Omicseq: a web-based search engine for exploring omics datasets

• Published in: Nucleic acids research Vol. 45; no. W1; pp. W445 - W452
• Main Authors: Sun, Xiaobo, Pittard, William S, Xu, Tianlei, Chen, Li, Zwick, Michael E, Jiang, Xiaoqian, Wang, Fusheng, Qin, Zhaohui S
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 03.07.2017
• Subjects: Algorithms; Biomarkers, Tumor - genetics; Biomarkers, Tumor - metabolism; Breast Neoplasms - genetics; Breast Neoplasms - metabolism; Breast Neoplasms - pathology; Databases, Genetic; Databases, Protein; Datasets as Topic; Female; Gene Expression; Genomics - methods; Humans; Internet; Kallikreins - genetics; Kallikreins - metabolism; Male; Metadata - statistics & numerical data; Prostate-Specific Antigen - genetics; Prostate-Specific Antigen - metabolism; Prostatic Neoplasms - genetics; Prostatic Neoplasms - metabolism; Prostatic Neoplasms - pathology; PTEN Phosphohydrolase - genetics; PTEN Phosphohydrolase - metabolism; Receptor, ErbB-2 - genetics; Receptor, ErbB-2 - metabolism; Search Engine; User-Computer Interface; Web Server Issue
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gkx258

The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve 'findability' of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org.