ArticleBioinformatics (Oxford, England)2020
Vargas: heuristic-free alignment for assessing linear and graph read aligners.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Theseus: fast and optimal affine-gap sequence-to-graph alignment.Bioinformatics (Oxford, England) · 2026Article
- Exploiting uniqueness: seed-chain-extend alignment on elastic founder graphs.Bioinformatics (Oxford, England) · 2025Article
- A survey of sequence-to-graph mapping algorithms in the pangenome era.Genome biology · 2025Review
- Embed-Search-Align: DNA sequence alignment using Transformer models.Bioinformatics (Oxford, England) · 2025Article
- SigAlign: an alignment algorithm guided by explicit similarity criteria.Nucleic acids research · 2024Article
- A compressive seeding algorithm in conjunction with reordering-based compression.Bioinformatics (Oxford, England) · 2024Article
- Pan-genome de Bruijn graph using the bidirectional FM-index.BMC bioinformatics · 2023Article
- Performance optimization in DNA short-read alignment.Bioinformatics (Oxford, England) · 2022Review
- Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space.Cell genomics · 2022Article
- Population-scale genotyping of structural variation in the era of long-read sequencing.Computational and structural biotechnology journal · 2022Review
- A variant selection framework for genome graphs.Bioinformatics (Oxford, England) · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
motivationRead alignment is central to many aspects of modern genomics. Most aligners use heuristics to accelerate processing, but these heuristics can fail to find the optimal alignments of reads. Alignment accuracy is typically measured through simulated reads; however, the simulated location may not be the (only) location with the optimal alignment score.
resultsVargas implements a heuristic-free algorithm guaranteed to find the highest-scoring alignment for real sequencing reads to a linear or graph genome. With semiglobal and local alignment modes and affine gap and quality-scaled mismatch penalties, it can implement the scoring functions of commonly used aligners to calculate optimal alignments. While this is computationally intensive, Vargas uses multi-core parallelization and vectorized (SIMD) instructions to make it practical to optimally align large numbers of reads, achieving a maximum speed of 456 billion cell updates per second. We demonstrate how these 'gold standard' Vargas alignments can be used to improve heuristic alignment accuracy by optimizing command-line parameters in Bowtie 2, BWA-maximal exact match and vg to align more reads correctly. AVAILABILITY AND IMPLEMENTATION: Source code implemented in C++ and compiled binary releases are available at https://github.com/langmead-lab/vargas under the MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.