SeqArray

SeqArray stores and enables fast analysis of whole-genome sequencing (WGS) variant call data, including single nucleotide variants (SNVs), insertions and deletions (indels), and structural variations, to support large-scale genomic analyses.

Key Features:

• Array-Oriented Data Storage: Stores variant calls in an array-oriented format to reduce file size and improve data retrieval efficiency compared to text-based VCF files.
• High Compression Options: Implements multiple high-compression options; for example, using 1000 Genomes Phase 3 data SeqArray achieves a file size of 2.6 Gb versus 14.0 Gb for VCF and 12.3 Gb for BCF (binary VCF).
• Efficient Data Access: Employs high-performance parallel computing to accelerate data access, with genotype reading benchmarks reported two to three times faster than the htslib C library with BCF files.
• Accelerated Computational Tasks: Delivers faster variant analytics such as allele frequency calculation, reported as over five times faster than PLINK v1.9 on VCF/BCF and more than sixteen times faster than vcftools.
• Integration with R/Bioconductor: Integrates with the R/Bioconductor ecosystem to enable use of Bioconductor packages for downstream WGS variant data analysis.

Scientific Applications:

• Population Genomics: Supports analysis of population-scale variant distributions and allele frequencies across thousands of individuals.
• Genetic Association Studies: Facilitates large-scale association analyses by providing compressed storage and rapid genotype access for variant call datasets.
• Personalized Medicine Research: Enables processing of cohort-scale WGS data to support variant-based investigations relevant to personalized medicine.

Methodology:

Stores variant calls in an array-oriented format, applies multiple compression options, and uses high-performance parallel computing for data access and computations; benchmark comparisons were performed against VCF/BCF using the htslib C library, PLINK v1.9, and vcftools on the 1000 Genomes Phase 3 dataset.