BIGwas: Single-command quality control and association testing for multi-cohort and biobank-scale GWAS/PheWAS data | Zendy

Jan Christian Kässens | Zendy; Lars Wienbrandt | Zendy; David Ellinghaus | Zendy

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BIGwas: Single-command quality control and association testing for multi-cohort and biobank-scale GWAS/PheWAS data

Author(s) -

Jan Christian Kässens,

Lars Wienbrandt,

David Ellinghaus

Publication year - 2021

Publication title -

gigascience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.947

H-Index - 54

ISSN - 2047-217X

DOI - 10.1093/gigascience/giab047

Subject(s) - biobank , genome wide association study , computer science , scale (ratio) , genetic association , association (psychology) , medicine , computational biology , bioinformatics , single nucleotide polymorphism , biology , genetics , psychology , genotype , gene , physics , quantum mechanics , psychotherapist

Genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) involving 1 million GWAS samples from dozens of population-based biobanks present a considerable computational challenge and are carried out by large scientific groups under great expenditure of time and personnel. Automating these processes requires highly efficient and scalable methods and software, but so far there is no workflow solution to easily process 1 million GWAS samples.

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