ArticleNature biotechnology2019
An open resource for accurately benchmarking small variant and reference calls.
Article in Nature biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 219 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
219 citing papers in PubMed.
- SNP calling, haplotype phasing and allele-specific analysis with long RNA-seq reads.Nature methods · 2026Article
- Large-scale whole-genome sequencing reveals the landscape and health implications of de novo mutations.Nature medicine · 2026Article
- Haplotype-resolved DiMeLo-seq maps centromeric chromatin in a complete diploid human genome.Cell genomics · 2026Article
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- Long-Read Sequencing in CKD Diagnostics: Breaking Genomic Barriers and Expanding Global Inclusion.Kidney international reports · 2026Review
- Artificial Intelligence and Genomic Data Analysis: New Frontiers in Precision Medicine.International journal of molecular sciences · 2026Review
- Pansoma, a machine learning tool for identifying somatic variants using pangenome graphs.bioRxiv : the preprint server for biology · 2026Article
- VCboost: reducing false positives in long-read variant calling for single-nucleotide polymorphism and indel detection in challenging genomic regions.Briefings in bioinformatics · 2026Article
- Article
- Article
- Aardvark: sifting through differences in a mound of variants.Genome biology · 2026Article
- Ensilication preserves high-molecular weight native DNA for clinical long-read sequencing.Genome biology · 2026Article
- Benchmarking Q40 sequencing for sensitive and efficient detection of rare genomic variants.Genome biology · 2026Article
- Article
- LongAllele: a joint inference framework for allele-specific analysis on long-read bulk and single-cell RNA sequencing.bioRxiv : the preprint server for biology · 2026Article
- From fragments to full pictures: how long-read sequencing platforms are revolutionizing oncology research.Molecular biology reports · 2026Review
- Distinct repair outcomes from single and convergent replication fork collapse.Nature structural & molecular biology · 2026Article
- IMPACT OF FLUORESCENT DYES ON MUTATIONS IN NEXT GENERATION SEQUENCING LIRBARY PREPARATION.bioRxiv : the preprint server for biology · 2026Article
- Characterization of subclonal variants in HG002 Genome in a Bottle reference material as a resource for benchmarking variant callers.Cell genomics · 2026Article
- A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long-Read Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
159 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Benchmark small variant calls are required for developing, optimizing and assessing the performance of sequencing and bioinformatics methods. Here, as part of the Genome in a Bottle (GIAB) Consortium, we apply a reproducible, cloud-based pipeline to integrate multiple short- and linked-read sequencing datasets and provide benchmark calls for human genomes. We generate benchmark calls for one previously analyzed GIAB sample, as well as six genomes from the Personal Genome Project. These new genomes have broad, open consent, making this a 'first of its kind' resource that is available to the community for multiple downstream applications. We produce 17% more benchmark single nucleotide variations, 176% more indels and 12% larger benchmark regions than previously published GIAB benchmarks. We demonstrate that this benchmark reliably identifies errors in existing callsets and highlight challenges in interpreting performance metrics when using benchmarks that are not perfect or comprehensive. Finally, we identify strengths and weaknesses of callsets by stratifying performance according to variant type and genome context.
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What OpenQuestion holds
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.