» Articles » PMID: 25503062

ViVar: a Comprehensive Platform for the Analysis and Visualization of Structural Genomic Variation

Overview
Journal PLoS One
Date 2014 Dec 16
PMID 25503062
Citations 28
Authors
Affiliations
Soon will be listed here.
Abstract

Structural genomic variations play an important role in human disease and phenotypic diversity. With the rise of high-throughput sequencing tools, mate-pair/paired-end/single-read sequencing has become an important technique for the detection and exploration of structural variation. Several analysis tools exist to handle different parts and aspects of such sequencing based structural variation analyses pipelines. A comprehensive analysis platform to handle all steps, from processing the sequencing data, to the discovery and visualization of structural variants, is missing. The ViVar platform is built to handle the discovery of structural variants, from Depth Of Coverage analysis, aberrant read pair clustering to split read analysis. ViVar provides you with powerful visualization options, enables easy reporting of results and better usability and data management. The platform facilitates the processing, analysis and visualization, of structural variation based on massive parallel sequencing data, enabling the rapid identification of disease loci or genes. ViVar allows you to scale your analysis with your work load over multiple (cloud) servers, has user access control to keep your data safe and is easy expandable as analysis techniques advance. URL: https://www.cmgg.be/vivar/

Citing Articles

Aligning genotyping and copy number data in single trophectoderm biopsies for aneuploidy prediction: uncovering incomplete concordance.

De Witte L, Baetens M, Tilleman K, Vanden Meerschaut F, Janssens S, Van Tongerloo A Hum Reprod Open. 2024; 2024(4):hoae056.

PMID: 39391861 PMC: 11461285. DOI: 10.1093/hropen/hoae056.


Predicting cytogenetic risk in multiple myeloma using conventional whole-body MRI, spinal dynamic contrast-enhanced MRI, and spinal diffusion-weighted imaging.

Den Berghe T, Verberckmoes B, Kint N, Wallaert S, De Vos N, Algoet C Insights Imaging. 2024; 15(1):106.

PMID: 38597979 PMC: 11006637. DOI: 10.1186/s13244-024-01672-1.


Various repair events following CRISPR/Cas9-based mutational correction of an infertility-related mutation in mouse embryos.

Bekaert B, Boel A, Rybouchkin A, Cosemans G, Declercq S, Chuva de Sousa Lopes S J Assist Reprod Genet. 2024; 41(6):1605-1617.

PMID: 38557805 PMC: 11224219. DOI: 10.1007/s10815-024-03095-9.


Retained chromosomal integrity following CRISPR-Cas9-based mutational correction in human embryos.

Bekaert B, Boel A, De Witte L, Vandenberghe W, Popovic M, Stamatiadis P Mol Ther. 2023; 31(8):2326-2341.

PMID: 37376733 PMC: 10422011. DOI: 10.1016/j.ymthe.2023.06.013.


The thorny complexities of visualization research for clinical settings: A case study from genomics.

Stahlbom E, Molin J, Ynnerman A, Lundstrom C Front Bioinform. 2023; 3:1112649.

PMID: 37063648 PMC: 10090312. DOI: 10.3389/fbinf.2023.1112649.


References
1.
Fujita P, Rhead B, Zweig A, Hinrichs A, Karolchik D, Cline M . The UCSC Genome Browser database: update 2011. Nucleic Acids Res. 2010; 39(Database issue):D876-82. PMC: 3242726. DOI: 10.1093/nar/gkq963. View

2.
Medvedev P, Stanciu M, Brudno M . Computational methods for discovering structural variation with next-generation sequencing. Nat Methods. 2009; 6(11 Suppl):S13-20. DOI: 10.1038/nmeth.1374. View

3.
OBrien T, Ritz A, Raphael B, Laidlaw D . Gremlin: an interactive visualization model for analyzing genomic rearrangements. IEEE Trans Vis Comput Graph. 2010; 16(6):918-26. DOI: 10.1109/TVCG.2010.163. View

4.
Feuk L, Carson A, Scherer S . Structural variation in the human genome. Nat Rev Genet. 2006; 7(2):85-97. DOI: 10.1038/nrg1767. View

5.
Xie C, Tammi M . CNV-seq, a new method to detect copy number variation using high-throughput sequencing. BMC Bioinformatics. 2009; 10:80. PMC: 2667514. DOI: 10.1186/1471-2105-10-80. View