Editorial: Current Status and Future Challenges of Biobank Data Analysis

doi:10.3389/fgene.2022.882611

Editorial

. 2022 Apr 14:13:882611.

doi: 10.3389/fgene.2022.882611. eCollection 2022.

Editorial: Current Status and Future Challenges of Biobank Data Analysis

Tzu-Pin Lu¹, Yoichiro Kamatani², Gillian Belbin³, Taesung Park⁴, Chuhsing Kate Hsiao¹

Affiliations

¹ Department of Public Health, College of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.
² Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
³ Institute of Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
⁴ Department of Statistics, Seoul National University, Seoul, South Korea.

PMID: 35495141
PMCID: PMC9047950
DOI: 10.3389/fgene.2022.882611

Editorial

Editorial: Current Status and Future Challenges of Biobank Data Analysis

Tzu-Pin Lu et al. Front Genet. 2022.

. 2022 Apr 14:13:882611.

doi: 10.3389/fgene.2022.882611. eCollection 2022.

Authors

Tzu-Pin Lu¹, Yoichiro Kamatani², Gillian Belbin³, Taesung Park⁴, Chuhsing Kate Hsiao¹

Affiliations

¹ Department of Public Health, College of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.
² Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
³ Institute of Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
⁴ Department of Statistics, Seoul National University, Seoul, South Korea.

PMID: 35495141
PMCID: PMC9047950
DOI: 10.3389/fgene.2022.882611

No abstract available

Keywords: GWAS; biobank data analysis; integrative analysis; personalized medicine; statistical genetics.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Editorial on the Research Topic Current Status and Future Challenges of Biobank Data Analysis

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References

1. Bi W., Lee S. (2021). Scalable and Robust Regression Methods for Phenome-wide Association Analysis on Large-Scale Biobank Data. Front. Genet. 12, 682638. 10.3389/fgene.2021.682638 - DOI - PMC - PubMed
1. Brucker A., Lu W., Marceau West R., Yu Q.-Y., Hsiao C. K., Hsiao T.-H., et al. (2020). Association Test Using Copy Number Profile Curves (CONCUR) Enhances Power in Rare Copy Number Variant Analysis. Plos Comput. Biol. 16, e1007797. 10.1371/journal.pcbi.1007797 - DOI - PMC - PubMed
1. Chattopadhyay A., Lu T. P. (2019). Gene-gene Interaction: the Curse of Dimensionality. Ann. Transl Med. 7, 813. 10.21037/atm.2019.12.87 - DOI - PMC - PubMed
1. Chen Y. J., Chen I. C., Lin H. J., Lin Y. C., Chang J. C., Chen Y. M., et al. (2021). Association of ABCG2 Rs2231142 Allele and BMI with Hyperuricemia in an East Asian Population. Front. Genet. 12, 709887. 10.3389/fgene.2021.709887 - DOI - PMC - PubMed
1. Chi J. T., Ipsen I. C. F., Hsiao T. H., Lin C. H., Wang L. S., Lee W. P., et al. (2021). SEAGLE: A Scalable Exact Algorithm for Large-Scale Set-Based Gene-Environment Interaction Tests in Biobank Data. Front. Genet. 12, 710055. 10.3389/fgene.2021.710055 - DOI - PMC - PubMed

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[1] Bi W., Lee S. (2021). Scalable and Robust Regression Methods for Phenome-wide Association Analysis on Large-Scale Biobank Data. Front. Genet. 12, 682638. 10.3389/fgene.2021.682638 - DOI - PMC - PubMed

[2] Bi W., Lee S. (2021). Scalable and Robust Regression Methods for Phenome-wide Association Analysis on Large-Scale Biobank Data. Front. Genet. 12, 682638. 10.3389/fgene.2021.682638 - DOI - PMC - PubMed

[3] Brucker A., Lu W., Marceau West R., Yu Q.-Y., Hsiao C. K., Hsiao T.-H., et al. (2020). Association Test Using Copy Number Profile Curves (CONCUR) Enhances Power in Rare Copy Number Variant Analysis. Plos Comput. Biol. 16, e1007797. 10.1371/journal.pcbi.1007797 - DOI - PMC - PubMed

[4] Brucker A., Lu W., Marceau West R., Yu Q.-Y., Hsiao C. K., Hsiao T.-H., et al. (2020). Association Test Using Copy Number Profile Curves (CONCUR) Enhances Power in Rare Copy Number Variant Analysis. Plos Comput. Biol. 16, e1007797. 10.1371/journal.pcbi.1007797 - DOI - PMC - PubMed

[5] Chattopadhyay A., Lu T. P. (2019). Gene-gene Interaction: the Curse of Dimensionality. Ann. Transl Med. 7, 813. 10.21037/atm.2019.12.87 - DOI - PMC - PubMed

[6] Chattopadhyay A., Lu T. P. (2019). Gene-gene Interaction: the Curse of Dimensionality. Ann. Transl Med. 7, 813. 10.21037/atm.2019.12.87 - DOI - PMC - PubMed

[7] Chen Y. J., Chen I. C., Lin H. J., Lin Y. C., Chang J. C., Chen Y. M., et al. (2021). Association of ABCG2 Rs2231142 Allele and BMI with Hyperuricemia in an East Asian Population. Front. Genet. 12, 709887. 10.3389/fgene.2021.709887 - DOI - PMC - PubMed

[8] Chen Y. J., Chen I. C., Lin H. J., Lin Y. C., Chang J. C., Chen Y. M., et al. (2021). Association of ABCG2 Rs2231142 Allele and BMI with Hyperuricemia in an East Asian Population. Front. Genet. 12, 709887. 10.3389/fgene.2021.709887 - DOI - PMC - PubMed

[9] Chi J. T., Ipsen I. C. F., Hsiao T. H., Lin C. H., Wang L. S., Lee W. P., et al. (2021). SEAGLE: A Scalable Exact Algorithm for Large-Scale Set-Based Gene-Environment Interaction Tests in Biobank Data. Front. Genet. 12, 710055. 10.3389/fgene.2021.710055 - DOI - PMC - PubMed

[10] Chi J. T., Ipsen I. C. F., Hsiao T. H., Lin C. H., Wang L. S., Lee W. P., et al. (2021). SEAGLE: A Scalable Exact Algorithm for Large-Scale Set-Based Gene-Environment Interaction Tests in Biobank Data. Front. Genet. 12, 710055. 10.3389/fgene.2021.710055 - DOI - PMC - PubMed

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Editorial: Current Status and Future Challenges of Biobank Data Analysis

Affiliations

Editorial: Current Status and Future Challenges of Biobank Data Analysis

Authors

Affiliations

Conflict of interest statement

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