SUMMARY: The JCVI pan-genome pipeline is a collection of programs to run PanOCT and tools that support and extend the capabilities of PanOCT. PanOCT (pan-genome ortholog clustering tool) is a tool for pan-genome analysis of closely related prokaryotic species or strains. The JCVI Pan-Genome Pipeline wrapper invokes command-line utilities that prepare input genomes, invoke third-party tools such as NCBI Blast+, run PanOCT, generate a consensus pan-genome, annotate features of the pan-genome, detect sets of genes of interest such as antimicrobial resistance (AMR) genes and generate figures, tables and html pages to visualize the results. The pipeline can run in a hierarchical mode, lowering the RAM and compute resources used. AVAILABILITY AND IMPLEMENTATION: Source code, demo data, and detailed documentation are freely available at https://github.com/JCVenterInstitute/PanGenomePipeline.

BACKGROUND: Bacterial pan-genomes, comprised of conserved and variable genes across multiple sequenced bacterial genomes, allow for identification of genomic regions that are phylogenetically discriminating or functionally important. Pan-genomes consist of large amounts of data, which can restrict researchers ability to locate and analyze these regions. Multiple software packages are available to visualize pan-genomes, but currently their ability to address these concerns are limited by using only pre-computed data sets, prioritizing core over variable gene clusters, or by not accounting for pan-chromosome positioning in the viewer. RESULTS: We introduce PanACEA (Pan-genome Atlas with Chromosome Explorer and Analyzer), which utilizes locally-computed interactive web-pages to view ordered pan-genome data. It consists of multi-tiered, hierarchical display pages that extend from pan-chromosomes to both core and variable regions to single genes. Regions and genes are functionally annotated to allow for rapid searching and visual identification of regions of interest with the option that user-supplied genomic phylogenies and metadata can be incorporated. PanACEA's memory and time requirements are within the capacities of standard laptops. The capability of PanACEA as a research tool is demonstrated by highlighting a variable region important in differentiating strains of Enterobacter hormaechei. CONCLUSIONS: PanACEA can rapidly translate the results of pan-chromosome programs into an intuitive and interactive visual representation. It will empower researchers to visually explore and identify regions of the pan-chromosome that are most biologically interesting, and to obtain publication quality images of these regions.

SUMMARY: LOCUST is a custom sequence locus typer tool for classifying microbial genomes. It provides a fully automated opportunity to customize the classification of genome-wide nucleotide variant data most relevant to biological research. AVAILABILITY AND IMPLEMENTATION: Source code, demo data, and detailed documentation are freely available at http://sourceforge.net/projects/locustyper . CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The growth of sequence data has been accompanied by an increasing need to analyze data on distributed computer clusters. The use of these systems for routine analysis requires scalable and robust software for data management of large datasets. Software is also needed to simplify data management and make large-scale bioinformatics analysis accessible and reproducible to a wide class of target users. RESULTS: We have developed a workflow management system named Ergatis that enables users to build, execute and monitor pipelines for computational analysis of genomics data. Ergatis contains preconfigured components and template pipelines for a number of common bioinformatics tasks such as prokaryotic genome annotation and genome comparisons. Outputs from many of these components can be loaded into a Chado relational database. Ergatis was designed to be accessible to a broad class of users and provides a user friendly, web-based interface. Ergatis supports high-throughput batch processing on distributed compute clusters and has been used for data management in a number of genome annotation and comparative genomics projects. AVAILABILITY: Ergatis is an open-source project and is freely available at http://ergatis.sourceforge.net.