ArticleNature biotechnology2021
A unified haplotype-based method for accurate and comprehensive variant calling.
Article in Nature biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 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
68 citing papers in PubMed, 118 citations in OpenAlex.
- Olaparib, durvalumab, and cyclophosphamide, and a prognostic blood signature in platinum-sensitive ovarian cancer: the randomized phase 2 SOLACE2 trial.Nature communications · 2025Trial
- ClairS: a deep-learning method for long-read tumor-normal pair somatic small variant calling.Nature methods · 2026Article
- Impact of preanalytical factors on liquid biopsy in the canine cancer model.Communications medicine · 2026Article
- DoBSeqWF: a framework for sensitive detection of individual genetic variation in pooled sequencing data.NAR genomics and bioinformatics · 2026Article
- Benchmarking within-sample minority variant detection with short-read sequencing inbioRxiv : the preprint server for biology · 2026Article
- Autoimmune HLA alleles and neoantigens predict myelodysplastic syndrome outcomes after allogeneic HSCT: A CIBMTR analysis.iScience · 2026Article
- Benchmarking long-read variant calling in diploid and polyploid genomes: insights from human and plants.BMC genomics · 2026Article
- ChoCallate: a computational pipeline for consensus germline variant calling in genomic sequencing data.PeerJ · 2026Article
- Article
- OctopuSV and TentacleSV: a one-stop toolkit for multi-sample, cross-platform structural variant comparison and analysis.Bioinformatics (Oxford, England) · 2025Article
- ClairS-TO: a deep-learning method for long-read tumor-only somatic small variant calling.Nature communications · 2025Article
- Genetic variation in recalcitrant repetitive regions of theGenome research · 2025Article
- Evolutionary unpredictability in cancer model systems.Scientific reports · 2025Article
- Review
- Finding easy regions for short-read variant calling from pangenome data.GigaScience · 2025Article
- Comprehensive genetic screening of 70 severe adolescent idiopathic scoliosis probands reveals novel pathogenic variants and syndromic associations.Frontiers in medicine · 2025Article
- Systematic phenotype and genotype characterization of Moebius syndrome.Genetics in medicine open · 2025Article
- Generative haplotype prediction outperforms statistical methods for small variant detection in next-generation sequencing data.Bioinformatics (Oxford, England) · 2024Article
- Insertions and Deletions: Computational Methods, Evolutionary Dynamics, and Biological Applications.Molecular biology and evolution · 2024Review
- Benchmarking UMI-aware and standard variant callers for low frequency ctDNA variant detection.BMC genomics · 2024Article
8 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
3 authors at 3 institutions in 2 countries.
Funding
Abstract
Almost all haplotype-based variant callers were designed specifically for detecting common germline variation in diploid populations, and give suboptimal results in other scenarios. Here we present Octopus, a variant caller that uses a polymorphic Bayesian genotyping model capable of modeling sequencing data from a range of experimental designs within a unified haplotype-aware framework. Octopus combines sequencing reads and prior information to phase-called genotypes of arbitrary ploidy, including those with somatic mutations. We show that Octopus accurately calls germline variants in individuals, including single nucleotide variants, indels and small complex replacements such as microinversions. Using a synthetic tumor data set derived from clean sequencing data from a sample with known germline haplotypes and observed mutations in a large cohort of tumor samples, we show that Octopus is more sensitive to low-frequency somatic variation, yet calls considerably fewer false positives than other methods. Octopus also outputs realigned evidence BAM files to aid validation and interpretation.
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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.