Препринт

CNSA: a data repository for archiving omics data

Xueqin GuoChina National GeneBank, Shenzhen 518120, ChinaFengzhen ChenChina National GeneBank, Shenzhen 518120, ChinaFei GaoChina National GeneBank, Shenzhen 518120, ChinaLing LiChina National GeneBank, Shenzhen 518120, ChinaKe LiuChina National GeneBank, Shenzhen 518120, ChinaLijin YouChina National GeneBank, Shenzhen 518120, ChinaCong HuaChina National GeneBank, Shenzhen 518120, ChinaFan YangChina National GeneBank, Shenzhen 518120, ChinaWanliang LiuChina National GeneBank, Shenzhen 518120, ChinaChunhua PengChina National GeneBank, Shenzhen 518120, ChinaLina WangChina National GeneBank, Shenzhen 518120, ChinaXiaoxia YangChina National GeneBank, Shenzhen 518120, ChinaFeiyu ZhouChina National GeneBank, Shenzhen 518120, ChinaJiawei TongChina National GeneBank, Shenzhen 518120, ChinaJia CaiChina National GeneBank, Shenzhen 518120, ChinaZhiyong LiChina National GeneBank, Shenzhen 518120, ChinaBo WanChina National GeneBank, Shenzhen 518120, ChinaLei ZhangChina National GeneBank, Shenzhen 518120, ChinaTao YangChina National GeneBank, Shenzhen 518120, ChinaMinwen ZhangChina National GeneBank, Shenzhen 518120, ChinaLinlin YangChina National GeneBank, Shenzhen 518120, ChinaYawen YangChina National GeneBank, Shenzhen 518120, ChinaWenjun ZengChina National GeneBank, Shenzhen 518120, ChinaBo WangChina National GeneBank, Shenzhen 518120, ChinaXiaofeng WeiChina National GeneBank, Shenzhen 518120, ChinaXun XuBGI-Shenzhen, Shenzhen 518083, China

2020en

ABI

Аннотация

Abstract With the application and development of high-throughput sequencing technology in life and health sciences, massive multi-dimensional biological 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 analytical data and related metadata which are organized into six objects, namely Project, Sample, Experiment, Run, Assembly, and Variation at present. Moreover, CNSA has created the correlation model of living samples, sample information, and analytical data on some projects, 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 the storage, management and sharing of omics data, improving the data standards, and providing 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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Идентификаторлар

DOI: 10.1101/2020.04.07.030833

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