ArticleHuman mutation2019
Allele balance bias identifies systematic genotyping errors and false disease associations.
Article in Human mutation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 36 citations in OpenAlex.
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- Chimeric reference panels for genomic imputation.Genetics · 2026Article
- Genotype imputation from low-coverage WGS using haplotype reference panels in cultivated strawberry.BMC genomics · 2025Article
- Tutorial: guidelines for quality filtering of whole-exome and whole-genome sequencing data for population-scale association analyses.Nature protocols · 2025Review
- Sodium azide mutagenesis induces a unique pattern of mutations.PLoS genetics · 2025Article
- How to handle high subgenome sequence similarity in allopolyploid Fragaria x ananassa: linkage disequilibrium based variant filtering.BMC genomics · 2024Article
- Unveiling the Genome-Wide Consequences of Range Expansion and Mating System Transitions in Primula vulgaris.Genome biology and evolution · 2024Article
- Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Microsatellite break-induced replication generates highly mutagenized extrachromosomal circular DNAs.NAR cancer · 2024Article
- Revisiting mutagenesis at non-B DNA motifs in the human genome.Nature structural & molecular biology · 2023Article
- Performance comparisons between clustering models for reconstructing NGS results from technical replicates.Frontiers in genetics · 2023Article
- Validation of Polygenic Risk Scores for Coronary Heart Disease in a Middle Eastern Cohort Using Whole Genome Sequencing.Circulation. Genomic and precision medicine · 2022Article
- A Fast and Robust Strategy to Remove Variant-Level Artifacts in Alzheimer Disease Sequencing Project Data.Neurology. Genetics · 2022Article
- Moment estimators of relatedness from low-depth whole-genome sequencing data.BMC bioinformatics · 2022Article
- Establishing analytical validity of BeadChip array genotype data by comparison to whole-genome sequence and standard benchmark datasets.BMC medical genomics · 2022Article
- Article
- Efficient and flexible Integration of variant characteristics in rare variant association studies using integrated nested Laplace approximation.PLoS computational biology · 2021Article
- The rate and spectrum of mosaic mutations during embryogenesis revealed by RNA sequencing of 49 tissues.Genome medicine · 2020Article
- Hardy-Weinberg Equilibrium in the Large Scale Genomic Sequencing Era.Frontiers in genetics · 2020Article
- eDiVA-Classification and prioritization of pathogenic variants for clinical diagnostics.Human mutation · 2019Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 2 countries.
Funding
Abstract
In recent years, next-generation sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors, and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the AB distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state-of-the-art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies. Availability: https://github.com/Francesc-Muyas/ABB.
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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.