An efficient and scalable analysis framework for variant extraction and refinement from population-scale DNA sequence data

By Goo Jun, Mary Kate Wing, Gonçalo R. Abecasis, Hyun Min Kang. Genome Research, 2015

409 citations recorded by the source corpus.

The analysis of next-generation sequencing data is computationally and statistically challenging because of the massive volume of data and imperfect data quality. We present GotCloud, a pipeline for efficiently detecting and genotyping high-quality variants from large-scale sequencing data. GotCloud automates sequence alignment, sample-level quality control, variant calling, filtering of likely artifacts using machine-learning techniques, and genotype refinement using haplotype information. The pipeline can process thousands of samples in parallel and requires less computational resources than current alternatives. Experiments with whole-genome and exome-targeted sequence data generated by the 1000 Genomes Project show that the pipeline provides effective filtering against false positive variants and high power to detect true variants. Our pipeline has already contributed to variant detection and genotyping in several large-scale sequencing projects, including the 1000 Genomes Project and the NHLBI Exome Sequencing Project. We hope it will now prove useful to many medical sequencing studies.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b34b6603c820aaff7db76297400a3351ead68918

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Citations in the corpus

Large-scale whole-genome sequencing of three diverse Asian populations in Singapore (2018, positive): “We performed variant detection and joint genotype calling using the GotCloud pipeline.(30) We used the version that was used to produce the freeze 3 variant call set for the TOPMed Program (see URLs), adjusting for sample contamination rates.”
Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program (2019, methodology): “Variant discovery and genotype calling was performed jointly, across TOPMed studies, for all samples in a given freeze using the GotCloud 78,79 pipeline.”