MOTIVATION: Next-generation sequencing 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 cell line 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 AND IMPLEMENTATION: http://medicalgenomics.org/rna_seq_atlas.
MOTIVATION: Next-generation sequencing 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 cell line 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 AND IMPLEMENTATION: http://medicalgenomics.org/rna_seq_atlas.
Authors: Sheng Li; Scott W Tighe; Charles M Nicolet; Deborah Grove; Shawn Levy; William Farmerie; Agnes Viale; Chris Wright; Peter A Schweitzer; Yuan Gao; Dewey Kim; Joe Boland; Belynda Hicks; Ryan Kim; Sagar Chhangawala; Nadereh Jafari; Nalini Raghavachari; Jorge Gandara; Natàlia Garcia-Reyero; Cynthia Hendrickson; David Roberson; Jeffrey Rosenfeld; Todd Smith; Jason G Underwood; May Wang; Paul Zumbo; Don A Baldwin; George S Grills; Christopher E Mason Journal: Nat Biotechnol Date: 2014-08-24 Impact factor: 54.908
Authors: Frank Staib; Markus Krupp; Thorsten Maass; Timo Itzel; Arndt Weinmann; Ju-Seog Lee; Bertil Schmidt; Martina Müller; Snorri S Thorgeirsson; Peter R Galle; Andreas Teufel Journal: Liver Int Date: 2013-09-09 Impact factor: 5.828
Authors: Max Kotlyar; Chiara Pastrello; Flavia Pivetta; Alessandra Lo Sardo; Christian Cumbaa; Han Li; Taline Naranian; Yun Niu; Zhiyong Ding; Fatemeh Vafaee; Fiona Broackes-Carter; Julia Petschnigg; Gordon B Mills; Andrea Jurisicova; Igor Stagljar; Roberta Maestro; Igor Jurisica Journal: Nat Methods Date: 2014-11-17 Impact factor: 28.547
Authors: Cosmas C Giallourakis; Yair Benita; Benoit Molinie; Zhifang Cao; Orion Despo; Henry E Pratt; Lawrence R Zukerberg; Mark J Daly; John D Rioux; Ramnik J Xavier Journal: J Immunol Date: 2013-04-24 Impact factor: 5.422