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RNA-Seq Atlas - A reference database for gene expression profiling in normal tissue by next generation sequencing.
Bioinformatics. 2012 Feb 17;
Authors: Krupp M, Marquardt JU, Sahin U, Galle PR, Castle J, Teufel A
Abstract
MOTIVATION: Next generation sequencing (NGS) technology enables an entirely new perspective for clinical research and will speed up personalized medicine. In contrast to microarray based approaches, RNA-Seq analysis provides a much more comprehensive and unbiased view of gene expression. Although the perspective is clear and the long-term success of this new technology obvious, bioinformatics resources making these data easily available especially to the biomedical research community are still evolving. RESULTS: We have generated RNA-Seq Atlas, a web-based repository of RNA-Seq gene expression profiles and query tools. The website offers open and easy access to RNA-Seq gene expression profiles and tools to both compare tissues and find genes with specific expression patterns. To enlarge the scope of the RNA-Seq Atlas, the data were linked to common functional and genetic databases, in particular offering information on the respective gene, signaling pathway analysis and evaluation of biological functions by means of gene ontologies. Additionally, data were linked to several microarray gene profiles, including BioGPS normal tissue profiles and NCI60 cancer cellline expression data. Our data search interface allows an integrative detailed comparison between our RNA-Seq data and the microarray information.This is the first database providing data mining tools and open access to large scale RNA-Seq expression profiles. Its applications will be versatile, as it will be beneficial in identifying tissue specific genes and expression profiles, comparison of gene expression profiles among diverse tissues, but also systems biology approaches linking tissue function to gene expression changes. AVAILABILITY: http://medicalgenomics.org/rna_seq_atlas CONTACT: [email protected], [email protected].
PMID: 22345621 [PubMed - as supplied by publisher]
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RNA-Seq Atlas - A reference database for gene expression profiling in normal tissue by next generation sequencing.
Bioinformatics. 2012 Feb 17;
Authors: Krupp M, Marquardt JU, Sahin U, Galle PR, Castle J, Teufel A
Abstract
MOTIVATION: Next generation sequencing (NGS) technology enables an entirely new perspective for clinical research and will speed up personalized medicine. In contrast to microarray based approaches, RNA-Seq analysis provides a much more comprehensive and unbiased view of gene expression. Although the perspective is clear and the long-term success of this new technology obvious, bioinformatics resources making these data easily available especially to the biomedical research community are still evolving. RESULTS: We have generated RNA-Seq Atlas, a web-based repository of RNA-Seq gene expression profiles and query tools. The website offers open and easy access to RNA-Seq gene expression profiles and tools to both compare tissues and find genes with specific expression patterns. To enlarge the scope of the RNA-Seq Atlas, the data were linked to common functional and genetic databases, in particular offering information on the respective gene, signaling pathway analysis and evaluation of biological functions by means of gene ontologies. Additionally, data were linked to several microarray gene profiles, including BioGPS normal tissue profiles and NCI60 cancer cellline expression data. Our data search interface allows an integrative detailed comparison between our RNA-Seq data and the microarray information.This is the first database providing data mining tools and open access to large scale RNA-Seq expression profiles. Its applications will be versatile, as it will be beneficial in identifying tissue specific genes and expression profiles, comparison of gene expression profiles among diverse tissues, but also systems biology approaches linking tissue function to gene expression changes. AVAILABILITY: http://medicalgenomics.org/rna_seq_atlas CONTACT: [email protected], [email protected].
PMID: 22345621 [PubMed - as supplied by publisher]
More...