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intansv: an R package for integrative analysis of structural variations

Identification of structural variations between individuals is very important for the understanding of phenotype variations and diseases. Despite the existence of dozens of programs for prediction of structural variations, none of them is the golden standard in this field and the results of multiple...

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Detalles Bibliográficos
Autores principales: Jia, Lihua, Liu, Na, Huang, Fangfang, Zhou, Zhengfu, He, Xin, Li, Haoran, Wang, Zhizhan, Yao, Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7194084/
https://www.ncbi.nlm.nih.gov/pubmed/32377445
http://dx.doi.org/10.7717/peerj.8867
Descripción
Sumario:Identification of structural variations between individuals is very important for the understanding of phenotype variations and diseases. Despite the existence of dozens of programs for prediction of structural variations, none of them is the golden standard in this field and the results of multiple programs were usually integrated to get more reliable predictions. Annotation and visualization of structural variations are important for the understanding of their functions. However, no program provides these functions currently as far as we are concerned. We report an R package, intansv, which can integrate the predictions of multiple programs as well as annotate and visualize structural variations. The source code and the help manual of intansv is freely available at https://github.com/venyao/intansv and http://www.bioconductor.org/packages/devel/bioc/html/intansv.html.