RESUMEN
The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, thus impairing analysis accuracy. Here we present a graph reference genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.0 million insertions and deletions (indels). The pipeline processes one whole-genome sequencing sample in 6.5 h using a system with 36 CPU cores. We show that using a graph genome reference improves read mapping sensitivity and produces a 0.5% increase in variant calling recall, with unaffected specificity. Structural variations incorporated into a graph genome can be genotyped accurately under a unified framework. Finally, we show that iterative augmentation of graph genomes yields incremental gains in variant calling accuracy. Our implementation is an important advance toward fulfilling the promise of graph genomes to radically enhance the scalability and accuracy of genomic analyses.
Asunto(s)
Genoma Humano/genética , Genómica/métodos , Humanos , Polimorfismo de Nucleótido Simple/genética , Alineación de Secuencia/métodos , Análisis de Secuencia de ADN/métodos , Eliminación de Secuencia/genética , Secuenciación Completa del Genoma/métodosRESUMEN
Motivation: Several tools exist to count Mendelian violations in family trios by comparing variants at the same genomic positions. This naive variant comparison, however, fails to assess regions where multiple variants need to be examined together, resulting in reduced accuracy of existing Mendelian violation checking tools. Results: We introduce VBT, a trio concordance analysis tool, which identifies Mendelian violations by approximately solving the 3-way variant matching problem to resolve variant representation differences in family trios. We show that VBT outperforms previous trio comparison methods by accuracy. Availability and implementation: VBT is implemented in C++ and source code is available under GNU GPLv3 license at the following URL: https://github.com/sbg/VBT-TrioAnalysis.git. Supplementary information: Supplementary data are available at Bioinformatics online.
