MUM
MUM detects structural variants in genomic assemblies by analyzing whole-genome alignments to identify insertions, deletions, tandem duplications, inversions, and translocations greater than 50 base pairs for assembly-based SV discovery and comparative genomics.
Key Features:
- Alignment engine: Operates on whole-genome alignments produced by MUMmer's nucmer.
- SV types detected: Identifies insertions, deletions, tandem duplications, inversions, and translocations.
- Size threshold: Calls structural variants larger than 50 base pairs.
- Input data: Designed to work on contiguous de-novo assemblies derived from third-generation sequencing technologies.
- Implementation: Packaged as a single bash script for automated processing of alignments.
- Benchmarking and performance: Validated against five other whole-genome-alignment SV callers on simulated yeast, plant, and human datasets with superior performance on simulated data and comparable results on two real human genome datasets.
Scientific Applications:
- Assembly-based SV discovery: Detection of structural variants directly from de-novo genome assemblies.
- Inversion identification: Accurate calling of inversions as part of the SV spectrum.
- Comparative genomics: Analysis of structural variation across species including yeast, plants, and humans.
- Method benchmarking: Evaluation and comparison of SV-calling performance using simulated and real genome datasets.
Methodology:
MUM analyzes whole-genome alignments generated by MUMmer's nucmer and parses those alignments to call insertions, deletions, tandem duplications, inversions, and translocations larger than 50 bp.
Topics
Details
- License:
- GPL-3.0
- Tool Type:
- command-line tool
- Programming Languages:
- Shell, Bash
- Added:
- 1/18/2021
- Last Updated:
- 3/2/2021
Operations
Publications
O’Donnell S, Fischer G. MUM&Co: accurate detection of all SV types through whole-genome alignment. Bioinformatics. 2020;36(10):3242-3243. doi:10.1093/bioinformatics/btaa115. PMID:32096823.
PMID: 32096823
Funding: - Agence Nationale de la Recherche: ANR-16-CE12-0019