Allele balance bias identifies systematic genotyping errors and false disease associations

Francesc Muyas, Mattia Bosio, Anna Puig, Hana Susak, Laura Domènech, Georgia Escaramis, Luis Zapata, German Demidov, Xavier P. Estivill, Raquel Rabionet, Stephan Ossowski

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
JournalHuman Mutation
DOIs
Publication statusAccepted/In press - 1 Jan 2018

Fingerprint

Alleles
Exome
Genotype
High-Throughput Nucleotide Sequencing
Rare Diseases
Mutation
Neoplasms

Keywords

  • allele balance
  • false positive variant calls
  • genetic variant detection
  • systematic NGS errors

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Muyas, F., Bosio, M., Puig, A., Susak, H., Domènech, L., Escaramis, G., ... Ossowski, S. (Accepted/In press). Allele balance bias identifies systematic genotyping errors and false disease associations. Human Mutation. https://doi.org/10.1002/humu.23674

Allele balance bias identifies systematic genotyping errors and false disease associations. / Muyas, Francesc; Bosio, Mattia; Puig, Anna; Susak, Hana; Domènech, Laura; Escaramis, Georgia; Zapata, Luis; Demidov, German; Estivill, Xavier P.; Rabionet, Raquel; Ossowski, Stephan.

In: Human Mutation, 01.01.2018.

Research output: Contribution to journalArticle

Muyas, F, Bosio, M, Puig, A, Susak, H, Domènech, L, Escaramis, G, Zapata, L, Demidov, G, Estivill, XP, Rabionet, R & Ossowski, S 2018, 'Allele balance bias identifies systematic genotyping errors and false disease associations', Human Mutation. https://doi.org/10.1002/humu.23674
Muyas, Francesc ; Bosio, Mattia ; Puig, Anna ; Susak, Hana ; Domènech, Laura ; Escaramis, Georgia ; Zapata, Luis ; Demidov, German ; Estivill, Xavier P. ; Rabionet, Raquel ; Ossowski, Stephan. / Allele balance bias identifies systematic genotyping errors and false disease associations. In: Human Mutation. 2018.
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