SeqArray—a storage-efficient high-performance data format for WGS variant calls | Zendy

Xiuwen Zheng | Zendy; Stephanie M. Gogarten | Zendy; Michael C. Lawrence | Zendy; Adrienne M. Stilp | Zendy; Matthew P. Conomos | Zendy; Bruce S. Weir | Zendy; Cathy C. Laurie | Zendy; David Levine | Zendy

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SeqArray—a storage-efficient high-performance data format for WGS variant calls

Author(s) -

Xiuwen Zheng,

Stephanie M. Gogarten,

Michael C. Lawrence,

Adrienne M. Stilp,

Matthew P. Conomos,

Bruce S. Weir,

Cathy C. Laurie,

David Levine

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx145

Subject(s) - computer science , database , operating system

Whole-genome sequencing (WGS) data are being generated at an unprecedented rate. Analysis of WGS data requires a flexible data format to store the different types of DNA variation. Variant call format (VCF) is a general text-based format developed to store variant genotypes and their annotations. However, VCF files are large and data retrieval is relatively slow. Here we introduce a new WGS variant data format implemented in the R/Bioconductor package 'SeqArray' for storing variant calls in an array-oriented manner which provides the same capabilities as VCF, but with multiple high compression options and data access using high-performance parallel computing.

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