Manta
Manta detects structural variants (SVs) and indels from next-generation sequencing (NGS) data, providing rapid germline and somatic variant calling for downstream genomic analyses.
Key Features:
- Speed and Efficiency: Processes high-coverage human genomes rapidly on standard compute hardware (e.g., NA12878 at 50× genomic coverage in under 20 minutes).
- Comprehensive Variant Detection: Detects structural variants, medium-sized indels, and large insertions using paired-end and split-read evidence.
- Optimized Scoring Models: Implements scoring models tailored for diploid germline analysis and somatic tumor–normal pairs, with call quality assessed by pedigree-consistency checks and comparisons to COSMIC variants.
- High-Resolution Assembly: Performs local assembly to resolve a higher fraction of variant breakpoints to base-pair resolution to aid downstream annotation and clinical interpretation.
Scientific Applications:
- Genomic Research: Enables comprehensive analysis of genetic variation for studies of disease genetics and evolutionary biology.
- Clinical Genomics: Supports structural variant and indel detection in clinical genomic analyses to identify clinically significant variants.
- Cancer Genomics: Enables somatic mutation and structural variant detection in tumor–normal sample pairs for cancer research and targeted therapy investigations.
Methodology:
Uses paired-end and split-read evidence, local assembly to base-pair resolution, and specialized scoring models for diploid germline and somatic tumor–normal analyses; validation methods include pedigree-consistency checks and comparisons to COSMIC.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux
- Programming Languages:
- C++, Python
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Data Inputs & Outputs
Variant calling
Publications
Chen X, Schulz-Trieglaff O, Shaw R, Barnes B, Schlesinger F, Källberg M, Cox AJ, Kruglyak S, Saunders CT. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics. 2015;32(8):1220-1222. doi:10.1093/bioinformatics/btv710. PMID:26647377.