Comparison of three bioinformatics tools in the detection of ASD candidate variants from whole exome sequencing data

Autor: Apurba Shil, Liron Levin, Hava Golan, Gal Meiri, Analya Michaelovski, Yair Sadaka, Adi Aran, Ilan Dinstein, Idan Menashe
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Druh dokumentu: article
ISSN: 2045-2322
DOI: 10.1038/s41598-023-46258-x
Popis: Abstract Autism spectrum disorder (ASD) is a heterogenous multifactorial neurodevelopmental condition with a significant genetic susceptibility component. Thus, identifying genetic variations associated with ASD is a complex task. Whole-exome sequencing (WES) is an effective approach for detecting extremely rare protein-coding single-nucleotide variants (SNVs) and short insertions/deletions (INDELs). However, interpreting these variants' functional and clinical consequences requires integrating multifaceted genomic information. We compared the concordance and effectiveness of three bioinformatics tools in detecting ASD candidate variants (SNVs and short INDELs) from WES data of 220 ASD family trios registered in the National Autism Database of Israel. We studied only rare (
Databáze: Directory of Open Access Journals
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