MARS
MARS refines and detects structural variants (SVs), specifically indels, in haplotype-resolved diploid genome assemblies using linked-read sequencing to enable high-sensitivity genotyping and phasing across multiple samples.
Key Features:
- Haplotype-resolved assembly compatibility: Operates on haplotype-resolved diploid assemblies to call and refine structural variants.
- Multiple alignment-based refinement: Uses a multiple alignment-based approach to define and refine SV calls across multiple samples.
- Linked-reads integration: Integrates linked-read sequencing data to improve sensitivity and accuracy of SV detection and phasing.
- High-sensitivity genotyping and phasing: Provides high-sensitivity genotyping and phasing of SVs across multiple samples.
- Population-wide analysis: Aligns and analyzes SVs across large cohorts to define population-level variant representations.
- Validation against Mendelian inheritance and PacBio HiFi reads: Demonstrated validation rates of 73%–87% for indels in diploid assemblies when evaluated with Mendelian inheritance patterns and PacBio HiFi reads.
Scientific Applications:
- Genomic research: High-resolution SV genotyping and refinement across multiple diploid samples.
- Population genetics: Analysis of SV distribution and refinement at population scale.
- Disease genomics: Identification and phasing of SVs relevant to disease-associated genetic variation.
Methodology:
MARS applies a multiple alignment-based approach that integrates linked-read sequencing data to refine SV detection in diploid assemblies and evaluates detected SVs against Mendelian inheritance patterns with validation using PacBio HiFi reads.
Topics
Details
- License:
- MIT
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python, JavaScript, C++, C, Shell
- Added:
- 2/20/2022
- Last Updated:
- 2/20/2022
Operations
Publications
Zhang L, Sidow A, Zhou X. MARS: a tool for haplotype-resolved population-based structural variation detection. Unknown Journal. 2021. doi:10.1101/2021.09.27.462061.