SVs

SVs reconstructs and characterizes large and complex genomic structural variants by leveraging long-fragment sequencing data such as 10x Genomics and performing sequence assembly at SV breakpoints to delineate disrupted genomic architecture.


Key Features:

  • Identification of large-scale structural variants: Detects a wide range of structural variants, including large and complex events across the genome.
  • Sequence assembly at breakpoints: Performs precise sequence assembly at SV breakpoints to reconstruct affected genomic sequence and architecture.
  • Utilization of long-fragment information: Integrates long-fragment sequencing data from platforms like 10x Genomics to improve resolution of complex SVs.
  • Integration of multiple computational methods: Applies multiple computational approaches tailored for different classes of SVs, zygosities, and size ranges.

Scientific Applications:

  • Medicine and molecular biology: Enables analysis of SV contributions to genetic disorders and disease mechanisms.
  • Gene expression regulation: Supports investigation of how structural variants influence gene expression patterns and regulatory elements.
  • Ethnic diversity and evolutionary studies: Facilitates characterization of SVs that contribute to population genetic differences and studies of large-scale chromosome evolution.

Methodology:

Infers structural variants across the full spectrum of large and complex variations and integrates multiple computational methods tailored for different classes of SVs, zygosities, and size ranges.

Topics

Details

License:
MIT
Programming Languages:
Python
Added:
1/14/2020
Last Updated:
1/16/2021

Operations

Publications

Mahmoud M, Gobet N, Cruz-Dávalos DI, Mounier N, Dessimoz C, Sedlazeck FJ. Structural variant calling: the long and the short of it. Genome Biology. 2019;20(1). doi:10.1186/s13059-019-1828-7. PMID:31747936. PMCID:PMC6868818.

PMID: 31747936
PMCID: PMC6868818
Funding: - Foundation for the National Institutes of Health: UM1 HG008898 - Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung: 150654, 31003A-143914, 31003A_173182 - H2020 European Research Council: CAMERA