ExplorePipolin
ExplorePipolin identifies, reconstructs, and annotates pipolins in draft, contig-based bacterial genomes to enable analysis of mobile genetic elements and their role in antimicrobial resistance.
Key Features:
- Implementation: Python-based bioinformatics pipeline for automated processing of bacterial genome assemblies.
- Screening and Reconstruction: Screens draft, contig-based bacterial genomes to identify pipolins and reconstructs their structure by piecing together contigs when necessary.
- Annotation Capabilities: Annotates pipolin boundaries and encoded genes using a custom database tailored for pipolin elements.
- Pipolin Characterization: Focuses on MGEs characterized by integrative and plasmidic nature and the presence of a primer-independent DNA polymerase.
- Output Formats: Produces standard file formats suitable for downstream comparative genomics analyses.
Scientific Applications:
- Pipolin detection and structural analysis: Identification and reconstruction of pipolin architectures from fragmented draft genomes.
- Comparative genomics of MGEs: Generation of annotated datasets for comparative analyses of mobile genetic elements across bacterial isolates.
- Antimicrobial resistance research: Investigation of the contribution of pipolins to the spread and evolution of antimicrobial resistance genes.
Methodology:
Implemented in Python; screens contig-based draft bacterial genomes, reconstructs pipolins by piecing together contigs, annotates boundaries and genes using a custom pipolin database, and exports results in standard comparative-genomics file formats.
Topics
Details
- License:
- GPL-3.0
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python
- Added:
- 2/26/2023
- Last Updated:
- 11/24/2024
Operations
Publications
Chuprikova L, Mateo-Cáceres V, de Toro M, Redrejo-Rodríguez M. ExplorePipolin: reconstruction and annotation of piPolB-encoding bacterial mobile elements from draft genomes. Bioinformatics Advances. 2022;2(1). doi:10.1093/bioadv/vbac056. PMID:36699382. PMCID:PMC9710591.