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颜林林 (2022-07-05 00:03):
#paper doi:10.1093/database/baac049 Database, 2022, dbBIP: a comprehensive bipolar disorder database for genetic research. 这篇文章,正如其期刊名,是一个数据库。它的研究主题和对象是bipolar disorder(BIP,双相情感障碍,又称躁狂抑郁症)。通过整合既往关于该疾病的大规模组学数据,包括两个基于芯片的GWAS队列(PGC2和PGC3,分别贡献了20352例BIP病例和31358名对照、41917例BIP和371549对照),也包括后续多项研究的WGS/WES测序数据,还包括大规模脑组织的转录组测序数据(表达谱数据),并通过各类组学分析方法,提供了对这些数据的功能注释、连锁关联、蛋白质相互作用、时空表达模式等信息。所有这些信息都以网站形式提供查询和在线分析功能。这是典型的生物信息学类型研究工作,也是深入开启某一研究方向的有效开局方式。
Abstract:
Bipolar disorder (BIP) is one of the most common hereditary psychiatric disorders worldwide. Elucidating the genetic basis of BIP will play a pivotal role in mechanistic delineation. Genome-wide association studies … >>>
Bipolar disorder (BIP) is one of the most common hereditary psychiatric disorders worldwide. Elucidating the genetic basis of BIP will play a pivotal role in mechanistic delineation. Genome-wide association studies (GWAS) have successfully reported multiple susceptibility loci conferring BIP risk, thus providing insight into the effects of its underlying pathobiology. However, difficulties remain in the extrication of important and biologically relevant data from genetic discoveries related to psychiatric disorders such as BIP. There is an urgent need for an integrated and comprehensive online database with unified access to genetic and multi-omics data for in-depth data mining. Here, we developed the dbBIP, a database for BIP genetic research based on published data. The dbBIP consists of several modules, i.e.: (i) single nucleotide polymorphism (SNP) module, containing large-scale GWAS genetic summary statistics and functional annotation information relevant to risk variants; (ii) gene module, containing BIP-related candidate risk genes from various sources and (iii) analysis module, providing a simple and user-friendly interface to analyze one's own data. We also conducted extensive analyses, including functional SNP annotation, integration (including summary-data-based Mendelian randomization and transcriptome-wide association studies), co-expression, gene expression, tissue expression, protein-protein interaction and brain expression quantitative trait loci analyses, thus shedding light on the genetic causes of BIP. Finally, we developed a graphical browser with powerful search tools to facilitate data navigation and access. The dbBIP provides a comprehensive resource for BIP genetic research as well as an integrated analysis platform for researchers and can be accessed online at http://dbbip.xialab.info. Database URL: http://dbbip.xialab.info. <<<
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