Ontology highlight
ABSTRACT: Motivation
Generation of genotype data has been growing exponentially over the last decade. With the large size of recent datasets comes a storage and computational burden with ever increasing costs. To reduce this burden we propose XSI, a file format with reduced storage footprint that also allows computation on the compressed data and we show how this can improve future analyses.Results
We show that XSI allows for a file size reduction of 4-20x compared to compressed BCF and demonstrate its potential for "compressive genomics" on the UK Biobank whole genome sequencing genotypes with 8x faster loading times, 5x faster run of homozygozity computation, 30x faster dot products computation, and 280x faster allele counts.Availability
The xSqueezeIt file format (XSI) spe
SUBMITTER: Wertenbroek R
PROVIDER: S-EPMC9344850 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature