 200031, PR China
Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai, 200031, PR China
Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
Identifiers:DOI:10.1186/1471-2164-10-161
ISSN:1471-2164
URL:http://www.biomedcentral.com/content/pdf/1471-2164...
The scope and number of records on eDoc is subject to the collection policies defined by each institute - see "info" button in the collection browse view.