PBGI
PBGI automates identification of bacterial genomes from short-read and long-read sequencing data generated by Illumina, PacBio, and Oxford Nanopore to support microbial genome identification and downstream genomic analyses.
Key Features:
- Automated Analysis: Automates processing of sequencing reads to identify bacterial genomes.
- Customization: Permits tailored analysis parameters and workflows to suit specific datasets.
- Platform Compatibility: Supports short-reads and long-reads from Illumina, PacBio, and Oxford Nanopore.
- Accuracy: Evaluation on practical datasets demonstrates accurate bacterial identification for both short-read and long-read analyses.
Scientific Applications:
- Microbiology Research: Enables precise bacterial genome identification in microbiology studies.
- Clinical Diagnostics: Applicable to clinical diagnostics that require accurate bacterial identification from sequencing data.
- Environmental Microbiome Studies: Supports identification of bacterial genomes within environmental microbiome sequencing datasets.
Methodology:
An automated pipeline that processes sequencing reads to identify bacterial genomes and integrates various computational techniques to analyze genomic data.
Topics
Details
- Maturity:
- Emerging
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python
- Added:
- 11/29/2021
- Last Updated:
- 11/29/2021
Operations
Publications
Liu J, Sun J, Liu Y. Effective Identification of Bacterial Genomes From Short and Long Read Sequencing Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2022;19(5):2806-2816. doi:10.1109/tcbb.2021.3095164. PMID:34232887.
PMID: 34232887
Funding: - National Key R&D Program of China: 2018YFC1603800, 2018YFC1603802, 2020YFA0908700, 2020YFA0908702
- National Natural Science Foundation of China: 61872115
Downloads
- Source codehttps://github.com/lyotvincent/PBGI/releases