FishingCNV: a Graphical Software Package for Detecting Rare Copy Number Variations in Exome-sequencing Data

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2013 Mar 30

PMID 23539306

Citations 32

Authors

Yuhao Shi

Jacek Majewski

Affiliations

Soon will be listed here.

Abstract

Summary: Rare copy number variations (CNVs) are frequent causes of genetic diseases. We developed a graphical software package based on a novel approach that can consistently identify CNVs of all types (homozygous deletions, heterozygous deletions, heterozygous duplications) from exome-sequencing data without the need of a paired control. The algorithm compares coverage depth in a test sample against a background distribution of control samples and uses principal component analysis to remove batch effects. It is user friendly and can be run on a personal computer.

Availability And Implementation: The main scripts are implemented in R (2.15), and the GUI is created using Java 1.6. It can be run on all major operating systems. A non-GUI version for pipeline implementation is also available. The program is freely available online: https://sourceforge.net/projects/fishingcnv/

Supplementary Information: Supplementary data are available at Bioinformatics online.

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Multiple Arterial Dissections and Connective Tissue Abnormalities.

Erhart P, Korfer D, Dihlmann S, Qiao J, Hausser I, Ringleb P J Clin Med. 2022; 11(12).

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Diagnostic yield of exome sequencing in congenital vertical talus.

Tayebi N, Charng W, Dickson P, Dobbs M, Gurnett C Eur J Med Genet. 2022; 65(6):104514.

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Diagnosis of SLC25A46-related pontocerebellar hypoplasia in two siblings with fulminant neonatal course: role of postmortem CT and whole genomic analysis: a case report.

Yamada M, Suzuki H, Adachi H, Noguchi A, Miya F, Takahashi T BMC Neurol. 2022; 22(1):20.

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Benchmarking germline CNV calling tools from exome sequencing data.

Gordeeva V, Sharova E, Babalyan K, Sultanov R, Govorun V, Arapidi G Sci Rep. 2021; 11(1):14416.

PMID: 34257369 PMC: 8277855. DOI: 10.1038/s41598-021-93878-2.