Author

Maura John

Weihenstephan-Triesdorf University of Applied SciencesORCID 0000-0002-2773-2426Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Arthur KorteiD· 2 shared Dominik G. GrimmiD· 2 shared Carolin Artmann· 1 shared Jan A. FreudenthaliD· 1 shared Markus Johannes AnkenbrandiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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2 shared papersBioinformatics

Arthur KorteORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 28, 2023

permGWAS2: Enhanced and Accelerated Permutation-based Genome-Wide Association Studies

Maura John, Arthur Korte, Dominik G. Grimm

permGWAS2 improves permutation-based GWAS by reducing computational demands and accounting for population structure, achieving lower false discovery rates.

1 citation

GWAS summary statisticsstatistical model

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedAug 24, 2022

Efficient Permutation-based Genome-wide Association Studies for Normal and Skewed Phenotypic Distributions

Maura John, Markus Johannes Ankenbrand, Carolin Artmann…·Dominik G. Grimm

The paper introduces permGWAS, a permutation-based GWAS method that improves significance thresholds for skewed phenotypes and reduces false discovery rates compared to Bonferroni correction.

25 citations

ArabidopsisGWAS summary statistics

𝕏 PostBluesky