MOTIVATION: Analysis of multiple genomes requires sophisticated tools that provide search, visualization, interactivity and data export. Comparative genomics datasets tend to be large and complex, making development of these tools difficult. In addition to scalability, comparative genomics tools must also provide user-friendly interfaces such that the research scientist can explore complex data with minimal technical expertise. RESULTS: We describe a new version of the Sybil software package and its application to the important human pathogen Streptococcus pneumoniae. This new software provides a feature-rich set of comparative genomics tools for inspection of multiple genome structures, mining of orthologous gene families and identification of potential vaccine candidates. AVAILABILITY: The S.pneumoniae resource is online at http://strepneumo-sybil.igs.umaryland.edu. The software, database and website are available for download as a portable virtual machine and from http://sourceforge.net/projects/sybil.

MOTIVATION: The relative ease and low cost of current generation sequencing technologies has led to a dramatic increase in the number of sequenced genomes for species across the tree of life. This increasing volume of data requires tools that can quickly compare multiple whole-genome sequences, millions of base pairs in length, to aid in the study of populations, pan-genomes, and genome evolution. RESULTS: We present a new multiple alignment tool for whole genomes named Mugsy. Mugsy is computationally efficient and can align 31 Streptococcus pneumoniae genomes in less than 2 hours producing alignments that compare favorably to other tools. Mugsy is also the fastest program evaluated for the multiple alignment of assembled human chromosome sequences from four individuals. Mugsy does not require a reference sequence, can align mixtures of assembled draft and completed genome data, and is robust in identifying a rich complement of genetic variation including duplications, rearrangements, and large-scale gain and loss of sequence. AVAILABILITY: Mugsy is free, open-source software available from http://mugsy.sf.net.

BACKGROUND: Rapid annotation and comparisons of genomes from multiple isolates (pan-genomes) is becoming commonplace due to advances in sequencing technology. Genome annotations can contain inconsistencies and errors that hinder comparative analysis even within a single species. Tools are needed to compare and improve annotation quality across sets of closely related genomes. RESULTS: We introduce a new tool, Mugsy-Annotator, that identifies orthologs and evaluates annotation quality in prokaryotic genomes using whole genome multiple alignment. Mugsy-Annotator identifies anomalies in annotated gene structures, including inconsistently located translation initiation sites and disrupted genes due to draft genome sequencing or pseudogenes. An evaluation of species pan-genomes using the tool indicates that such anomalies are common, especially at translation initiation sites. Mugsy-Annotator reports alternate annotations that improve consistency and are candidates for further review. CONCLUSIONS: Whole genome multiple alignment can be used to efficiently identify orthologs and annotation problem areas in a bacterial pan-genome. Comparisons of annotated gene structures within a species may show more variation than is actually present in the genome, indicating errors in genome annotation. Our new tool Mugsy-Annotator assists re-annotation efforts by highlighting edits that improve annotation consistency.

BACKGROUND: Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. RESULTS: We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. CONCLUSION: The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

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.