Brian D. Ondov
Georgia Institute of Technology
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Featured researches published by Brian D. Ondov.
Genome Biology | 2014
Todd J. Treangen; Brian D. Ondov; Sergey Koren; Adam M. Phillippy
Whole-genome sequences are now available for many microbial species and clades, however existing whole-genome alignment methods are limited in their ability to perform sequence comparisons of multiple sequences simultaneously. Here we present the Harvest suite of core-genome alignment and visualization tools for the rapid and simultaneous analysis of thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Together they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.
BMC Bioinformatics | 2011
Brian D. Ondov; Nicholas H. Bergman; Adam M. Phillippy
BackgroundA critical output of metagenomic studies is the estimation of abundances of taxonomical or functional groups. The inherent uncertainty in assignments to these groups makes it important to consider both their hierarchical contexts and their prediction confidence. The current tools for visualizing metagenomic data, however, omit or distort quantitative hierarchical relationships and lack the facility for displaying secondary variables.ResultsHere we present Krona, a new visualization tool that allows intuitive exploration of relative abundances and confidences within the complex hierarchies of metagenomic classifications. Krona combines a variant of radial, space-filling displays with parametric coloring and interactive polar-coordinate zooming. The HTML5 and JavaScript implementation enables fully interactive charts that can be explored with any modern Web browser, without the need for installed software or plug-ins. This Web-based architecture also allows each chart to be an independent document, making them easy to share via e-mail or post to a standard Web server. To illustrate Kronas utility, we describe its application to various metagenomic data sets and its compatibility with popular metagenomic analysis tools.ConclusionsKrona is both a powerful metagenomic visualization tool and a demonstration of the potential of HTML5 for highly accessible bioinformatic visualizations. Its rich and interactive displays facilitate more informed interpretations of metagenomic analyses, while its implementation as a browser-based application makes it extremely portable and easily adopted into existing analysis packages. Both the Krona rendering code and conversion tools are freely available under a BSD open-source license, and available from: http://krona.sourceforge.net.
Journal of Bacteriology | 2009
Karla D. Passalacqua; Anjana Varadarajan; Brian D. Ondov; David T. Okou; Michael E. Zwick; Nicholas H. Bergman
Although gene expression has been studied in bacteria for decades, many aspects of the bacterial transcriptome remain poorly understood. Transcript structure, operon linkages, and information on absolute abundance all provide valuable insights into gene function and regulation, but none has ever been determined on a genome-wide scale for any bacterium. Indeed, these aspects of the prokaryotic transcriptome have been explored on a large scale in only a few instances, and consequently little is known about the absolute composition of the mRNA population within a bacterial cell. Here we report the use of a high-throughput sequencing-based approach in assembling the first comprehensive, single-nucleotide resolution view of a bacterial transcriptome. We sampled the Bacillus anthracis transcriptome under a variety of growth conditions and showed that the data provide an accurate and high-resolution map of transcript start sites and operon structure throughout the genome. Further, the sequence data identified previously nonannotated regions with significant transcriptional activity and enhanced the accuracy of existing genome annotations. Finally, our data provide estimates of absolute transcript abundance and suggest that there is significant transcriptional heterogeneity within a clonal, synchronized bacterial population. Overall, our results offer an unprecedented view of gene expression and regulation in a bacterial cell.
Genome Biology | 2016
Brian D. Ondov; Todd J. Treangen; Páll Melsted; Adam B. Mallonee; Nicholas H. Bergman; Sergey Koren; Adam M. Phillippy
Mash extends the MinHash dimensionality-reduction technique to include a pairwise mutation distance and P value significance test, enabling the efficient clustering and search of massive sequence collections. Mash reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated. We demonstrate several use cases, including the clustering of all 54,118 NCBI RefSeq genomes in 33 CPU h; real-time database search using assembled or unassembled Illumina, Pacific Biosciences, and Oxford Nanopore data; and the scalable clustering of hundreds of metagenomic samples by composition. Mash is freely released under a BSD license (https://github.com/marbl/mash).
Genome Biology | 2013
Todd J. Treangen; Sergey Koren; Daniel D. Sommer; Bo Liu; Irina Astrovskaya; Brian D. Ondov; Aaron E. Darling; Adam M. Phillippy; Mihai Pop
We describe MetAMOS, an open source and modular metagenomic assembly and analysis pipeline. MetAMOS represents an important step towards fully automated metagenomic analysis, starting with next-generation sequencing reads and producing genomic scaffolds, open-reading frames and taxonomic or functional annotations. MetAMOS can aid in reducing assembly errors, commonly encountered when assembling metagenomic samples, and improves taxonomic assignment accuracy while also reducing computational cost. MetAMOS can be downloaded from: https://github.com/treangen/MetAMOS.
Bioinformatics | 2010
Brian D. Ondov; Charles Cochran; Mark Landers; Gavin D. Meredith; Miroslav Dudas; Nicholas H. Bergman
Summary: Bisulfite sequencing allows cytosine methylation, an important epigenetic marker, to be detected via nucleotide substitutions. Since the Applied Biosystems SOLiD System uses a unique di-base encoding that increases confidence in the detection of nucleotide substitutions, it is a potentially advantageous platform for this application. However, the di-base encoding also makes reads with many nucleotide substitutions difficult to align to a reference sequence with existing tools, preventing the platforms potential utility for bisulfite sequencing from being realized. Here, we present SOCS-B, a reference-based, un-gapped alignment algorithm for the SOLiD System that is tolerant of both bisulfite-induced nucleotide substitutions and a parametric number of sequencing errors, facilitating bisulfite sequencing on this platform. An implementation of the algorithm has been integrated with the previously reported SOCS alignment tool, and was used to align CpG methylation-enriched Arabidopsis thaliana bisulfite sequence data, exhibiting a 2-fold increase in sensitivity compared to existing methods for aligning SOLiD bisulfite data. Availability: Executables, source code, and sample data are available at http://solidsoftwaretools.com/gf/project/socs/ Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Genome Announcements | 2014
Todd J. Treangen; Rosslyn Maybank; Sana Enke; Mary Beth Friss; Lynn F. Diviak; David Karaolis; Sergey Koren; Brian D. Ondov; Adam M. Phillippy; Nicholas H. Bergman; M. J. Rosovitz
ABSTRACT Staphylococcus aureus subsp. aureus ATCC 25923 is commonly used as a control strain for susceptibility testing to antibiotics and as a quality control strain for commercial products. We present the completed genome sequence for the strain, consisting of the chromosome and a 27.5-kb plasmid.
PLOS ONE | 2012
Karla D. Passalacqua; Anjana Varadarajan; Charlotte Weist; Brian D. Ondov; Benjamin Byrd; Timothy D. Read; Nicholas H. Bergman
Background Although genome-wide transcriptional analysis has been used for many years to study bacterial gene expression, many aspects of the bacterial transcriptome remain undefined. One example is antisense transcription, which has been observed in a number of bacteria, though the function of antisense transcripts, and their distribution across the bacterial genome, is still unclear. Methodology/Principal Findings Single-stranded RNA-seq results revealed a widespread and non-random pattern of antisense transcription covering more than two thirds of the B. anthracis genome. Our analysis revealed a variety of antisense structural patterns, suggesting multiple mechanisms of antisense transcription. The data revealed several instances of sense and antisense expression changes in different growth conditions, suggesting that antisense transcription may play a role in the ways in which B. anthracis responds to its environment. Significantly, genome-wide antisense expression occurred at consistently higher levels on the lagging strand, while the leading strand showed very little antisense activity. Intrasample gene expression comparisons revealed a gene dosage effect in all growth conditions, where genes farthest from the origin showed the lowest overall range of expression for both sense and antisense directed transcription. Additionally, transcription from both strands was verified using a novel strand-specific assay. The variety of structural patterns we observed in antisense transcription suggests multiple mechanisms for this phenomenon, suggesting that some antisense transcription may play a role in regulating the expression of key genes, while some may be due to chromosome replication dynamics and transcriptional noise. Conclusions/Significance Although the variety of structural patterns we observed in antisense transcription suggest multiple mechanisms for antisense expression, our data also clearly indicate that antisense transcription may play a genome-wide role in regulating the expression of key genes in Bacillus species. This study illustrates the surprising complexity of prokaryotic RNA abundance for both strands of a bacterial chromosome.
bioRxiv | 2014
Todd J. Treangen; Brian D. Ondov; Sergey Koren; Adam M. Phillippy
Though many microbial species or clades now have hundreds of sequenced genomes, existing whole-genome alignment methods do not efficiently handle comparisons on this scale. Here we present the Harvest suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Combined they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.
Genome Announcements | 2013
Robin Harrington; Brian D. Ondov; Diana Radune; Mary Beth Friss; Joy Klubnik; Lynn F. Diviak; Jonathan Hnath; Stephen R. Cendrowski; Thomas E. Blank; David Karaolis; Arthur M. Friedlander; James Burans; M. J. Rosovitz; Todd J. Treangen; Adam M. Phillippy; Nicholas H. Bergman
ABSTRACT The Bacillus anthracis Carbosap genome, which includes the pXO1 and pXO2 plasmids, has been shown to encode the major B. anthracis virulence factors, yet this strains attenuation has not yet been explained. Here we report the draft genome sequence of this strain, and a comparison to fully virulent B. anthracis.