R/qtlcharts: Interactive Graphics for Quantitative Trait Locus Mapping

Every data visualization can be improved with some level of interactivity. Interactive graphics hold particular promise for the exploration of high-dimensional data. R/qtlcharts is an R package to create interactive graphics for experiments to map quantitative trait loci (QTL) (genetic loci that influence quantitative traits). R/qtlcharts serves as a companion to the R/qtl package, providing interactive versions of R/qtl’s static graphs, as well as additional interactive graphs for the exploration of high-dimensional genotype and phenotype data.     

MetaSee: An Interactive and Extendable Visualization Toolbox for Metagenomic Sample Analysis and Comparison

The NGS (next generation sequencing)-based metagenomic data analysis is becoming the mainstream for the study of microbial communities. Faced with a large amount of data in metagenomic research, effective data visualization is important for scientists to effectively explore, interpret and manipulate such rich information. The visualization of the metagenomic data, especially multi-sample data, is one of the most critical challenges. The different data sample sources, sequencing approaches and heterogeneous data formats make robust and seamless data visualization difficult. Moreover, researchers have different focuses on metagenomic studies: taxonomical or functional, sample-centric or genome-centric, single sample or multiple samples, etc. However, current efforts in metagenomic data visualization cannot fulfill all of these needs, and it is extremely hard to organize all of these visualization effects in a systematic manner. An extendable, interactive visualization tool would be the method of choice to fulfill all of these visualization needs. In this paper, we have present MetaSee, an extendable toolbox that facilitates the interactive visualization of metagenomic samples of interests. The main components of MetaSee include: (I) a core visualization engine that is composed of different views for comparison of multiple samples: Global view, Phylogenetic view, Sample view and Taxa view, as well as link-out for more in-depth analysis; (II) front-end user interface with real metagenomic models that connect to the above core visualization engine and (III) open-source portal for the development of plug-ins for MetaSee. This integrative visualization tool not only provides the visualization effects, but also enables researchers to perform in-depth analysis of the metagenomic samples of interests. Moreover, its open-source portal allows for the design of plug-ins for MetaSee, which would facilitate the development of any additional visualization effects.     

Open Data in Global Environmental Research: The Belmont Forum’s Open Data Survey

This paper presents the findings of the Belmont Forum’s survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users’ perceptions of the term “open data”, expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing.     

Unlocking the potential of Google Earth as a tool in invasion science

Distribution data are central to many invasion science applications. The shortage of good information on the distribution of alien species and their spatial dynamics is largely attributable to the cost, effort and expertise required to monitor these species over large areas. Virtual globes, particularly Google Earth, are free and user-friendly software which provide high-resolution aerial imagery for the entire globe. We suggest this has enormous potential for invasion science. We provide suggestions and tools for gathering data on the distribution and abundance of invasive alien trees using visual interpretation of Google Earth imagery, and propose how these data may be used for a number of purposes, including calculating useful metrics of invasions, prioritising species or areas for management and predicting potential distributions of species. We also suggest various practical uses of Google Earth, such as providing a tool for early detection of emerging invasions, monitoring invasions over time, and to help researchers and managers identify suitable field study sites. Virtual globes such as Google Earth are not without limitations and we provide guidance on how some of these can be overcome, or when imagery from Google Earth may not be fit for invasion science purposes. Because of Google Earth’s huge popularity and ease of use, we also highlight possibilities for awareness-raising and information sharing that it provides. Finally, we provide the foundations and guidelines for a virtual global network of sentinel sites for early detection, monitoring and data gathering of invasive alien trees, which we propose should be developed as part of a “citizen science” effort. There has been limited use of virtual globes by invasion scientists and managers; it is our hope that this paper will stimulate their greater use, both within the field of invasion science and within ecology generally.     

What would it take to describe the global diversity of parasites?

How many parasites are there on Earth? Here, we use helminth parasites to highlight how little is known about parasite diversity, and how insufficient our current approach will be to describe the full scope of life on Earth. Using the largest database of host–parasite associations and one of the world’s largest parasite collections, we estimate a global total of roughly 100 000–350 000 species of helminth endoparasites of vertebrates, of which 85–95% are unknown to science. The parasites of amphibians and reptiles remain the most poorly described, but the majority of undescribed species are probably parasites of birds and bony fish. Missing species are disproportionately likely to be smaller parasites of smaller hosts in undersampled countries. At current rates, it would take centuries to comprehensively sample, collect and name vertebrate helminths. While some have suggested that macroecology can work around existing data limitations, we argue that patterns described from a small, biased sample of diversity aren’t necessarily reliable, especially as host–parasite networks are increasingly altered by global change. In the spirit of moonshots like the Human Genome Project and the Global Virome Project, we consider the idea of a Global Parasite Project: a global effort to transform parasitology and inventory parasite diversity at an unprecedented pace.     

New tools for epidemiology: a space odyssey

Geographical Information Systems (GIS) facilitate access to epidemiological data through visualization and may be consulted for the development of mathematical models and analysis by spatial statistics. Variables such as land-cover, land-use, elevations, surface temperatures, rainfall etc. emanating from earth-observing satellites, complement GIS as this information allows the analysis of disease distribution based on environmental characteristics. The strength of this approach issues from the specific environmental requirements of those causative infectious agents, which depend on intermediate hosts for their transmission. The distribution of these diseases is restricted, both by the environmental requirements of their intermediate hosts/vectors and by the ambient temperature inside these hosts, which effectively govern the speed of maturation of the parasite. This paper discusses the current capabilities with regard to satellite data collection in terms of resolution (spatial, temporal and spectral) of the sensor instruments on board drawing attention to the utility of computer-based models of the Earth for epidemiological research. Virtual globes, available from Google and other commercial firms, are superior to conventional maps as they do not only show geographical and man-made features, but also allow instant import of data-sets of specific interest, e.g. environmental parameters, demographic information etc., from the Internet.     

netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis

Existing software tools for topology-based pathway enrichment analysis are either computationally inefficient, have undesirable statistical power, or require expert knowledge to leverage the methods’ capabilities. To address these limitations, we have overhauled NetGSA, an existing topology-based method, to provide a computationally-efficient user-friendly tool that offers interactive visualization. Pathway enrichment analysis for thousands of genes can be performed in minutes on a personal computer without sacrificing statistical power. The new software also removes the need for expert knowledge by directly curating gene-gene interaction information from multiple external databases. Lastly, by utilizing the capabilities of Cytoscape, the new software also offers interactive and intuitive network visualization.     

Preliminary Results of National Amyotrophic Lateral Sclerosis (ALS) Registry Risk Factor Survey Data

BackgroundThe National ALS Registry is made up of two components to capture amyotrophic lateral sclerosis (ALS) cases: national administrative databases (Medicare, Medicaid, Veterans Health Administration and Veterans Benefits Administration) and self-identified cases captured by the Registry’s web portal. This study describes self-reported characteristics of U.S. adults with ALS using the data collected by the National ALS Registry web portal risk factor surveys only from October 19, 2010 through December 31, 2013.ObjectiveTo describe findings from the National ALS Registry’s web portal risk factor surveys.MeasurementsThe prevalence of select risk factors among adults with ALS was determined by calculating the frequencies of select risk factors—smoking and alcohol (non, current and former) histories, military service and occupational history, and family history of neurodegenerative diseases such as ALS, Alzheimer’s and/or Parkinson’s.ResultsNearly half of survey respondents were ever smokers compared with nearly 41% of adults nationally. Most respondents were ever drinkers which is comparable to national estimates. The majority were light drinkers. Nearly one-quarter of survey respondents were veterans compared with roughly 9% of US adults nationally. Most respondents were retired or disabled. The industries in which respondents were employed for the longest time were Professional and Scientific and Technical Services. When family history of neurodegenerative diseases in first degree relatives was evaluated against our comparison group, the rates of ALS were similar, but were higher for Parkinson’s disease, Alzheimer’s disease and any neurodegenerative diseases.ConclusionsThe National ALS Registry web portal, to our knowledge, is the largest, most geographically diverse collection of risk factor data about adults living with ALS. Various characteristics were consistent with other published studies on ALS risk factors and will allow researchers to generate hypotheses for future research.     

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

We have developed an open software platform called Neurokernel for collaborative development of comprehensive models of the brain of the fruit fly Drosophila melanogaster and their execution and testing on multiple Graphics Processing Units (GPUs). Neurokernel provides a programming model that capitalizes upon the structural organization of the fly brain into a fixed number of functional modules to distinguish between these modules’ local information processing capabilities and the connectivity patterns that link them. By defining mandatory communication interfaces that specify how data is transmitted between models of each of these modules regardless of their internal design, Neurokernel explicitly enables multiple researchers to collaboratively model the fruit fly’s entire brain by integration of their independently developed models of its constituent processing units. We demonstrate the power of Neurokernel’s model integration by combining independently developed models of the retina and lamina neuropils in the fly’s visual system and by demonstrating their neuroinformation processing capability. We also illustrate Neurokernel’s ability to take advantage of direct GPU-to-GPU data transfers with benchmarks that demonstrate scaling of Neurokernel’s communication performance both over the number of interface ports exposed by an emulation’s constituent modules and the total number of modules comprised by an emulation.     

Preserving the Impossible: Conservation of Soft-Sediment Hominin Footprint Sites and Strategies for Three-Dimensional Digital Data Capture

Human footprints provide some of the most publically emotive and tangible evidence of our ancestors. To the scientific community they provide evidence of stature, presence, behaviour and in the case of early hominins potential evidence with respect to the evolution of gait. While rare in the geological record the number of footprint sites has increased in recent years along with the analytical tools available for their study. Many of these sites are at risk from rapid erosion, including the Ileret footprints in northern Kenya which are second only in age to those at Laetoli (Tanzania). Unlithified, soft-sediment footprint sites such these pose a significant geoconservation challenge. In the first part of this paper conservation and preservation options are explored leading to the conclusion that to ‘record and digitally rescue’ provides the only viable approach. Key to such strategies is the increasing availability of three-dimensional data capture either via optical laser scanning and/or digital photogrammetry. Within the discipline there is a developing schism between those that favour one approach over the other and a requirement from geoconservationists and the scientific community for some form of objective appraisal of these alternatives is necessary. Consequently in the second part of this paper we evaluate these alternative approaches and the role they can play in a ‘record and digitally rescue’ conservation strategy. Using modern footprint data, digital models created via optical laser scanning are compared to those generated by state-of-the-art photogrammetry. Both methods give comparable although subtly different results. This data is evaluated alongside a review of field deployment issues to provide guidance to the community with respect to the factors which need to be considered in digital conservation of human/hominin footprints.     

A Drosophila Toolkit for the Visualization and Quantification of Viral Replication Launched from Transgenic Genomes

Arthropod RNA viruses pose a serious threat to human health, yet many aspects of their replication cycle remain incompletely understood. Here we describe a versatile Drosophila toolkit of transgenic, self-replicating genomes (‘replicons’) from Sindbis virus that allow rapid visualization and quantification of viral replication in vivo. We generated replicons expressing Luciferase for the quantification of viral replication, serving as useful new tools for large-scale genetic screens for identifying cellular pathways that influence viral replication. We also present a new binary system in which replication-deficient viral genomes can be activated ‘in trans’, through co-expression of an intact replicon contributing an RNA-dependent RNA polymerase. The utility of this toolkit for studying virus biology is demonstrated by the observation of stochastic exclusion between replicons expressing different fluorescent proteins, when co-expressed under control of the same cellular promoter. This process is analogous to ‘superinfection exclusion’ between virus particles in cell culture, a process that is incompletely understood. We show that viral polymerases strongly prefer to replicate the genome that encoded them, and that almost invariably only a single virus genome is stochastically chosen for replication in each cell. Our in vivo system now makes this process amenable to detailed genetic dissection. Thus, this toolkit allows the cell-type specific, quantitative study of viral replication in a genetic model organism, opening new avenues for molecular, genetic and pharmacological dissection of virus biology and tool development.     

The Importance of Biodiversity E-infrastructures for Megadiverse Countries

Addressing the challenges of biodiversity conservation and sustainable development requires global cooperation, support structures, and new governance models to integrate diverse initiatives and achieve massive, open exchange of data, tools, and technology. The traditional paradigm of sharing scientific knowledge through publications is not sufficient to meet contemporary demands that require not only the results but also data, knowledge, and skills to analyze the data. E-infrastructures are key in facilitating access to data and providing the framework for collaboration. Here we discuss the importance of e-infrastructures of public interest and the lack of long-term funding policies. We present the example of Brazil’s speciesLink network, an e-infrastructure that provides free and open access to biodiversity primary data and associated tools. SpeciesLink currently integrates 382 datasets from 135 national institutions and 13 institutions from abroad, openly sharing ~7.4 million records, 94% of which are associated to voucher specimens. Just as important as the data is the network of data providers and users. In 2014, more than 95% of its users were from Brazil, demonstrating the importance of local e-infrastructures in enabling and promoting local use of biodiversity data and knowledge. From the outset, speciesLink has been sustained through project-based funding, normally public grants for 2–4-year periods. In between projects, there are short-term crises in trying to keep the system operational, a fact that has also been observed in global biodiversity portals, as well as in social and physical sciences platforms and even in computing services portals. In the last decade, the open access movement propelled the development of many web platforms for sharing data. Adequate policies unfortunately did not follow the same tempo, and now many initiatives may perish.     

Spatial and temporal invasion dynamics of the 2014–2017 Zika and chikungunya epidemics in Colombia

Zika virus (ZIKV) and chikungunya virus (CHIKV) were recently introduced into the Americas resulting in significant disease burdens. Understanding their spatial and temporal dynamics at the subnational level is key to informing surveillance and preparedness for future epidemics. We analyzed anonymized line list data on approximately 105,000 Zika virus disease and 412,000 chikungunya fever suspected and laboratory-confirmed cases during the 2014–2017 epidemics. We first determined the week of invasion in each city. Out of 1,122, 288 cities met criteria for epidemic invasion by ZIKV and 338 cities by CHIKV. We analyzed risk factors for invasion using linear and logistic regression models. We also estimated that the geographic origin of both epidemics was located in Barranquilla, north Colombia. We assessed the spatial and temporal invasion dynamics of both viruses to analyze transmission between cities using a suite of (i) gravity models, (ii) Stouffer’s rank models, and (iii) radiation models with two types of distance metrics, geographic distance and travel time between cities. Invasion risk was best captured by a gravity model when accounting for geographic distance and intermediate levels of density dependence; Stouffer’s rank model with geographic distance performed similarly well. Although a few long-distance invasion events occurred at the beginning of the epidemics, an estimated distance power of 1.7 (95% CrI: 1.5–2.0) from the gravity models suggests that spatial spread was primarily driven by short-distance transmission. Similarities between the epidemics were highlighted by jointly fitted models, which were preferred over individual models when the transmission intensity was allowed to vary across arboviruses. However, ZIKV spread considerably faster than CHIKV.     

Novel anti-repression mechanism of H-NS proteins by a phage protein

H-NS family proteins, bacterial xenogeneic silencers, play central roles in genome organization and in the regulation of foreign genes. It is thought that gene repression is directly dependent on the DNA binding modes of H-NS family proteins. These proteins form lateral protofilaments along DNA. Under specific environmental conditions they switch to bridging two DNA duplexes. This switching is a direct effect of environmental conditions on electrostatic interactions between the oppositely charged DNA binding and N-terminal domains of H-NS proteins. The Pseudomonas lytic phage LUZ24 encodes the protein gp4, which modulates the DNA binding and function of the H-NS family protein MvaT of Pseudomonas aeruginosa. However, the mechanism by which gp4 affects MvaT activity remains elusive. In this study, we show that gp4 specifically interferes with the formation and stability of the bridged MvaT–DNA complex. Structural investigations suggest that gp4 acts as an ‘electrostatic zipper’ between the oppositely charged domains of MvaT protomers, and stabilizes a structure resembling their ‘half-open’ conformation, resulting in relief of gene silencing and adverse effects on P. aeruginosa growth. The ability to control H-NS conformation and thereby its impact on global gene regulation and growth might open new avenues to fight Pseudomonas multidrug resistance.     

Combinations of PARP Inhibitors with Temozolomide Drive PARP1 Trapping and Apoptosis in Ewing’s Sarcoma

Ewing’s sarcoma is a malignant pediatric bone tumor with a poor prognosis for patients with metastatic or recurrent disease. Ewing’s sarcoma cells are acutely hypersensitive to poly (ADP-ribose) polymerase (PARP) inhibition and this is being evaluated in clinical trials, although the mechanism of hypersensitivity has not been directly addressed. PARP inhibitors have efficacy in tumors with BRCA1/2 mutations, which confer deficiency in DNA double-strand break (DSB) repair by homologous recombination (HR). This drives dependence on PARP1/2 due to their function in DNA single-strand break (SSB) repair. PARP inhibitors are also cytotoxic through inhibiting PARP1/2 auto-PARylation, blocking PARP1/2 release from substrate DNA. Here, we show that PARP inhibitor sensitivity in Ewing’s sarcoma cells is not through an apparent defect in DNA repair by HR, but through hypersensitivity to trapped PARP1-DNA complexes. This drives accumulation of DNA damage during replication, ultimately leading to apoptosis. We also show that the activity of PARP inhibitors is potentiated by temozolomide in Ewing’s sarcoma cells and is associated with enhanced trapping of PARP1-DNA complexes. Furthermore, through mining of large-scale drug sensitivity datasets, we identify a subset of glioma, neuroblastoma and melanoma cell lines as hypersensitive to the combination of temozolomide and PARP inhibition, potentially identifying new avenues for therapeutic intervention. These data provide insights into the anti-cancer activity of PARP inhibitors with implications for the design of treatment for Ewing’s sarcoma patients with PARP inhibitors.     

Explaining Bacterial Dispersion on Leaf Surfaces with an Individual-Based Model (PHYLLOSIM)

We developed the individual-based model PHYLLOSIM to explain observed variation in the size of bacterial clusters on plant leaf surfaces (the phyllosphere). Specifically, we tested how different ‘waterscapes’ impacted the diffusion of nutrients from the leaf interior to the surface and the growth of individual bacteria on these nutrients. In the ‘null’ model or more complex ‘patchy’ models, the surface was covered with a continuous water film or with water drops of equal or different volumes, respectively. While these models predicted the growth of individual bacterial immigrants into clusters of variable sizes, they were unable to reproduce experimentally derived, previously published patterns of dispersion which were characterized by a much larger variation in cluster sizes and a disproportionate occurrence of clusters consisting of only one or two bacteria. The fit of model predictions to experimental data was about equally poor (<5%) regardless of whether the water films were continuous or patchy. Only by allowing individual bacteria to detach from developing clusters and re-attach elsewhere to start a new cluster, did PHYLLOSIM come much closer to reproducing experimental observations. The goodness of fit including detachment increased to about 70–80% for all waterscapes. Predictions of this ‘detachment’ model were further supported by the visualization and quantification of bacterial detachment and attachment events at an agarose-water interface. Thus, both model and experiment suggest that detachment of bacterial cells from clusters is an important mechanism underlying bacterial exploration of the phyllosphere.     

R package for animal behavior classification from accelerometer data—rabc

Increasingly, animal behavior studies are enhanced through the use of accelerometry. To allow translation of raw accelerometer data to animal behaviors requires the development of classifiers. Here, we present the “rabc” (r for animal behavior classification) package to assist researchers with the interactive development of such animal behavior classifiers in a supervised classification approach. The package uses datasets consisting of accelerometer data with their corresponding animal behaviors (e.g., for triaxial accelerometer data along the x, y and z axes arranged as “x, y, z, x, y, z,…, behavior”). Using an example dataset collected on white stork (Ciconia ciconia), we illustrate the workflow of this package, including accelerometer data visualization, feature calculation, feature selection, feature visualization, extreme gradient boost model training, validation, and, finally, a demonstration of the behavior classification results.     

Movement-Based Estimation and Visualization of Space Use in 3D for Wildlife Ecology and Conservation

Advances in digital biotelemetry technologies are enabling the collection of bigger and more accurate data on the movements of free-ranging wildlife in space and time. Although many biotelemetry devices record 3D location data with x, y, and z coordinates from tracked animals, the third z coordinate is typically not integrated into studies of animal spatial use. Disregarding the vertical component may seriously limit understanding of animal habitat use and niche separation. We present novel movement-based kernel density estimators and computer visualization tools for generating and exploring 3D home ranges based on location data. We use case studies of three wildlife species – giant panda, dugong, and California condor – to demonstrate the ecological insights and conservation management benefits provided by 3D home range estimation and visualization for terrestrial, aquatic, and avian wildlife research.