Big Data Research ›› 2019, Vol. 5 ›› Issue (4): 67-88.doi: 10.11959/j.issn.2096-0271.2019033

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Integrative analysis for big data in genomics

Xianghong HU1,Heng PENG2,Can YANG3,Tsunghui CHANG1,Xiang WAN1,Zhiquan LUO1   

  1. 1 Shenzhen Research Institute of Big Data,Shenzhen 518172,China
    2 Department of Mathematics,Hong Kong Baptist University,Hong Kong 999077,China
    3 Department of Mathematics,Hong Kong University of Science and Technology,Hong Kong 999077,China
  • Online:2019-07-15 Published:2019-08-09

Abstract:

With the rapid development of bio-technology (e.g.,genotyping chip and sequencing),world-wide researchers have accumulated massive data sets at different levels.Integrative analysis of multi-layered genomic data can greatly contribute to the completion of causal chain from genetic variants to phenotype variations,laying a scientific foundation for personalized and precise medicine.The integrative analysis from the following three aspects mainly reviewed:identification of causal variants and their functional annotation,pleiotropy in human complex traits,Mendelian randomization forcausal inference between phenotypes,and several case studies were provided.Finally,the importance of integrative analysis in genomic data for precision medicine was highlighted.

Key words: GWAS, integrative analysis, polygenicity, pleiotropy, Mendelian randomization

CLC Number: 

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