PanACoTA

PanACoTA performs large-scale microbial comparative genomics by automating genome retrieval, consistent annotation, pangenome and core-genome construction, and phylogenetic inference.


Key Features:

  • Modular design: A modular workflow separates downloading, quality filtering, annotation, pangenome construction, core-genome variant generation, and phylogenetic inference into independent steps.
  • Genome retrieval: Automated downloading of available genomes for a specified microbial species.
  • Quality and redundancy filtering: Quality control and redundancy checks to select high-quality, nonredundant genomes for analysis.
  • Uniform annotation: Standardized annotation applied consistently across all genomes.
  • Pangenome and core-genome construction: Building comprehensive pangenomes and multiple core-genome variants and producing their alignments.
  • Phylogenetic inference: Rapid generation of phylogenetic trees to assess evolutionary relationships.
  • Implementation: Implemented in Python3.

Scientific Applications:

  • Pangenome characterization: Analysis of gene repertoires across strains or species to define core and accessory genomes.
  • Comparative genomics: Comparative analysis across large sets of microbial genomes to study genomic variation and content differences.
  • Evolutionary inference: Reconstruction of phylogenetic relationships and evolutionary trajectories among microbial genomes.
  • Study of diversity and adaptation: Investigation of microbial diversity, adaptation, and gene content changes across populations or environments.

Methodology:

Automated genome retrieval, quality and redundancy filtering, standardized annotation, construction of pangenomes and multiple core-genome alignments, and generation of phylogenetic trees.

Topics

Details

Programming Languages:
Python
Added:
1/18/2021
Last Updated:
1/22/2021

Operations

Publications

Perrin A, Rocha EP. PanACoTA: A modular tool for massive microbial comparative genomics. Unknown Journal. 2020. doi:10.1101/2020.09.11.293472.