» Articles » PMID: 35751599

ClearCNV: CNV Calling from NGS Panel Data in the Presence of Ambiguity and Noise

Overview
Journal Bioinformatics
Specialty Biology
Date 2022 Jun 25
PMID 35751599
Authors
Affiliations
Soon will be listed here.
Abstract

Motivation: While the identification of small variants in panel sequencing data can be considered a solved problem, the identification of larger, multi-exon copy number variants (CNVs) still poses a considerable challenge. Thus, CNV calling has not been established in all laboratories performing panel sequencing. At the same time, such laboratories have accumulated large datasets and thus have the need to identify CNVs on their data to close the diagnostic gap.

Results: In this article, we present our method clearCNV that addresses this need in two ways. First, it helps laboratories to properly assign datasets to enrichment kits. Based on homogeneous subsets of data, clearCNV identifies CNVs affecting the targeted regions. Using real-world datasets and validation, we show that our method is highly competitive with previous methods and preferable in terms of specificity.

Availability And Implementation: The software is available for free under a permissible license at https://github.com/bihealth/clear-cnv.

Supplementary Information: Supplementary data are available at Bioinformatics online.

Citing Articles

Detection of germline CNVs from gene panel data: benchmarking the state of the art.

Munte E, Roca C, Del Valle J, Feliubadalo L, Pineda M, Gel B Brief Bioinform. 2024; 26(1).

PMID: 39668338 PMC: 11637760. DOI: 10.1093/bib/bbae645.


Compositae-ParaLoss-1272: A complementary sunflower-specific probe set reduces paralogs in phylogenomic analyses of complex systems.

Moore-Pollard E, Jones D, Mandel J Appl Plant Sci. 2024; 12(1):e11568.

PMID: 38369976 PMC: 10873820. DOI: 10.1002/aps3.11568.