| URL: | http://rnaseqmetadb.ece.tamu.edu |
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| Description: | RNA-Seq (Wang et al., 2009), a high-throughput sequencing (HTS) method for transcriptome analysis, has been successfully used on many of these mouse models, enabling global analyses of specific genomic alterations at a high sequencing depth with a resonable accuracy. As RNA-Seq becomes increasingly popular, hundreds of RNA-Seq datasets have been generated and have been released to the public. These data are currently available from online |
| Year founded: | 2015 |
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| Accessibility: |
Accessible
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| Country/Region: | United States |
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| University/Institution: | Texas A&M University |
| Address: | Department of Electrical and Computer Engineering & TEES-AgriLife Center for Bioinformatics and Genomic Systems Engineering, Texas A&M University, College Station, TX 77843, USA, |
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| Country/Region: | United States |
| Contact name (PI/Team): | Peng Yu |
| Contact email (PI/Helpdesk): | yup6@sustc.edu.cn |
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RNASeqMetaDB: a database and web server for navigating metadata of publicly available mouse RNA-Seq datasets. [PMID: 26323714]
Gene targeting is a protocol for introducing a mutation to a specific gene in an organism. Because of the importance of in vivo assessment of gene function and modeling of human diseases, this technique has been widely adopted to generate a large number of mutant mouse models. Due to the recent breakthroughs in high-throughput sequencing technologies, RNA-Seq experiments have been performed on many of these mouse models, leading to hundreds of publicly available datasets. To facilitate the reuse of these datasets, we collected the associated metadata and organized them in a database called RNASeqMetaDB. The metadata were manually curated to ensure annotation consistency. We developed a web server to allow easy database navigation and data querying. Users can search the database using multiple parameters like genes, diseases, tissue types, keywords and associated publications in order to find datasets that match their interests. Summary statistics of the metadata are also presented on the web server showing interesting global patterns of RNA-Seq studies. |