Open AccessSVPV: a structural variant prediction viewer for paired-end sequencing datasets
Author(s) -
Jacob E. Munro,
Sally L. Dunwoodie,
Eleni Giannoulatou
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx117
Subject(s) - computer science , annotation , visualization , software , data mining , graphical user interface , population , artificial intelligence , demography , sociology , programming language
A wide range of algorithms exist for the prediction of structural variants (SVs) from paired-end whole genome sequencing (WGS) alignments. It is essential for the purpose of quality control to be able to visualize, compare and contrast the data underlying the predictions across multiple different algorithms.
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