CNSA: a data repository for archiving omics data

Xueqin Guo(China National GeneBank), Fengzhen Chen(China National GeneBank), Fei Gao(China National GeneBank), Ling Li(China National GeneBank), Ke Liu(China National GeneBank), Lijin You(China National GeneBank), Cong Hua(China National GeneBank), Fan Yang(China National GeneBank), Wanliang Liu(China National GeneBank), Chunhua Peng(China National GeneBank), Lina Wang(China National GeneBank), Xiaoxia Yang(China National GeneBank), Feiyu Zhou(China National GeneBank), Jiawei Tong(China National GeneBank), Jia Cai(China National GeneBank), Zhiyong Li(China National GeneBank), Bo Wan(China National GeneBank), Lei Zhang(China National GeneBank), Tao Yang(China National GeneBank), Minwen Zhang(China National GeneBank), Linlin Yang(China National GeneBank), Yawen Yang(China National GeneBank), Wenjun Zeng(China National GeneBank), Bo Wang(China National GeneBank), Xiaofeng Wei(China National GeneBank), Xun Xu(BGI Group (China))
Database
January 1, 2020
Cited by 448Open Access
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Abstract

With the application and development of high-throughput sequencing technology in life and health sciences, massive multi-omics data brings the problem of efficient management and utilization. Database development and biocuration are the prerequisites for the reuse of these big data. Here, relying on China National GeneBank (CNGB), we present CNGB Sequence Archive (CNSA) for archiving omics data, including raw sequencing data and its further analyzed results which are organized into six objects, namely Project, Sample, Experiment, Run, Assembly and Variation at present. Moreover, CNSA has created a correlation model of living samples, sample information and analytical data on some projects. Both living samples and analytical data are directly correlated with the sample information. From either one, information or data of the other two can be obtained, so that all data can be traced throughout the life cycle from the living sample to the sample information to the analytical data. Complying with the data standards commonly used in the life sciences, CNSA is committed to building a comprehensive and curated data repository for storing, managing and sharing of omics data. We will continue to improve the data standards and provide free access to open-data resources for worldwide scientific communities to support academic research and the bio-industry. Database URL: https://db.cngb.org/cnsa/.


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