37 research outputs found
RBioCloud : a light-weight framework for bioconductor and R-based jobs on the Cloud
No full textLarge-scale ad hoc analytics of genomic data is popular using the R-programming language supported by over 700 software packages provided by Bioconductor. More recently, analytical jobs are benefitting from on-demand computing and storage, their scalability and their low maintenance cost, all of which are offered by the cloud. While Biologists and Bioinformaticists can take an analytical job and execute it on their personal workstations, it remains challenging to seamlessly execute the job on the cloud infrastructure without extensive knowledge of the cloud dashboard. How analytical jobs can not only with minimum effort be executed on the cloud, but also how both the resources and data required by the job can be managed is explored in this paper. An open-source light-weight framework for executing R-scripts using Bioconductor packages, referred to as ‘RBioCloud’, is designed and developed. RBioCloud offers a set of simple command-line tools for managing the cloud resources, the data and the execution of the job. Three biological test cases validate the feasibility of RBioCloud. The framework is available from http://www.rbiocloud.com.Peer reviewe
Gene synteny and evolution of genome architecture in trypanosomatids
No full textFil: Ghedin, Elodie. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: Bringaud, Frederic. Université Victor Segalen de Bordeaux II. Laboratoire de Parasitologie Moléculaire; Francia.Fil: Peterson, Jeremy. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: Myler, Peter. Seattle Biomedical Research Institute; Estados Unidos.Fil: Berriman, Matthew. The Wellcome Trust Genome Campus. The Wellcome Trust Sanger Institute; Inglaterra.Fil: Ivens, Alasdair. The Wellcome Trust Genome Campus. The Wellcome Trust Sanger Institute; Inglaterra.Fil: Andersson, Björn. Karolinska Institute. Center for Genomics and Bioinformatics; Suecia.Fil: Bontempi, Esteban. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Parasitología; Argentina.Fil: Eisen, Jonathan. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: Angiuoli, Sam. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: Wanless, David. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: Von Arx, Anna. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: Murphy, Lee. The Wellcome Trust Genome Campus. The Wellcome Trust Sanger Institute; Inglaterra.Fil: Lennard, Nicola. The Wellcome Trust Genome Campus. The Wellcome Trust Sanger Institute; Inglaterra.Fil: Salzberg, Steven. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: Adams, Mark D. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: White, Owen. The Wellcome Trust Genome Campus. The Wellcome Trust Sanger Institute; Inglaterra.Fil: Hall, Neil. The Wellcome Trust Genome Campus. The Wellcome Trust Sanger Institute; Inglaterra.Fil: Stuart, Kenneth. Seattle Biomedical Research Institute; Estados Unidos.Fil: Fraser, Claire M. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.Fil: El-Sayed, Najib M A. The Institute for Genomic Research. Parasite Genomics; Estados Unidos.The trypanosomatid protozoa Trypanosoma brucei, Trypanosoma cruzi and Leishmania major are related human pathogens that cause markedly distinct diseases. Using information from genome sequencing projects currently underway, we have compared the sequences of large chromosomal fragments from each species. Despite high levels of divergence at the sequence level, these three species exhibit a striking conservation of gene order, suggesting that selection has maintained gene order among the trypanosomatids over hundreds of millions of years of evolution. The few sites of genome rearrangement between these species are marked by the presence of retrotransposon-like elements, suggesting that retrotransposons may have played an important role in shaping trypanosomatid genome organization. A degenerate retroelement was identified in L. major by examining the regions near breakage points of the synteny. This is the first such element found in L. major suggesting that retroelements were found in the common ancestor of all three species
Abstract 604: Accurate identification and prioritization of candidate neoantigens from integrated cancer exome and transcriptome sequencing of FFPE samples
No full textAbstract
Precise identification and characterization of candidate neoantigens is important for the development of effective cancer vaccines, adoptive T-cell transfer, and prediction of response to checkpoint inhibitors. The candidate tumor neoantigens are actionable only when expressed, however, current prediction methods lack the capacity to evaluate neoantigen expression. Sequencing both DNA and RNA from a patient’s tumor tissue enables identification of mutations and evaluation of their expression leading to accurate identification of putative neoantigens. The purpose of this study was to develop and validate a methodology for co-extraction and sequencing of DNA and RNA from formalin-fixed paraffin-embedded (FFPE) samples to enable a robust neoantigen prediction protocol that integrates whole exome and transcriptome data to identify and prioritize tumor neoantigens for application in immuno-oncology research and clinical trials. In order to prepare high-quality sequencing libraries from FFPE specimens, the tissue was macrodissected to enrich for tumor-specific material, and improve the overall accuracy of next-generation sequencing for detection of somatic alterations. Total DNA and RNA was co-extracted and purified. The DNA was used to prepare whole exome sequencing (WES) libraries, while the co-extracted RNA was ribosome-depleted, and reverse-transcribed to prepare RNA sequencing (RNAseq) libraries. The WES and RNAseq data was then analyzed using a multi-algorithm HLA typing and neoantigen prediction protocol (ImmunoSelect-RTM). ImmunoSelect-R evaluates somatic genomic alterations identified from WES of tumor and matched normal tissue to ensure appropriate prediction of candidate neoantigens. The process of neoantigen prediction was then refined by integration of patient tumor-matched RNAseq data, which allowed for removal of non-expressed putative neoantigens. To further validate the approach, we applied the methodology to a set of experimentally validated neoantigens. In this setting, ImmunoSelect-R correctly classified 18 out of 19 as strong neoantigen candidates, suggesting a sensitivity of greater than 90%. Moreover, in a set of 10 patients, ImmunoSelect-R consistently ranked experimentally validated neoantigens within the top 20% of all neoantigen candidates derived from whole exome sequencing. In summary, our combined tissue processing, macrodissection, co-extraction, and neoantigen prediction methodology is able to identify and prioritize candidate neoantigens. Our approach is unique in combining high-fidelity sequencing (WES) and expression (RNAseq) data to accurately inform the selection of actionable tumor neoantigens for immuno-oncology applications.
Citation Format: Marián Novak, Sam Angiuoli, Luis A. Diaz, Andrew Georgiadis, Sian Jones, Peter R. Loverso, Sonya Parpart-Li, Maria Sevdali, Victor E. Velculescu, Ellen L. Verner, James White, Theresa Zhang, Mark Sausen. Accurate identification and prioritization of candidate neoantigens from integrated cancer exome and transcriptome sequencing of FFPE samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 604. doi:10.1158/1538-7445.AM2017-604</jats:p
Draft genome of the filarial nematode parasite Brugia malayi
No full textParasitic nematodes that cause elephantiasis and river blindness threaten hundreds of millions of people in the developing world. We have sequenced the approximately 90 megabase (Mb) genome of the human filarial parasite Brugia malayi and predict approximately 11,500 protein coding genes in 71 Mb of robustly assembled sequence. Comparative analysis with the free-living, model nematode Caenorhabditis elegans revealed that, despite these genes having maintained little conservation of local synteny during approximately 350 million years of evolution, they largely remain in linkage on chromosomal units. More than 100 conserved operons were identified. Analysis of the predicted proteome provides evidence for adaptations of B. malayi to niches in its human and vector hosts and insights into the molecular basis of a mutualistic relationship with its Wolbachia endosymbiont. These findings offer a foundation for rational drug design
Abstract 528: Identify and prioritize candidate neoantigens from cancer exome sequencing with unmatched accuracy
No full textThe kinomes of apicomplexan parasites
No full textProtein phosphorylation plays a fundamental role in the biology of apicomplexan parasites. Many apicomplexan protein kinases are substantially different from their mammalian orthologues, and thus constitute a landscape of potential drug targets. Here, we integrate genomic, biochemical, genetic and evolutionary information to provide an integrated and up-to-date analysis of twelve apicomplexan kinomes. All kinome sequences are available through the Kinomer database
Abstract 1665: Development of standardized assay and software systems to deliver concordant results across sequencing platforms
No full textGemina: A Web-Based Epidemiology and Genomic Metadata System Designed to Identify Infectious Agents
No full textAbstract A039: Accurate identification and prioritization of candidate neoantigens from cancer exome sequencing
No full textGemina, genomic metadata for infectious agents, a geospatial surveillance pathogen database
No full textThe Gemina syste
