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Copy‐number analysis by base‐level normalization: An intuitive visualization tool for evaluating copy number variations.

Authors :
Kim, Hongkyung
Shim, Yeeun
Lee, Taek Gyu
Won, Dongju
Choi, Jong Rak
Shin, Saeam
Lee, Seung‐Tae
Source :
Clinical Genetics. Jan2023, Vol. 103 Issue 1, p35-44. 10p.
Publication Year :
2023

Abstract

Next‐generation sequencing (NGS) facilitates comprehensive molecular analyses that help with diagnosing unsolved disorders. In addition to detecting single‐nucleotide variations and small insertions/deletions, bioinformatics tools can identify copy number variations (CNVs) in NGS data, which improves the diagnostic yield. However, due to the possibility of false positives, subsequent confirmation tests are generally performed. Here, we introduce Copy‐number Analysis by BAse‐level NormAlization (CABANA), a visualization tool that allows users to intuitively identify candidate CNVs using the normalized single‐base‐level read depth calculated from NGS data. To demonstrate how CABANA works, NGS data were obtained from 474 patients with neuromuscular disorders. CNVs were screened using a conventional bioinformatics tool, ExomeDepth, and then we normalized and visualized those data at the single‐base level using CABANA, followed by manual inspection by geneticists to filter out false positives and determine candidate CNVs. In doing so, we identified 31 candidate CNVs (7%) in 474 patients and subsequently confirmed all of them to be true using multiplex ligation‐dependent probe amplification. The performance of CABANA was deemed acceptable by comparing its diagnostic yield with previous data about neuromuscular disorders. Despite some limitations, we expect CABANA to help researchers accurately identify CNVs and reduce the need for subsequent confirmation testing. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00099163
Volume :
103
Issue :
1
Database :
Academic Search Index
Journal :
Clinical Genetics
Publication Type :
Academic Journal
Accession number :
160717055
Full Text :
https://doi.org/10.1111/cge.14236