Repeat- and error-aware comparison of deletions
Author(s) -
Roland Wittler,
Tobias Marschall,
Alexander Schönhuth,
Veli Mäkinen
Publication year - 2015
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/btv304
Subject(s) - computer science , redundancy (engineering) , comparability , matching (statistics) , data mining , open source , relevance (law) , computational biology , information retrieval , software , programming language , biology , statistics , mathematics , political science , law , combinatorics , operating system
The number of reported genetic variants is rapidly growing, empowered by ever faster accumulation of next-generation sequencing data. A major issue is comparability. Standards that address the combined problem of inaccurately predicted breakpoints and repeat-induced ambiguities are missing. This decisively lowers the quality of 'consensus' callsets and hampers the removal of duplicate entries in variant databases, which can have deleterious effects in downstream analyses.
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