Author

Hisashi Noma

Japan Science and Technology AgencyORCID 0000-0002-2520-9949Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Daichi ShigemizuiD· 1 shared Hidenori Ochi· 1 shared Jo NishinoiD· 1 shared Katsunori IkariiD· 1 shared Keith A. BoroevichiD· 1 shared Kota MatsuiiD· 1 shared Mamoru KatoiD· 1 shared Shigeyuki MatsuiiD· 1 shared

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2018-2018 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperGenomics

Daichi ShigemizuORCID

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1 paper

Recent·Most cited

GenomicsFrontiers in GeneticsPeer-reviewedApr 24, 2018

Empirical Bayes estimation of semi-parametric hierarchical mixture models for unbiased characterization of polygenic disease architectures

Jo Nishino, Yuta Kochi, Daichi Shigemizu…·Shigeyuki Matsui

The paper uses empirical Bayes estimation of semi-parametric hierarchical mixture models to analyze GWAS summary statistics and characterize the polygenic architectures of schizophrenia and rheumatoid arthritis.

10 citations

humanGWAS summary statistics