114 research outputs found

    inPHAP: Interactive visualization of genotype and phased haplotype data

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    Background: To understand individual genomes it is necessary to look at the variations that lead to changes in phenotype and possibly to disease. However, genotype information alone is often not sufficient and additional knowledge regarding the phase of the variation is needed to make correct interpretations. Interactive visualizations, that allow the user to explore the data in various ways, can be of great assistance in the process of making well informed decisions. But, currently there is a lack for visualizations that are able to deal with phased haplotype data. Results: We present inPHAP, an interactive visualization tool for genotype and phased haplotype data. inPHAP features a variety of interaction possibilities such as zooming, sorting, filtering and aggregation of rows in order to explore patterns hidden in large genetic data sets. As a proof of concept, we apply inPHAP to the phased haplotype data set of Phase 1 of the 1000 Genomes Project. Thereby, inPHAP's ability to show genetic variations on the population as well as on the individuals level is demonstrated for several disease related loci. Conclusions: As of today, inPHAP is the only visual analytical tool that allows the user to explore unphased and phased haplotype data interactively. Due to its highly scalable design, inPHAP can be applied to large datasets with up to 100 GB of data, enabling users to visualize even large scale input data. inPHAP closes the gap between common visualization tools for unphased genotype data and introduces several new features, such as the visualization of phased data.Comment: BioVis 2014 conferenc

    Computational methods for ancient genome reconstruction

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    Applications of next-generation sequencing (NGS) technologies have become the de facto standard in the systematic analysis of the genetic composition of organisms. Aforementioned is not just valid for modern DNA analysis, but also for ancient DNA (aDNA) where NGS methods have almost entirely replaced PCR-based approaches. Studying DNA variation in ancient humans provides promising opportunities to unravel missing links in human history that are otherwise hard to detect. Today, the methods that paleogenetics can provide to study ancient populations can change the understanding of human history to a large extent. While this is encouraging, there are still several issues in analyzing NGS data from ancient specimens, posing challenges to bioinformatics. As aDNA research projects typically produce low levels of DNA extract, bioinformatic methods have to cope with low DNA content. Furthermore, the inherent challenges of aDNA, such as DNA misincorporation patterns as well as human DNA contamination not only from modern sources, pose further challenges for the successful analysis of aDNA. Therefore, the primary research focus of bioinformatics in aDNA analysis lies on the reconstruction of ancient genomes and the subsequent data analysis of reconstructed genomes. Pipeline scripts that were used before, were limited in their applicability to few research questions and therefore required the adaption of the respective tools even for slightly different research scopes. The main topic of this dissertation concentrates on the development of EAGER, a framework for the analysis of aDNA data with a variety of use cases and improvements in contrast to previously published methods. EAGER features several newly contributed analysis methods, aiming at recovering as much aDNA as possible from sequencing experiments. Additionally, the pipeline provides an integrated solution to analyze aDNA data in an advanced way, running several state of the art analysis methods to reconstruct ancient genomes. The applicability of EAGER has been demonstrated in various aDNA analysis projects and is further illustrated within this thesis, having been applied to the reconstruction of the genome of George Bähr, the architect of Dresden Frauenkirche, and a total of 90 ancient Egyptian individuals from Abusir El-Meleq in Northern Egypt. Apart from the general processing as handled in EAGER, the handling of genomic data and metadata is of crucial importance in today's research. While sequencing projects prospered in the last couple of years, thereby producing more and more data, efficient bioinformatic tools to aid users in organizing, storing and analyzing their respective data have had difficulties in keeping up with the increasing amount of data produced. Therefore, the current situation in population genetics suffers struggles with a lack of bioinformatics methods capable of accommodating researchers with functionality to organize and analyze their data in larger sample cohorts. The second part of this thesis therefore concentrates on the conceptual introduction of MitoBench and MitoDB. The idea of MitoBench centers around the concept of an advanced analysis application that can be used by researchers to integrate their mitochondrial population genetics data with metadata from a variety of resources. In addition, the idea of MitoDB provides a centrally accessible database of mitochondrial DNA with metadata to serve as a data resource for future analysis projects within a mitochondrial population genetics context. As sequencing costs are in steady decline and thus sample sizes for research projects are growing at equal speed, novel methods and frameworks for the analysis of aDNA are required. Overall, both the EAGER framework explained in this dissertation and the conceptual ideas of MitoBench and MitoDB have contributed in understanding human history better. They will hopefully continue to aid researchers in elucidating the changes past populations have experienced

    Ten simple rules for providing effective bioinformatics research support.

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    Life scientists are increasingly turning to high-throughput sequencing technologies in their research programs, owing to the enormous potential of these methods. In a parallel manner, the number of core facilities that provide bioinformatics support are also increasing. Notably, the generation of complex large datasets has necessitated the development of bioinformatics support core facilities that aid laboratory scientists with cost-effective and efficient data management, analysis, and interpretation. In this article, we address the challenges-related to communication, good laboratory practice, and data handling-that may be encountered in core support facilities when providing bioinformatics support, drawing on our own experiences working as support bioinformaticians on multidisciplinary research projects. Most importantly, the article proposes a list of guidelines that outline how these challenges can be preemptively avoided and effectively managed to increase the value of outputs to the end user, covering the entire research project lifecycle, including experimental design, data analysis, and management (i.e., sharing and storage). In addition, we highlight the importance of clear and transparent communication, comprehensive preparation, appropriate handling of samples and data using monitoring systems, and the employment of appropriate tools and standard operating procedures to provide effective bioinformatics support

    Adherence to Tuberculosis Therapy among Patients Receiving Home-Based Directly Observed Treatment: Evidence from the United Republic of Tanzania.

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    \ud \ud Non-adherence to tuberculosis (TB) treatment is the leading contributor to the selection of drug-resistant strains of Mycobacterium tuberculosis and subsequent treatment failure. Tanzania introduced a TB Patient Centred Treatment (PCT) approach which gives new TB patients the choice between home-based treatment supervised by a treatment supporter of their own choice, and health facility-based treatment observed by a medical professional. The aim of this study was to assess the extent and determinants of adherence to anti-TB therapy in patients opting for home-based treatment under the novel PCT approach. In this cross-sectional study, the primary outcome was the percentage of patients adherent to TB therapy as detected by the presence of isoniazid in urine (IsoScreen assay). The primary analysis followed a non-inferiority approach in which adherence could not be lower than 75%. Logistic regression was used to examine the influence of potentially predictive factors. A total of 651 new TB patients were included. Of these, 645 (99.1%) provided urine for testing and 617 patients (95.7%; 90%CI 94.3-96.9) showed a positive result. This result was statistically non-inferior to the postulated adherence level of 75% (p<0.001). Adherence to TB therapy under home-based Directly Observed Treatment can be ensured in programmatic settings. A reliable supply of medication and the careful selection of treatment supporters, who preferably live very close to the patient, are crucial success factors. Finally, we recommend a cohort study to assess the rate of adherence throughout the full course of TB treatment

    Genomic analyses of hair from Ludwig van Beethoven

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    Ludwig van Beethoven (1770–1827) remains among the most influential and popular classical music composers. Health problems significantly impacted his career as a composer and pianist, including progressive hearing loss, recurring gastrointestinal complaints, and liver disease. In 1802, Beethoven requested that following his death, his disease be described and made public. Medical biographers have since proposed numerous hypotheses, including many substantially heritable conditions. Here we attempt a genomic analysis of Beethoven in order to elucidate potential underlying genetic and infectious causes of his illnesses. We incorporated improvements in ancient DNA methods into existing protocols for ancient hair samples, enabling the sequencing of high-coverage genomes from small quantities of historical hair. We analyzed eight independently sourced locks of hair attributed to Beethoven, five of which originated from a single European male. We deemed these matching samples to be almost certainly authentic and sequenced Beethoven\u27s genome to 24-fold genomic coverage. Although we could not identify a genetic explanation for Beethoven\u27s hearing disorder or gastrointestinal problems, we found that Beethoven had a genetic predisposition for liver disease. Metagenomic analyses revealed furthermore that Beethoven had a hepatitis B infection during at least the months prior to his death. Together with the genetic predisposition and his broadly accepted alcohol consumption, these present plausible explanations for Beethoven\u27s severe liver disease, which culminated in his death. Unexpectedly, an analysis of Y chromosomes sequenced from five living members of the Van Beethoven patrilineage revealed the occurrence of an extra-pair paternity event in Ludwig van Beethoven\u27s patrilineal ancestry

    heiMAP – Virtual Research Environment for collaborative spatio-temporal research in the Humanities

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    heiMAP is a Virtual Research Environment (VRE) for research in the Humanities that facilitates collaborative work in spatio-temporal contexts. The differentiating characteristic of heiMAP is its holistic approach, representing the entire scientific data lifecycle. This includes the generation of, as well as discourse about, spatio-temporal data, their publication, archiving and sustainable reuse. The VRE consists of an Open Source Content Management System (CMS) that handles data and research projects, and an integrated Web Geographic Information Systems (GIS) application used to contextualize vector and raster data, especially maps. By sticking to international standards (OGC, CIDOC CRM among others), we strive for a maximum of data interoperability and reusability of the data produced within heiMAP. Close cooperation with the Heidelberg University Library and Heidelberg Computing Center allows for the publication, referenced by a Digital Object Identifier (DOI), as well as the long-term archiving of individual research projects and their related outcomes. One major challenge in building an environment for collaborative research is to ensure that users retain control over their data where necessary but are also enabled to share it with others when they wish to. Therefore, heiMAP possesses a sophisticated system for user and rights management as well as fine-grained control of user rights based on the CMS. To allow a broad range of users from different parts of the Humanities (including both University and Citizen Science projects) with varying degrees of expertise in spatial research and GIS, to effectively use heiMAP, the platform focuses on a number of core functions while allowing export of research data into more sophisticated desktop-based GIS programs when necessary

    Crop Updates 2002 - Weeds

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    This session covers fifty eight papers from different authors: 1. INTRODUCTION Vanessa Stewart, DEPARTMENT OF AGRICULTURE INTEGRATED WEED MANAGEMENT IWM system studies / demonstration sites 2. Major outcomes from IWM demonstration sites, Alexandra Douglas Department of Agriculture 3. Integrated weed management: Katanning, Alexandra Douglas Department of Agriculture 4. Integrated weed management: Merredin, Vanessa Stewart Department of Agriculture 5. Long term resistance site: Get ryegrass numbers low and keep them low! Peter Newman and Glen Adams Department of Agriculture 6. Using pastures to manage ryegrass populations, Andrew Blake and Natalie Lauritsen Department of Agriculture Weed biology and competition 7. Understanding the weed seed bank life if important agricultural weeds, Sally Peltzer and Paul Matson Department of Agriculture 8. Consequence of radish competition on lupin nutrients in wheat-lupin rotation, Abul Hashem and Nerys Wilkins Department of Agriculture 9. Consequence of ryegrass competition on lupin nutrients in a wheat-lupin rotation, Abul Hashem and Nerys Wilkins Department of Agriculture 10. Brome grass too competitive for early sown wheat in a dry year at Mullewa, Peter Newman and Glenn Adam Department of Agriculture Crop establishment and weed management 11. Seeding rate, row spacing and herbicides for weed control, David Minkey Department of Agriculture 12. Effect of different seeding methods on wheat and ryegrass, Abul Hashem, Glen Riethmuller and Nerys Wilkins Department of Agriculture 13. Role of tillage implements and trifluralin on the effectiveness of the autumn tickle for stimulating annual ryegrass emergence, Tim Cusack1, Kathryn Steadman1 and Abul Hashem2,1Western Australia Herbicide Resistance Initiative, UWA; 2Department of Agriculture, 14. Timing of autumn tickle in important for non-wetting soils, Pippa Michael1, Peter Newman2 and Kathryn Steadman 2, 1Western Australia Herbicide Resistance Initiative, UWA, 2Department of Agriculture 15. Early investigation into weed seed burial by mouldboard plough, Sally Peltzer and Alex Douglas Department of Agriculture 16. Rolling post-emergent lupins to improve weed emergence and control on loamy sand, Paul Blackwell, Department of Agriculture and Dave Brindal, Strawberry via Mingenew IWM tools 17. Crop topping in 2001: How did we do? Peter Newman and Glenn Adam Department of Agriculture 18. Wickwipers work! Peter Newman and Glenn Adam Department of Agriculture 19. Wild radish and ryegrass seed collection at harvest: Chaff carts and other devices, Michael Walsh Western Australia Herbicide Resistance Initiative, UWA and Wayne Parker Department of Agriculture 20. Improving weed control in grazed pastures using legumes with low palatability, Clinton Revell, Giles Glasson Department of Agriculture, and Dean Thomas Faculty of Agriculture, University of Western Australia Adoption and modelling 21. Grower weed survey, Peter Newman and Glenn Adam Department of Agriculture 22. Agronomist survey, Peter Newman and Glenn Adam Department of Agriculture 23. Ryegrass RIM model stands the test of IWM field trial data, Alister Draper Western Australia Herbicide Resistance Initiative, UWA and Bill Roy, Western Australia Herbicide Resistance Initiative, UWA Agricultural Consulting and Research Services 24. Multi-species RIM: An update, Marta Monjardin1,2, David Pannell2 and Stephen Powles 1, 1Western Australia Herbicide Resistance Initiative, UWA, 2 ARE, University of Western Australia 25. RIM survey feedback, Robert Barrett-Lennard and Alister Draper Western Australia Herbicide Resistance Initiative, UWA 26. Effect of historic input and product prices on choice of ryegrass management strategies, Alister Draper1 and Martin Bent2, 1Western Australia Herbicide Resistance Initiative, UWA, 2Muresk Institute of Agriculture 27. Living with ryegrass – trading off weed control and economic performance, Martin Bent1 and Alister Draper2 , 1Muresk Institute of Agriculture, Curtin University, 2Western Australia Herbicide Resistance Initiative, UWA HERBICIDE RESISTANCE 28. Glyphosate resistance in WA and Australia: Where are we at? Paul Neve1, Art Diggle2, Patrick Smith3, Mechelle Owen1, Abul Hashem2, Christopher Preston4and Stephen Powles1,1Western Australian Herbicide Resistance Initiative, University of Western Australia, 2Department of Agriculture, 3CSIRO Sustainable Ecosystems, 4CRC for Australian Weed Management and Department of Applied and Molecular Ecology, Waite Campus, University of Adelaide 29. We need you weeds: A survey of knockdown resistance in the WA wheatbelt, Paul Neve1, Mechelle Owen1, Abul Hashem2 and Stephen Powles1 1Western Australian Herbicide Resistance Initiative, University of Western Australia, 2Department of Agriculture 30. A test for resistance testing, Mechelle Owen, Tracey Gillam, Rick Llewellyn and Steve Powles,Western Australia Herbicide Resistance Initiative, University of Western Australia 31. In field testing for herbicide resistance, a purpose built multi-treatment spray boom with results from 2001, Richard Quinlan, Elders Ltd 32. Advantages and limitations of a purpose built multi-treatment spray boom, Richard Quinlan, Elders Ltd 33. Group F resistant wild radish: What’s new? Aik Cheam, Siew Lee Department of Agriculture, and Mike Clarke Aventis Crop Science 34. Cross resistance of Brodal® resistant wild radish to Sniper®, Aik Cheam and Siew Lee, Department of Agriculture 35. Managing a biotype of wild radish with Group F and Group C resistance, Aik Cheam, Siew Lee, David Nicholson, Peter Newman Department of Agriculture and Mike Clarke, Aventis Crop Science HERBICIDE TOLERANCE 36. Herbicide tolerance of new wheat varieties, Harmohinder S. Dhammu, Terry Piper and David Nicholson, Agriculture Western Australia 37. Response of barley varieties to herbicides, Harmohinder S. Dhammu, Terry Piper, Department of Agriculture 38. Tolerance of barley to phenoxy herbicides, Harmohinder S. Dhammu, Terry Piper, Department of Agriculture and Chad Sayer, Nufarm Australia Limited 39. Response of Durum wheats to herbicides, Harmohinder S. Dhammu, Terry Piper, Department of Agriculture 40. Response of new field pea varieties to herbicides, Harmohinder S. Dhammu, Terry Piper and David Nicholson, Department of Agriculture 41. Herbicide tolerance of Desi chickpeas on marginal soil, Harmohinder S. Dhammu, Terry Piper and David Nicholson, Department of Agriculture 42. Herbicide tolerance of newer lupin varieties, Terry Piper, Harmohinder Dhammu and David Nicholson, Department of Agriculture 43. Herbicide tolerance of some annual pasture legumes, Clinton Revell and Ian Rose, Department of Agriculture 44. Herbicide tolerance of pasture legumes, Andrew Blake, Department of Agriculture HERBICIDES – NEW PRODUCTS/PRODUCT USES; USE 45. Knockdown herbicides do not reliably kill small grass weeds, Peter Newman and Glenn Adam, Department of Agriculture 46. ‘Hair Cutting’ wheat with Spray.Seed®: Does it work? Peter Newman and Glenn Adam, Department of Agriculture 47. ‘Haircutting’: Does the number one cut work? Robert Barrett-Lennard1 and Jerome Critch2,1WA Herbicide Resistance Initiative, University of WA, 2Student, University of WA 48. Hammer EC (Carfentrazone-ethyl): A mixing partner for glyphosate to enhance the control of difficult broadleaf weeds, Gordon R. Cumming, Crop Care Australasia 49. Marshmallow control in reduced tillage systems, Sam Taylor, Wesfarmers Landmark 50. Herbicide options for summer germinating marshmallow, Vanessa Stewart, Department of Agriculture 51. Dual Gold® safe in a dry year at Coorow, Peter Newman and Glenn Adam, Department of Agriculture 52. The effect of glyphosate, paraquat and diquat as a crop topping application on the germination of barley, John Moore and Roslyn Jettner, Department of Agriculture 53. Herbicide options for melon control, Vanessa Stewart, Department of Agriculture 54. Herbicide options for the control of Chloris truncate (windmill grass) Vanessa Stewart, Department of Agriculture 55. Allelopathic effects of crop, pasture and weed residues on subsequent crop and pasture establishment, Stuart Bee1, Lionel Martin1, Keith Devenish2 and Terry Piper2, 1Muresk Institute of Agriculture, Curtin University of Technology, Northam, Western Australia, 2Centre for Cropping Systems, Department of Agriculture WEED ISSUES 56. Role of Roundup ReadyÒ canola in the farming system, Art Diggle1, Patrick Smith2, Paul Neve3, Felicity Flugge4, Amir Abadi5 and Stephen Powles3, 1Department of Agriculture; 2CSIRO, Sustainable Ecosystems; 3Western Australian Herbicide Resistance Initiative; 4Centre for Legumes in Mediterranean Agriculture; 5Touchstone Consulting 57. ’Weeds for Feed’ and livestock enterprise structures: A feasibility study and farmer survey in the north-easern wheatbelt, Duncan Peter and Stuart McAlpine, Department of Agriculture and Liebe Group, Buntine 58. e-weed, Vanessa Stewart, Agriculture Western Australi

    Ancient genomes reveal a high diversity of Mycobacterium leprae in medieval Europe.

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    Studying ancient DNA allows us to retrace the evolutionary history of human pathogens, such as Mycobacterium leprae, the main causative agent of leprosy. Leprosy is one of the oldest recorded and most stigmatizing diseases in human history. The disease was prevalent in Europe until the 16th century and is still endemic in many countries with over 200,000 new cases reported annually. Previous worldwide studies on modern and European medieval M. leprae genomes revealed that they cluster into several distinct branches of which two were present in medieval Northwestern Europe. In this study, we analyzed 10 new medieval M. leprae genomes including the so far oldest M. leprae genome from one of the earliest known cases of leprosy in the United Kingdom-a skeleton from the Great Chesterford cemetery with a calibrated age of 415-545 C.E. This dataset provides a genetic time transect of M. leprae diversity in Europe over the past 1500 years. We find M. leprae strains from four distinct branches to be present in the Early Medieval Period, and strains from three different branches were detected within a single cemetery from the High Medieval Period. Altogether these findings suggest a higher genetic diversity of M. leprae strains in medieval Europe at various time points than previously assumed. The resulting more complex picture of the past phylogeography of leprosy in Europe impacts current phylogeographical models of M. leprae dissemination. It suggests alternative models for the past spread of leprosy such as a wide spread prevalence of strains from different branches in Eurasia already in Antiquity or maybe even an origin in Western Eurasia. Furthermore, these results highlight how studying ancient M. leprae strains improves understanding the history of leprosy worldwide
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