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unCOVERApp: an interactive graphical application for clinical assessment of sequence coverage at the base-pair level
Author(s) -
Emanuela Iovino,
Marco Seri,
Tommaso Pippucci
Publication year - 2020
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/btaa730
Subject(s) - annotation , computer science , calculator , set (abstract data type) , data mining , sequence (biology) , artificial intelligence , biology , genetics , programming language , operating system
Next-generation sequencing is increasingly adopted in the clinical practice largely thanks to concurrent advancements in bioinformatic tools for variant detection and annotation. However, the need to assess sequencing quality at the base-pair level still poses challenges for diagnostic accuracy. One of the most popular quality parameters is the percentage of targeted bases characterized by low depth of coverage (DoC). These regions potentially 'hide' clinically relevant variants, but no annotation is usually returned with them. However, visualizing low-DoC data with their potential functional and clinical consequences may be useful to prioritize inspection of specific regions before re-sequencing all coverage gaps or making assertions about completeness of the diagnostic test. To meet this need, we have developed unCOVERApp, an interactive application for graphical inspection and clinical annotation of low-DoC genomic regions containing genes.

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