Rob Egan

Bio: Rob Egan is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Metagenomics & Genome. The author has an hindex of 10, co-authored 17 publications receiving 2570 citations. Previous affiliations of Rob Egan include Joint Genome Institute.

MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities

Abstract: Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. It automatically forms hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat.

Metagenomic discovery of biomass-degrading genes and genomes from cow rumen.

Abstract: The paucity of enzymes that efficiently deconstruct plant polysaccharides represents a major bottleneck for industrial-scale conversion of cellulosic biomass into biofuels. Cow rumen microbes specialize in degradation of cellulosic plant material, but most members of this complex community resist cultivation. To characterize biomass-degrading genes and genomes, we sequenced and analyzed 268 gigabases of metagenomic DNA from microbes adherent to plant fiber incubated in cow rumen. From these data, we identified 27,755 putative carbohydrate-active genes and expressed 90 candidate proteins, of which 57% were enzymatically active against cellulosic substrates. We also assembled 15 uncultured microbial genomes, which were validated by complementary methods including single-cell genome sequencing. These data sets provide a substantially expanded catalog of genes and genomes participating in the deconstruction of cellulosic biomass.

De novoIdentification of DNA Modifications Enabled by Genome-Guided Nanopore Signal Processing

Abstract: Advances in nanopore sequencing technology have enabled investigation of the full catalogue of covalent DNA modifications. We present the first algorithm for the identification of modified nucleotides without the need for prior training data along with the open source software implementation, nanoraw. Nanoraw accurately assigns contiguous raw nanopore signal to genomic positions, enabling novel data visualization, and increasing power and accuracy for the discovery of covalently modified bases in native DNA. Ground truth case studies utilizing synthetically methylated DNA show the capacity to identify three distinct methylation marks, 4mC, 5mC, and 6mA, in seven distinct sequence contexts without any changes to the algorithm. We demonstrate quantitative reproducibility simultaneously identifying 5mC and 6mA in native E. coli across biological replicates processed in different labs. Finally we propose a pipeline for the comprehensive discovery of DNA modifications in any genome without a priori knowledge of their chemical identities.

ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies

Abstract: Motivation: Researchers need general purpose methods for objectively evaluating the accuracy of single and metagenome assemblies and for automatically detecting any errors they may contain. Current methods do not fully meet this need because they require a reference, only consider one of the many aspects of assembly quality or lack statistical justification, and none are designed to evaluate metagenome assemblies. Results: In this article, we present an Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences’ own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process. Availability: ALE is released as open source software under the UoI/ NCSA license at http://www.alescore.org. It is implemented in C and Python.

HipMer: an extreme-scale de novo genome assembler

Abstract: De novo whole genome assembly reconstructs genomic sequences from short, overlapping, and potentially erroneous DNA segments and is one of the most important computations in modern genomics. This work presents HipMer, the first high-quality end-to-end de novo assembler designed for extreme scale analysis, via efficient parallelization of the Meraculous code. First, we significantly improve scalability of parallel k-mer analysis for complex repetitive genomes that exhibit skewed frequency distributions. Next, we optimize the traversal of the de Bruijn graph of k-mers by employing a novel communication-avoiding parallel algorithm in a variety of use-case scenarios. Finally, we parallelize the Meraculous scaffolding modules by leveraging the one-sided communication capabilities of the Unified Parallel C while effectively mitigating load imbalance. Large-scale results on a Cray XC30 using grand-challenge genomes demonstrate efficient performance and scalability on thousands of cores. Overall, our pipeline accelerates Meraculous performance by orders of magnitude, enabling the complete assembly of the human genome in just 8.4 minutes on 15K cores of the Cray XC30, and creating unprecedented capability for extreme-scale genomic analysis.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs

Abstract: Motivation Genomics has revolutionized biological research, but quality assessment of the resulting assembled sequences is complicated and remains mostly limited to technical measures like N50. Results We propose a measure for quantitative assessment of genome assembly and annotation completeness based on evolutionarily informed expectations of gene content. We implemented the assessment procedure in open-source software, with sets of Benchmarking Universal Single-Copy Orthologs, named BUSCO. Availability and implementation Software implemented in Python and datasets available for download from http://busco.ezlab.org. Contact evgeny.zdobnov@unige.ch Supplementary information Supplementary data are available at Bioinformatics online.

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

BUSCO: Assessing Genome Assembly and Annotation Completeness with Single-Copy Orthologs

Abstract: MOTIVATION Genomics has revolutionized biological research, but quality assessment of the resulting assembled sequences is complicated and remains mostly limited to technical measures like N50. RESULTS We propose a measure for quantitative assessment of genome assembly and annotation completeness based on evolutionarily informed expectations of gene content. We implemented the assessment procedure in open-source software, with sets of Benchmarking Universal Single-Copy Orthologs, named BUSCO. AVAILABILITY AND IMPLEMENTATION Software implemented in Python and datasets available for download from http://busco.ezlab.org. CONTACT evgeny.zdobnov@unige.ch SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

MetaSPAdes: A new versatile metagenomic assembler

Abstract: While metagenomics has emerged as a technology of choice for analyzing bacterial populations, the assembly of metagenomic data remains challenging, thus stifling biological discoveries. Moreover, recent studies revealed that complex bacterial populations may be composed from dozens of related strains, thus further amplifying the challenge of metagenomic assembly. metaSPAdes addresses various challenges of metagenomic assembly by capitalizing on computational ideas that proved to be useful in assemblies of single cells and highly polymorphic diploid genomes. We benchmark metaSPAdes against other state-of-the-art metagenome assemblers and demonstrate that it results in high-quality assemblies across diverse data sets.