Article ; Online: Dysgu: efficient structural variant calling using short or long reads.
2022 Volume 50, Issue 9, Page(s) e53
Abstract: Structural variation (SV) plays a fundamental role in genome evolution and can underlie inherited or acquired diseases such as cancer. Long-read sequencing technologies have led to improvements in the characterization of structural variants (SVs), ... ...
Abstract | Structural variation (SV) plays a fundamental role in genome evolution and can underlie inherited or acquired diseases such as cancer. Long-read sequencing technologies have led to improvements in the characterization of structural variants (SVs), although paired-end sequencing offers better scalability. Here, we present dysgu, which calls SVs or indels using paired-end or long reads. Dysgu detects signals from alignment gaps, discordant and supplementary mappings, and generates consensus contigs, before classifying events using machine learning. Additional SVs are identified by remapping of anomalous sequences. Dysgu outperforms existing state-of-the-art tools using paired-end or long-reads, offering high sensitivity and precision whilst being among the fastest tools to run. We find that combining low coverage paired-end and long-reads is competitive in terms of performance with long-reads at higher coverage values. |
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MeSH term(s) | Genomic Structural Variation ; High-Throughput Nucleotide Sequencing ; INDEL Mutation ; Sequence Analysis, DNA ; Software |
Language | English |
Publishing date | 2022-01-29 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 186809-3 |
ISSN | 1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048 |
ISSN (online) | 1362-4962 ; 1362-4954 |
ISSN | 0301-5610 ; 0305-1048 |
DOI | 10.1093/nar/gkac039 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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