Ontology highlight
ABSTRACT: Motivation
With high-throughput DNA sequencing costs dropping <$1000 for human genomes, data storage, retrieval and analysis are the major bottlenecks in biological studies. To address the large-data challenges, we advocate a clean separation between the evidence collection and the inference in variant calling. We define and implement a Genome Query Language (GQL) that allows for the rapid collection of evidence needed for calling variants.Results
We provide a number of cases to showcase the use of GQL for complex evidence collection, such as the evidence for large structural variations. Specifically, typical GQL queries can be written in 5-10 lines of high-level code and search large datasets (100 GB) in minutes. We also demonstrate its complementarity with other variant c
SUBMITTER: Kozanitis C
PROVIDER: S-EPMC3866549 | biostudies-literature | 2014 Jan
REPOSITORIES: biostudies-literature