General, orders-of-magnitude faster whole-genome analysis with genotype representation graphs

enable a level of scalability and methodological flexibility that is not achievable with traditional genotype formats.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-04-11
DOI
https://doi.org/10.64898/2026.04.10.717786
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

General, orders-of-magnitude faster whole-genome analysis with genotype representation graphs

Xinzhu Wei, Drew DeHaas, Chris Adonizio, Ziqing Pan
bioRxiv (Cold Spring Harbor Laboratory)
Genetic Associations and Epidemiology
article

General, orders-of-magnitude faster whole-genome analysis with genotype representation graphs

Xinzhu Wei, Drew DeHaas, Chris Adonizio, Ziqing Pan
article en

Abstract

enable a level of scalability and methodological flexibility that is not achievable with traditional genotype formats.

bioRxiv (Cold Spring Harbor Laboratory)
Cornell University (US)
National Science Foundation, National Institutes of Health
Life in Land
Openalex Percentile: Top 25%
Genetic Associations and Epidemiology
DOIOpen Access PDFOpenAlex
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General, orders-of-magnitude faster whole-genome analysis with genotype representation graphs — Xinzhu Wei, Drew DeHaas, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS