A5
A5 performs de novo genome assembly by integrating read cleaning, error correction, assembly, and quality control to produce draft genomes from Illumina sequencing data.
Key Features:
- Automation and Integration: Chains established algorithms and custom-developed programs to automate the de novo assembly workflow, including read cleaning, error correction, assembly, and quality control.
- Quality Control and Parameter Optimization: Implements algorithms for quality control and automated parameter selection to enhance assembly accuracy without extensive manual tuning.
- Performance Benchmarking: Produces assemblies comparable to SOAPdenovo and reduces broken protein-coding sequences by over 50% relative to SOAPdenovo.
- Versatility with Sequencing Data: Capable of assembling Illumina sequence data from libraries constructed using the Nextera protocol, which differ from mechanically sheared libraries.
- Computational Efficiency: Can assemble typical bacterial genomes on standard desktop or laptop hardware within two hours, depending on sequencing depth of coverage.
Scientific Applications:
- Microbial genomics: De novo assembly of bacterial genomes from Illumina/Nextera data to generate draft genomes for downstream genomic analyses.
- Evolutionary studies: Production of assemblies to support comparative genomics and evolutionary analyses.
- Personalized medicine: Generation of draft genomes to support genomic analyses relevant to personalized medicine.
Methodology:
The pipeline chains established and custom assembly algorithms and performs sequence data cleaning, error correction, assembly, quality control, and automated parameter selection.
Topics
Details
- License:
- GPL-3.0
- Maturity:
- Mature
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Mac
- Programming Languages:
- Perl
- Added:
- 1/13/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Tritt A, Eisen JA, Facciotti MT, Darling AE. An Integrated Pipeline for de Novo Assembly of Microbial Genomes. PLoS ONE. 2012;7(9):e42304. doi:10.1371/journal.pone.0042304. PMID:23028432. PMCID:PMC3441570.