GRACy

GRACy reconstructs and annotates human cytomegalovirus (HCMV) genomes from Illumina sequencing data to support genotyping, variant detection, and downstream genomic analyses.


Key Features:

  • Read Quality Filtering: Automated modules perform read quality filtering to select high-quality Illumina sequencing reads for reliable downstream analysis.
  • Genotyping: Facilitates accurate genotyping of HCMV strains to characterize viral diversity.
  • De Novo Assembly: Supports de novo genome assembly from raw sequence data to reconstruct complete or near-complete HCMV genomes without a reference.
  • Variant Detection: Provides variant analysis capabilities to identify mutations of potential clinical significance.
  • Genome Annotation: Automates annotation of genomic features and links them to functional information.
  • Data Submission: Implements pathways for submitting sequence data and annotations to public databases.

Scientific Applications:

  • Viral evolution: Enables comparative analyses to investigate HCMV evolutionary dynamics.
  • Pathogenesis studies: Supports genomic investigations into determinants of HCMV pathogenesis.
  • Resistance mechanism analysis: Facilitates detection and study of mutations associated with antiviral resistance.
  • Clinical and diagnostic genomics: Provides genomic data and annotations to inform clinical research and diagnostic investigations.

Methodology:

Performs automated read quality filtering, HCMV genotyping, de novo assembly, variant detection, genome annotation, and data submission workflows and is implemented in Python; it has been tested on simulated and experimental datasets.

Topics

Details

License:
GPL-3.0
Tool Type:
command-line tool, desktop application
Programming Languages:
Python
Added:
3/19/2021
Last Updated:
3/30/2021

Operations

Publications

Camiolo S, Suárez NM, Chalka A, Venturini C, Breuer J, Davison AJ. GRACy: A tool for analysing human cytomegalovirus sequence data. Virus Evolution. 2020;7(1). doi:10.1093/ve/veaa099. PMID:33505707. PMCID:PMC7816668.

PMID: 33505707
PMCID: PMC7816668
Funding: - Wellcome Trust: 204870/Z/16/Z