TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies

Author:

Lu Mingming123,Zhang Yadong12ORCID,Yang Fengchun4,Mai Jialin123,Gao Qianwen123,Xu Xiaowei4,Kang Hongyu4,Hou Li4,Shang Yunfei123,Qain Qiheng123,Liu Jie5,Jiang Meiye123,Zhang Hao123ORCID,Bu Congfan12,Wang Jinyue6,Zhang Zhewen12,Zhang Zaichao7,Zeng Jingyao12ORCID,Li Jiao4,Xiao Jingfa123ORCID

Affiliation:

1. National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation , Beijing  100101,  China

2. CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation , Beijing  100101,  China

3. University of Chinese Academy of Sciences , Beijing  100049,  China

4. Institute of Medical Information, Chinese Academy of Medical Sciences/Peking Union Medical College , Beijing  100020,  China

5. North China University of Science and Technology Affiliated Hospital , Tangshan  063000,  China

6. Institute of Biophysics, Chinese Academy of Sciences , Beijing  100101,  China

7. Department of Biology, The University of Western Ontario ,  London ,  Ontario N6A 5B7 , Canada

Abstract

Abstract Transcriptome-wide association studies (TWASs), as a practical and prevalent approach for detecting the associations between genetically regulated genes and traits, are now leading to a better understanding of the complex mechanisms of genetic variants in regulating various diseases and traits. Despite the ever-increasing TWAS outputs, there is still a lack of databases curating massive public TWAS information and knowledge. To fill this gap, here we present TWAS Atlas (https://ngdc.cncb.ac.cn/twas/), an integrated knowledgebase of TWAS findings manually curated from extensive literature. In the current implementation, TWAS Atlas collects 401,266 high-quality human gene–trait associations from 200 publications, covering 22,247 genes and 257 traits across 135 tissue types. In particular, an interactive knowledge graph of the collected gene–trait associations is constructed together with single nucleotide polymorphism (SNP)–gene associations to build up comprehensive regulatory networks at multi-omics levels. In addition, TWAS Atlas, as a user-friendly web interface, efficiently enables users to browse, search and download all association information, relevant research metadata and annotation information of interest. Taken together, TWAS Atlas is of great value for promoting the utility and availability of TWAS results in explaining the complex genetic basis as well as providing new insights for human health and disease research.

Funder

Chinese Academy of Sciences

CAMS Innovation Fund for Medical Sciences

National Natural Science Foundation of China

National Key Research Program of China

Specialized Research Assistant Program of the Chinese Academy of Sciences

The Youth Innovation Promotion Association of Chinese Academy of Science

China Postdoctoral Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Genetics

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