Assemblytics
Assemblytics detects and analyzes genomic variants by comparing de novo genome assemblies to reference genomes and employs an anchor filtering method to improve robustness in repetitive regions.
Key Features:
- Alignment-based detection: Detects variants by aligning de novo genome assemblies to reference genomes.
- Anchor filtering approach: Uses an anchor filtering technique to mitigate issues caused by repetitive elements and reduce spurious variant calls.
- Variant classification: Identifies six distinct classes of variants based on their alignment signatures.
- Application flexibility: Supports comparisons of aberrant genomes such as human cancers to reference genomes and identification of genetic differences between related species.
- Visualizations: Provides multiple visualizations to explore the genomic distribution and characteristics of detected variants.
Scientific Applications:
- Cancer genomics: Comparison of cancer genomes to reference genomes to identify mutations and structural variations relevant to oncogenesis and disease progression.
- Comparative genomics: Identification of genetic differences between related species to inform evolutionary and functional analyses.
- Genome annotation and evolutionary studies: Classification of variants and variant distributions to support genome annotation and studies of genomic evolution.
Methodology:
Align de novo assembled genomes to reference genomes, apply anchor filtering to enhance detection in repetitive regions, and identify six variant classes characterized by distinct alignment signatures.
Topics
Details
- License:
- Unlicense
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R, Perl, Python
- Added:
- 8/4/2019
- Last Updated:
- 11/24/2024
Operations
Publications
Nattestad M, Schatz MC. Assemblytics: a web analytics tool for the detection of variants from an assembly. Bioinformatics. 2016;32(19):3021-3023. doi:10.1093/bioinformatics/btw369. PMID:27318204. PMCID:PMC6191160.
PMID: 27318204
PMCID: PMC6191160
Funding: - National Human Genome Research Institute: R01-HG006677
- National Science Foundation: DBI-1350041