Author

Guy Nathaniel Brock

The Ohio State UniversityORCID 0000-0001-5317-079XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Amy WebbiD· 2 shared Christopher A. HaimaniD· 2 shared Lara E. Sucheston‐CampbelliD· 2 shared Loreall PooleriD· 2 shared Marcelo C. PasquiniiD· 2 shared Philip L. McCarthyiD· 2 shared Qianqian ZhuiD· 2 shared Stephen R. SpellmaniD· 2 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenetics

Amy WebbORCID

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3 papers

Recent·Most cited

GeneticsbioRxivPreprintAug 31, 2022

Associations of Minor Histocompatibility Antigens with Clinical Outcomes Following Allogeneic Hematopoietic Cell Transplantation

Othmane Jadi, Hancong Tang, Kelly Shea Olsen…·Lara E. Sucheston‐Campbell

This study investigates the association between predicted minor histocompatibility antigens (mHAs) and clinical outcomes in allogeneic hematopoietic cell transplantation using multivariate survival models.

DOI 10.1101/2022.08.31.506092

humanstatistical model

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GenomicsFrontiers in GeneticsPeer-reviewedJun 17, 2021

Genome-wide association analyses identify variants in IRF4 associated with acute myeloid leukemia and myelodysplastic syndrome susceptibility

Junke Wang, Alyssa Clay‐Gilmour, Ezgi Karaesmen…·Lara E. Sucheston‐Campbell

This study identifies IRF4 variants associated with increased risk of de novo AML and MDS through GWAS and TWAS analyses using the DISCOVeRY-BMT cohorts.

17 citations

humanGWAS summary statistics

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BioinformaticsJournal of Statistical SoftwarePeer-reviewedJan 1, 2019

Polychrome: Creating and Assessing Qualitative Palettes With Many Colors

Kevin R. Coombes, Guy Nathaniel Brock, Zachary B. Abrams, Lynne V. Abruzzo

Polychrome creates and evaluates color palettes with at least 24 distinguishable colors for categorical data visualization, addressing limitations in existing R packages.

34 citations

statistical modelbenchmarking

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