SvABA: genome-wide detection of structural variants and indels by local assembly.

Genome Res
Authors
Keywords
Abstract

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA's performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (

Year of Publication
2018
Journal
Genome Res
Volume
28
Issue
4
Pages
581-591
Date Published
2018 04
ISSN
1549-5469
DOI
10.1101/gr.221028.117
PubMed ID
29535149
PubMed Central ID
PMC5880247
Links
Grant list
R01 CA188228 / CA / NCI NIH HHS / United States
U24 CA210978 / CA / NCI NIH HHS / United States
U54 CA143798 / CA / NCI NIH HHS / United States
T32 HG002295 / HG / NHGRI NIH HHS / United States
R01 CA215489 / CA / NCI NIH HHS / United States