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: |
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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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