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

Downloads

Links