Sequence Analysis Tools Research Articles

BamBam: genome sequence analysis tools for biologists.

BackgroundMassive computational power is needed to analyze the genomic data produced by next-generation sequencing, but extensive computational experience and specific knowledge of algorithms should not be necessary to run genomic analyses or interpret their results.FindingsWe present BamBam, a package of tools for genome sequence analysis. BamBam contains tools that facilitate summarizing data from BAM alignment files and identifying features such as SNPs, indels, and haplotypes represented in those alignments.ConclusionsBamBam provides a powerful and convenient framework to analyze genome sequence data contained in BAM files.Electronic supplementary materialThe online version of this article (doi:10.1186/1756-0500-7-829) contains supplementary material, which is available to authorized users.

Scaling up genome annotation using MAKER and work queue.

Next generation sequencing technologies have enabled sequencing many genomes. Because of the overall increasing demand and the inherent parallelism available in many required analyses, these bioinformatics applications should ideally run on clusters, clouds and/or grids. We present a modified annotation framework that achieves a speed-up of 45x using 50 workers using a Caenorhabditis japonica test case. We also evaluate these modifications within the Amazon EC2 cloud framework. The underlying genome annotation (MAKER) is parallelised as an MPI application. Our framework enables it to now run without MPI while utilising a wide variety of distributed computing resources. This parallel framework also allows easy explicit data transfer, which helps overcome a major limitation of bioinformatics tools that often rely on shared file systems. Combined, our proposed framework can be used, even during early stages of development, to easily run sequence analysis tools on clusters, grids and clouds.

MtDNA Variation and Analysis Using Mitomap and Mitomaster.

The Mitomap database of human mitochondrial DNA (mtDNA) information has been an important compilation of mtDNA variation for researchers, clinicians and genetic counselors for the past twenty-five years. The Mitomap protocol shows how users may look up human mitochondrial gene loci, search for public mitochondrial sequences, and browse or search for reported general population nucleotide variants as well as those reported in clinical disease. Within Mitomap is the powerful sequence analysis tool for human mitochondrial DNA, Mitomaster. The Mitomaster protocol gives step-by-step instructions showing how to submit sequences to identify nucleotide variants relative to the rCRS, to determine the haplogroup, and to view species conservation. User-supplied sequences, GenBank identifiers and single nucleotide variants may be analyzed.

CAMP: Collection of sequences and structures of antimicrobial peptides

Antimicrobial peptides (AMPs) are gaining importance as anti-infective agents. Here we describe the updated Collection of Antimicrobial Peptide (CAMP) database, available online at http://www.camp.bicnirrh.res.in/. The 3D structures of peptides are known to influence antimicrobial activity. Although there exists databases of AMPs, information on structures of AMPs is limited in these databases. CAMP is manually curated and currently holds 6756 sequences and 682 3D structures of AMPs. Sequence and structure analysis tools have been incorporated to enhance the usefulness of the database.

161-P: NEXT GENERATION HLA TYPING SOFTWARE AS TORRENT SERVER PLUG-IN ON ION PGM

Ion Torrent Next Generation Sequencing (NGS) technology using the Personal Genomic Sequencer (PGM) provides a new platform for HLA sequence based typing. The recent assay development opens the door for unambiguous genotype with unprecedented coverage and accuracy. Interpretation from the massive data generated by PGM becomes a challenge, in addition to the issues of transferring data across networks or computers. Our approach is to leverage the existing PGM framework and infrastructure to develop HLA software tools. The PGM uses the Torrent Suite software through web browser to configure, execute and review a sample run. Other software packages can be added to the Torrent Suite through plug-ins. A plug-in is fully integrated into the Torrent Suite and can be automatically executed after a run. In addition, the plug-in can directly access raw PGM data, eliminating any data transfer from the PGM. We have developed a plug-in to read and process barcode files for a run directly on the PGM computer. It uses proprietary algorithms to map NGS reads to the HLA allele alignment library to construct consensus sequences and determine genotypes from the consensus sequences. The genotype for each barcode is reported in a tabulated form as part of the Torrent Suite run report. So far, whole gene sequences of HLA-A,B,C,DRB1, and DQB1 from 30 samples have been used to verify the typing algorithm. We are able to achieve typing concordance in the majority with average read depth in hundreds and complete coverage across target region. The challenges in HLA allele calling are mainly due to unknown HLA library sequences and insertion-deletion sequences. While the algorithm will continue to evolve by validating against deep sequencing analysis tools using a panel of well characterized HLA samples, Life Technologies HLA typing plug-in can be seamlessly integrated into the assay workflow and provides users the simplest way to produce HLA genotypes from the PGM. Shi:Life Technologies: Employee. Dinauer: Life Technologies: Employee. Radick: Life Technologies: Employee. Hunsicker: Life Technologies: Employee. Veldre: Life Technologies: Employee. Lelivelt: Life Technologies: Employee. Conradson: Life Technologies: Employee.

Application of Genotyping-by-Sequencing on Semiconductor Sequencing Platforms: A Comparison of Genetic and Reference-Based Marker Ordering in Barley

The rapid development of next-generation sequencing platforms has enabled the use of sequencing for routine genotyping across a range of genetics studies and breeding applications. Genotyping-by-sequencing (GBS), a low-cost, reduced representation sequencing method, is becoming a common approach for whole-genome marker profiling in many species. With quickly developing sequencing technologies, adapting current GBS methodologies to new platforms will leverage these advancements for future studies. To test new semiconductor sequencing platforms for GBS, we genotyped a barley recombinant inbred line (RIL) population. Based on a previous GBS approach, we designed bar code and adapter sets for the Ion Torrent platforms. Four sets of 24-plex libraries were constructed consisting of 94 RILs and the two parents and sequenced on two Ion platforms. In parallel, a 96-plex library of the same RILs was sequenced on the Illumina HiSeq 2000. We applied two different computational pipelines to analyze sequencing data; the reference-independent TASSEL pipeline and a reference-based pipeline using SAMtools. Sequence contigs positioned on the integrated physical and genetic map were used for read mapping and variant calling. We found high agreement in genotype calls between the different platforms and high concordance between genetic and reference-based marker order. There was, however, paucity in the number of SNP that were jointly discovered by the different pipelines indicating a strong effect of alignment and filtering parameters on SNP discovery. We show the utility of the current barley genome assembly as a framework for developing very low-cost genetic maps, facilitating high resolution genetic mapping and negating the need for developing de novo genetic maps for future studies in barley. Through demonstration of GBS on semiconductor sequencing platforms, we conclude that the GBS approach is amenable to a range of platforms and can easily be modified as new sequencing technologies, analysis tools and genomic resources develop.

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of “effector” proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen’s predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology.This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols.The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu).

Modern Computational Techniques for the HMMER Sequence Analysis.

This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications—hidden Markov models (HMM). We show the detailed performance comparison of sequence analysis tools on various computing platforms recently developed in the bioinformatics society. The characteristics of the sequence analysis, such as data and compute-intensive natures, make it very attractive to optimize and parallelize by using both traditional software approach and innovated hardware acceleration technologies.

GSA: An Integrated Analysis System for Gene Sequence

According to the analysis for gene sequence, various data analysis as well as a variety of software and tools needs to be integrated, also the friendly graphical interface is a must. Based on this, we propose to build a software tool named GSA (gene sequence analysis tool) which is Java-based J2EE environment based on workflow. This tool provides a unified data, algorithm interface and visualization graphical interface, not only integrates a variety of sequence analysis algorithms, but also to achieve the integration of heterogeneous data. The workflow mechanism of GSA provides a collaborative research solution for the field of sequence analysis.

Identification of novel protein domains required for the expression of an active dehydratase fragment from a polyunsaturated fatty acid synthase

Polyunsaturated fatty acids (PUFAs) are made in some strains of deep-sea bacteria by multidomain proteins that catalyze condensation, ketoreduction, dehydration, and enoyl-reduction. In this work, we have used the Udwary-Merski Algorithm sequence analysis tool to define the boundaries that enclose the dehydratase (DH) domains in a PUFA multienzyme. Sequence analysis revealed the presence of four areas of high structure in a region that was previously thought to contain only two DH domains as defined by FabA-homology. The expression of the protein fragment containing all four protein domains resulted in an active enzyme, while shorter protein fragments were not soluble. The tetradomain fragment was capable of catalyzing the conversion of crotonyl-CoA to β-hydroxybutyryl-CoA efficiently, as shown by UV absorbance change as well as by chromatographic retention of reaction products. Sequence alignments showed that the two novel domains contain as much sequence conservation as the FabA-homology domains, suggesting that they too may play a functional role in the overall reaction. Structure predictions revealed that all domains belong to the hotdog protein family: two of them contain the active site His70 residue present in FabA-like DHs, while the remaining two do not. Replacing the active site His residues in both FabA domains for Ala abolished the activity of the tetradomain fragment, indicating that the DH activity is contained within the FabA-homology regions. Taken together, these results provide a first glimpse into a rare arrangement of DH domains which constitute a defining feature of the PUFA synthases.

IMSA: Integrated Metagenomic Sequence Analysis for Identification of Exogenous Reads in a Host Genomic Background

Metagenomics, the study of microbial genomes within diverse environments, is a rapidly developing field. The identification of microbial sequences within a host organism enables the study of human intestinal, respiratory, and skin microbiota, and has allowed the identification of novel viruses in diseases such as Merkel cell carcinoma. There are few publicly available tools for metagenomic high throughput sequence analysis. We present Integrated Metagenomic Sequence Analysis (IMSA), a flexible, fast, and robust computational analysis pipeline that is available for public use. IMSA takes input sequence from high throughput datasets and uses a user-defined host database to filter out host sequence. IMSA then aligns the filtered reads to a user-defined universal database to characterize exogenous reads within the host background. IMSA assigns a score to each node of the taxonomy based on read frequency, and can output this as a taxonomy report suitable for cluster analysis or as a taxonomy map (TaxMap). IMSA also outputs the specific sequence reads assigned to a taxon of interest for downstream analysis. We demonstrate the use of IMSA to detect pathogens and normal flora within sequence data from a primary human cervical cancer carrying HPV16, a primary human cutaneous squamous cell carcinoma carrying HPV 16, the CaSki cell line carrying HPV16, and the HeLa cell line carrying HPV18.

MtDNAprofiler: A Web Application for the Nomenclature and Comparison of Human Mitochondrial DNA Sequences,

Mitochondrial DNA (mtDNA) is a valuable tool in the fields of forensic, population, and medical genetics. However, recording and comparing mtDNA control region or entire genome sequences would be difficult if researchers are not familiar with mtDNA nomenclature conventions. Therefore, mtDNAprofiler, a Web application, was designed for the analysis and comparison of mtDNA sequences in a string format or as a list of mtDNA single-nucleotide polymorphisms (mtSNPs). mtDNAprofiler which comprises four mtDNA sequence-analysis tools (mtDNA nomenclature, mtDNA assembly, mtSNP conversion, and mtSNP concordance-check) supports not only the accurate analysis of mtDNA sequences via an automated nomenclature function, but also consistent management of mtSNP data via direct comparison and validity-check functions. Since mtDNAprofiler consists of four tools that are associated with key steps of mtDNA sequence analysis, mtDNAprofiler will be helpful for researchers working with mtDNA. mtDNAprofiler is freely available at http://mtprofiler.yonsei.ac.kr.

IgBLAST: an immunoglobulin variable domain sequence analysis tool

The variable domain of an immunoglobulin (IG) sequence is encoded by multiple genes, including the variable (V) gene, the diversity (D) gene and the joining (J) gene. Analysis of IG sequences typically requires identification of each gene, as well as a comparison of sequence variations in the context of defined regions. General purpose tools, such as the BLAST program, have only limited use for such tasks, as the rearranged nature of an IG sequence and the variable length of each gene requires multiple rounds of BLAST searches for a single IG sequence. Additionally, manual assembly of different genes is difficult and error-prone. To address these issues and to facilitate other common tasks in analysing IG sequences, we have developed the sequence analysis tool IgBLAST (http://www.ncbi.nlm.nih.gov/igblast/). With this tool, users can view the matches to the germline V, D and J genes, details at rearrangement junctions, the delineation of IG V domain framework regions and complementarity determining regions. IgBLAST has the capability to analyse nucleotide and protein sequences and can process sequences in batches. Furthermore, IgBLAST allows searches against the germline gene databases and other sequence databases simultaneously to minimize the chance of missing possibly the best matching germline V gene.

How many signal peptides are there in bacteria?

Over the last 5 years proteogenomics (using mass spectroscopy to identify proteins predicted from genomic sequences) has emerged as a promising approach to the high-throughput identification of protein N-termini, which remains a problem in genome annotation. Comparison of the experimentally determined N-termini with those predicted by sequence analysis tools allows identification of the signal peptides and therefore conclusions on the cytoplasmic or extracytoplasmic (periplasmic or extracellular) localization of the respective proteins. We present here the results of a proteogenomic study of the signal peptides in Escherichia coli K-12 and compare its results with the available experimental data and predictions by such software tools as SignalP and Phobius. A single proteogenomics experiment recovered more than a third of all signal peptides that had been experimentally determined during the past three decades and confirmed at least 31 additional signal peptides, mostly in the known exported proteins, which had been previously predicted but not validated. The filtering of putative signal peptides for the peptide length and the presence of an eight-residue hydrophobic patch and a typical signal peptidase cleavage site proved sufficient to eliminate the false-positive hits. Surprisingly, the results of this proteogenomics study, as well as a re-analysis of the E. coli genome with the latest version of SignalP program, show that the fraction of proteins containing signal peptides is only about 10%, or half of previous estimates.

Reconfigurable Accelerator for the Word-Matching Stage of BLASTN

BLAST is one of the most popular sequence analysis tools used by molecular biologists. It is designed to efficiently find similar regions between two sequences that have biological significance. However, because the size of genomic databases is growing rapidly, the computation time of BLAST, when performing a complete genomic database search, is continuously increasing. Thus, there is a clear need to accelerate this process. In this paper, we present a new approach for genomic sequence database scanning utilizing reconfigurable field programmable gate array (FPGA)-based hardware. In order to derive an efficient structure for BLASTN, we propose a reconfigurable architecture to accelerate the computation of the word-matching stage. The experimental results show that the FPGA implementation achieves a speedup around one order of magnitude compared to the NCBI BLASTN software running on a general purpose computer.

CloVR-ITS: Automated internal transcribed spacer amplicon sequence analysis pipeline for the characterization of fungal microbiota

BackgroundBesides the development of comprehensive tools for high-throughput 16S ribosomal RNA amplicon sequence analysis, there exists a growing need for protocols emphasizing alternative phylogenetic markers such as those representing eukaryotic organisms.ResultsHere we introduce CloVR-ITS, an automated pipeline for comparative analysis of internal transcribed spacer (ITS) pyrosequences amplified from metagenomic DNA isolates and representing fungal species. This pipeline performs a variety of steps similar to those commonly used for 16S rRNA amplicon sequence analysis, including preprocessing for quality, chimera detection, clustering of sequences into operational taxonomic units (OTUs), taxonomic assignment (at class, order, family, genus, and species levels) and statistical analysis of sample groups of interest based on user-provided information. Using ITS amplicon pyrosequencing data from a previous human gastric fluid study, we demonstrate the utility of CloVR-ITS for fungal microbiota analysis and provide runtime and cost examples, including analysis of extremely large datasets on the cloud. We show that the largest fractions of reads from the stomach fluid samples were assigned to Dothideomycetes, Saccharomycetes, Agaricomycetes and Sordariomycetes but that all samples were dominated by sequences that could not be taxonomically classified. Representatives of the Candida genus were identified in all samples, most notably C. quercitrusa, while sequence reads assigned to the Aspergillus genus were only identified in a subset of samples. CloVR-ITS is made available as a pre-installed, automated, and portable software pipeline for cloud-friendly execution as part of the CloVR virtual machine package (http://clovr.org).ConclusionThe CloVR-ITS pipeline provides fungal microbiota analysis that can be complementary to bacterial 16S rRNA and total metagenome sequence analysis allowing for more comprehensive studies of environmental and host-associated microbial communities.

A survey of enabling technologies in synthetic biology.

BackgroundRealizing constructive applications of synthetic biology requires continued development of enabling technologies as well as policies and practices to ensure these technologies remain accessible for research. Broadly defined, enabling technologies for synthetic biology include any reagent or method that, alone or in combination with associated technologies, provides the means to generate any new research tool or application. Because applications of synthetic biology likely will embody multiple patented inventions, it will be important to create structures for managing intellectual property rights that best promote continued innovation. Monitoring the enabling technologies of synthetic biology will facilitate the systematic investigation of property rights coupled to these technologies and help shape policies and practices that impact the use, regulation, patenting, and licensing of these technologies.ResultsWe conducted a survey among a self-identifying community of practitioners engaged in synthetic biology research to obtain their opinions and experiences with technologies that support the engineering of biological systems. Technologies widely used and considered enabling by survey participants included public and private registries of biological parts, standard methods for physical assembly of DNA constructs, genomic databases, software tools for search, alignment, analysis, and editing of DNA sequences, and commercial services for DNA synthesis and sequencing. Standards and methods supporting measurement, functional composition, and data exchange were less widely used though still considered enabling by a subset of survey participants.ConclusionsThe set of enabling technologies compiled from this survey provide insight into the many and varied technologies that support innovation in synthetic biology. Many of these technologies are widely accessible for use, either by virtue of being in the public domain or through legal tools such as non-exclusive licensing. Access to some patent protected technologies is less clear and use of these technologies may be subject to restrictions imposed by material transfer agreements or other contract terms. We expect the technologies considered enabling for synthetic biology to change as the field advances. By monitoring the enabling technologies of synthetic biology and addressing the policies and practices that impact their development and use, our hope is that the field will be better able to realize its full potential.

Personalized cloud-based bioinformatics services for research and education: use cases and the elasticHPC package

BackgroundBioinformatics services have been traditionally provided in the form of a web-server that is hosted at institutional infrastructure and serves multiple users. This model, however, is not flexible enough to cope with the increasing number of users, increasing data size, and new requirements in terms of speed and availability of service. The advent of cloud computing suggests a new service model that provides an efficient solution to these problems, based on the concepts of "resources-on-demand" and "pay-as-you-go". However, cloud computing has not yet been introduced within bioinformatics servers due to the lack of usage scenarios and software layers that address the requirements of the bioinformatics domain.ResultsIn this paper, we provide different use case scenarios for providing cloud computing based services, considering both the technical and financial aspects of the cloud computing service model. These scenarios are for individual users seeking computational power as well as bioinformatics service providers aiming at provision of personalized bioinformatics services to their users. We also present elasticHPC, a software package and a library that facilitates the use of high performance cloud computing resources in general and the implementation of the suggested bioinformatics scenarios in particular. Concrete examples that demonstrate the suggested use case scenarios with whole bioinformatics servers and major sequence analysis tools like BLAST are presented. Experimental results with large datasets are also included to show the advantages of the cloud model.ConclusionsOur use case scenarios and the elasticHPC package are steps towards the provision of cloud based bioinformatics services, which would help in overcoming the data challenge of recent biological research. All resources related to elasticHPC and its web-interface are available at http://www.elasticHPC.org.

HBVdb: a knowledge database for Hepatitis B Virus

We have developed a specialized database, HBVdb (http://hbvdb.ibcp.fr), allowing the researchers to investigate the genetic variability of Hepatitis B Virus (HBV) and viral resistance to treatment. HBV is a major health problem worldwide with more than 350 million individuals being chronically infected. HBV is an enveloped DNA virus that replicates by reverse transcription of an RNA intermediate. HBV genome is optimized, being circular and encoding four overlapping reading frames. Indeed, each nucleotide of the genome takes part in the coding of at least one protein. However, HBV shows some genome variability leading to at least eight different genotypes and recombinant forms. The main drugs used to treat infected patients are nucleos(t)ides analogs (reverse transcriptase inhibitors). Unfortunately, HBV mutants resistant to these drugs may be selected and be responsible for treatment failure. HBVdb contains a collection of computer-annotated sequences based on manually annotated reference genomes. The database can be accessed through a web interface that allows static and dynamic queries and offers integrated generic sequence analysis tools and specialized analysis tools (e.g. annotation, genotyping, drug resistance profiling).

Analysis of Mutations in theSGene of Hepatitis B Virus Strains in Patients with Chronic Infection by Online Bioinformatics Tools

Hepatitis B virus (HBV) genomes show a high rate of mutations. This can lead to a variety of amino acid changes in the surface and polymerase genes, causing changes in viral protein conformation that can result in diminished antibody binding or decreased secretion of surface antigen (HBsAg). HBV monitoring increasingly relies on HBsAg detection and quantification, and therefore epidemiological data on HBsAg mutations are needed. We therefore analyzed the frequency of HBsAg mutations possibly influencing the quantification of HBsAg (MUPIQHs) in an unselected patient collective. To this end, we determined the HBV surface and polymerase gene sequences of an unselected patient collective of 237 individuals chronically infected with HBV and analyzed the MUPIQHs in these sequences using three different online HBV sequence analysis tools. We found that 17 or 34% of the patients, depending on the online interpretation algorithm used, harbored MUPIQHs and that MUPIQHs were not significantly associated with the duration of disease, treatment, or HBV genotype. Thus, this study shows that a substantial amount of HBV sequences derived from unselected patients chronically infected with HBV carry MUPIQHs, and therefore the reliability of routine quantitative and qualitative HBsAg tests needs to be reevaluated.