Author

Bernd Holleczek

German Cancer Research CenterORCID 0000-0001-8759-4371Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Hermann BrenneriD· 3 shared Adam Stuart KibeliD· 2 shared Agnieszka MichaeliD· 2 shared Ali Amin Al OlamaiD· 2 shared Amanda B. SpurdleiD· 2 shared Anders Martin DaleiD· 2 shared Australian Prostate Cancer BioResource (APCB)· 2 shared Ben SchöttkeriD· 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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3 shared papersGenetics

Hermann BrennerORCID

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3 papers

Recent·Most cited

GeneticsBreast Cancer ResearchPeer-reviewedJan 4, 2022

Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Thomas U. Ahearn, Haoyu Zhang, Kyriaki Michailidou…·Peter T. Simpson

The paper identifies breast cancer risk variants associated with tumor subtypes and shows their differential effects on luminal and non-luminal subtypes.

33 citations

humanGWAS summary statistics

𝕏 PostBluesky

GeneticsEuropean Journal of Human GeneticsPeer-reviewedJun 8, 2020

The effect of sample size on polygenic hazard models for prostate cancer

Roshan A. Karunamuni, Minh‐Phuong Huynh‐Le, Chun Chieh Fan…·Tyler M. Seibert

This paper evaluates how sample size affects polygenic hazard score models for prostate cancer, finding that 20-30k samples are needed for discovery models, but 10k suffice if SNPs are pre-established.

11 citations

humanGWAS summary statistics

𝕏 PostBluesky

GeneticsbioRxivPreprintApr 26, 2019

A genetic hazard score to personalize prostate cancer screening, applied to population data

Minh‐Phuong Huynh‐Le, Chun Chieh Fan, Roshan A. Karunamuni…·Tyler M. Seibert

The paper evaluates a polygenic hazard score for prostate cancer screening, showing it improves positive predictive value by adjusting screening age based on genetic risk.

DOI 10.1101/619718

humanGWAS summary statistics

𝕏 PostBluesky