Allele balance bias identifies systematic genotyping errors and false disease associations.
Date
2019-01-01ICR Author
Author
Muyas, F
Bosio, M
Puig, A
Susak, H
Domènech, L
Escaramis, G
Zapata, L
Demidov, G
Estivill, X
Rabionet, R
Ossowski, S
Type
Journal Article
Metadata
Show full item recordAbstract
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.
Collections
Subject
allele balance
false positive variant calls
genetic variant detection
systematic NGS errors
Alleles
Bias
Databases, Genetic
Disease
Genetic Association Studies
Genome, Human
Genotype
Genotyping Techniques
Humans
Models, Genetic
Polymorphism, Single Nucleotide
Research team
Directorate for CEC
Language
eng
Date accepted
2018-10-20
License start date
2019-01-01
Citation
Human Mutation, 2019, 40 (1), pp. 115 - 126
Publisher
WILEY