FindSV
FindSV detects and annotates structural variants from whole-genome sequencing (WGS) data to support genetic diagnosis by identifying copy-number variants, complex rearrangements, uniparental disomy (UPD), and short tandem repeat (STR) expansions.
Key Features:
- Variant Calling: Uses TIDDIT and CNVnator to call a wide range of structural variants, including large chromosomal rearrangements and small deletions/duplications.
- Variant Merging: Merges similar variants to streamline downstream analysis.
- Output Files: Generates unfiltered per-caller VCFs, a combined unfiltered VCF (_Combined.vcf), an annotated and filtered VCF (_FindSV.vcf), and a chromosome-specific ploidy tab file.
- Annotation: Annotates and filters variants using VEP, frequency databases, genmod, and custom scripts.
- Detection Scope: Supports detection of complex SVs such as ring chromosomes and insertional translocations, and identification of UPD and STR expansions.
Scientific Applications:
- Diagnostic Yield Enhancement: Increases diagnostic yield in monogenic WGS cohorts by detecting pathogenic SNVs and SVs that were missed by chromosomal microarray analysis (CMA).
- Complex Variant Detection: Identifies complex structural variants including ring chromosomes, insertional translocations, and cases of uniparental disomy such as Prader-Willi syndrome.
- Comprehensive Genetic Testing: Enables integrated analysis of SNVs, SVs, UPD, and STR expansions within a single WGS framework and provides positional information across cohorts.
Methodology:
FindSV performs variant calling with TIDDIT and CNVnator, merges similar variants, generates per-caller and combined VCFs plus a ploidy tab, and annotates/filters variants using VEP, frequency databases, genmod, and custom scripts; it was validated on a retrospective cohort with known CNVs.
Topics
Details
- Tool Type:
- command-line tool, workflow
- Programming Languages:
- Shell, Python
- Added:
- 1/14/2020
- Last Updated:
- 12/28/2020
Operations
Publications
Lindstrand A, Eisfeldt J, Pettersson M, Carvalho CMB, Kvarnung M, Grigelioniene G, Anderlid B, Bjerin O, Gustavsson P, Hammarsjö A, Georgii-Hemming P, Iwarsson E, Johansson-Soller M, Lagerstedt-Robinson K, Lieden A, Magnusson M, Martin M, Malmgren H, Nordenskjöld M, Norling A, Sahlin E, Stranneheim H, Tham E, Wincent J, Ygberg S, Wedell A, Wirta V, Nordgren A, Lundin J, Nilsson D. From cytogenetics to cytogenomics: whole-genome sequencing as a first-line test comprehensively captures the diverse spectrum of disease-causing genetic variation underlying intellectual disability. Genome Medicine. 2019;11(1). doi:10.1186/s13073-019-0675-1. PMID:31694722. PMCID:PMC6836550.