TransAtlasDB: an integrated database connecting expression data, metadata and variants
| Author(s) | Adetunji, Modupeore O. | |
| Author(s) | Lamont, Susan J. | |
| Author(s) | Schmidt, Carl J. | |
| Date Accessioned | 2025-02-20T18:29:33Z | |
| Date Available | 2025-02-20T18:29:33Z | |
| Publication Date | 2018-02-23 | |
| Description | This article was originally published in Database: The Journal of Biological Databases and Curation Published by Oxford University Press. The version of record is available at: https://doi.org/10.1093/database/bay014. © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. | |
| Abstract | High-throughput transcriptome sequencing (RNAseq) is the universally applied method for target-free transcript identification and gene expression quantification, generating huge amounts of data. The constraint of accessing such data and interpreting results can be a major impediment in postulating suitable hypothesis, thus an innovative storage solution that addresses these limitations, such as hard disk storage requirements, efficiency and reproducibility are paramount. By offering a uniform data storage and retrieval mechanism, various data can be compared and easily investigated. We present a sophisticated system, TransAtlasDB, which incorporates a hybrid architecture of both relational and NoSQL databases for fast and efficient data storage, processing and querying of large datasets from transcript expression analysis with corresponding metadata, as well as gene-associated variants (such as SNPs) and their predicted gene effects. TransAtlasDB provides the data model of accurate storage of the large amount of data derived from RNAseq analysis and also methods of interacting with the database, either via the command-line data management workflows, written in Perl, with useful functionalities that simplifies the complexity of data storage and possibly manipulation of the massive amounts of data generated from RNAseq analysis or through the web interface. The database application is currently modeled to handle analyses data from agricultural species, and will be expanded to include more species groups. Overall TransAtlasDB aims to serve as an accessible repository for the large complex results data files derived from RNAseq gene expression profiling and variant analysis. | |
| Sponsor | This project was supported by Agriculture and Food Research Initiative Competitive Grant 2011-67003-30228 from the United States Department of Agriculture National institute of Food and Agriculture. | |
| Citation | Modupeore O Adetunji, Susan J Lamont, Carl J Schmidt, TransAtlasDB: an integrated database connecting expression data, metadata and variants, Database, Volume 2018, 2018, bay014, https://doi.org/10.1093/database/bay014 | |
| ISSN | 1758-0463 | |
| URL | https://udspace.udel.edu/handle/19716/35827 | |
| Language | en_US | |
| Publisher | Database: The Journal of Biological Databases and Curation | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| Title | TransAtlasDB: an integrated database connecting expression data, metadata and variants | |
| Type | Article |
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