VarSCAT: A computational tool for sequence context annotations of genomic variants

: Wang Ning, Khan Sofia, Elo Laura L

Publisher: PUBLIC LIBRARY SCIENCE

: 2023

: PLoS Computational Biology

: PLOS COMPUTATIONAL BIOLOGY

: PLOS COMPUT BIOL

: e1010727

: 19

: 8

: 26

: 1553-734X

DOI: https://doi.org/10.1371/journal.pcbi.1010727(external)

: https://doi.org/10.1371/journal.pcbi.1010727(external)

: https://research.utu.fi/converis/portal/detail/Publication/181158858(external)

The sequence contexts of genomic variants play important roles in understanding biological significances of variants and potential sequencing related variant calling issues. However, methods for assessing the diverse sequence contexts of genomic variants such as tandem repeats and unambiguous annotations have been limited. Herein, we describe the Variant Sequence Context Annotation Tool (VarSCAT) for annotating the sequence contexts of genomic variants, including breakpoint ambiguities, flanking bases of variants, wildtype/mutated DNA sequences, variant nomenclatures, distances between adjacent variants, tandem repeat regions, and custom annotation with user customizable options. Our analyses demonstrate that VarSCAT is more versatile and customizable than the currently available methods or strategies for annotating variants in short tandem repeat (STR) regions or insertions and deletions (indels) with breakpoint ambiguity. Variant sequence context annotations of high-confidence human variant sets with VarSCAT revealed that more than 75% of all human individual germline and clinically relevant indels have breakpoint ambiguities. Moreover, we illustrate that more than 80% of human individual germline small variants in STR regions are indels and that the sizes of these indels correlated with STR motif sizes. VarSCAT is available from .

journal.pcbi.1010727.pdf