Web-based Visualization Tool Research Articles

LoRaFarM: A LoRaWAN-Based Smart Farming Modular IoT Architecture.

Presently, the adoption of Internet of Things (IoT)-related technologies in the Smart Farming domain is rapidly emerging. The ultimate goal is to collect, monitor, and effectively employ relevant data for agricultural processes, with the purpose of achieving an optimized and more environmentally sustainable agriculture. In this paper, a low-cost, modular, and Long-Range Wide-Area Network (LoRaWAN)-based IoT platform, denoted as “LoRaWAN-based Smart Farming Modular IoT Architecture” (LoRaFarM), and aimed at improving the management of generic farms in a highly customizable way, is presented. The platform, built around a core middleware, is easily extensible with ad-hoc low-level modules (feeding the middleware with data coming from the sensors deployed in the farm) or high-level modules (providing advanced functionalities to the farmer). The proposed platform has been evaluated in a real farm in Italy, collecting environmental data (air/soil temperature and humidity) related to the growth of farm products (namely grapes and greenhouse vegetables) over a period of three months. A web-based visualization tool for the collected data is also presented, to validate the LoRaFarM architecture.

CPVA: a web-based metabolomic tool for chromatographic peak visualization and annotation.

Liquid chromatography-mass spectrometry-based non-targeted metabolomics is routinely performed to qualitatively and quantitatively analyze a tremendous amount of metabolite signals in complex biological samples. However, false-positive peaks in the datasets are commonly detected as metabolite signals by using many popular software, resulting in non-reliable measurement. To reduce false-positive calling, we developed an interactive web tool, termed CPVA, for visualization and accurate annotation of the detected peaks in non-targeted metabolomics data. We used a chromatogram-centric strategy to unfold the characteristics of chromatographic peaks through visualization of peak morphology metrics, with additional functions to annotate adducts, isotopes and contaminants. CPVA is a free, user-friendly tool to help users to identify peak background noises and contaminants, resulting in decrease of false-positive or redundant peak calling, thereby improving the data quality of non-targeted metabolomics studies. The CPVA is freely available at http://cpva.eastus.cloudapp.azure.com. Source code and installation instructions are available on GitHub: https://github.com/13479776/cpva. Supplementary data are available at Bioinformatics online.

LogoJS: a Javascript package for creating sequence logos and embedding them in web applications.

Sequence logos were introduced nearly 30 years ago as a human-readable format for representing consensus sequences, and they remain widely used. As new experimental and computational techniques have developed, logos have been extended: extra symbols represent covalent modifications to nucleotides, logos with multiple letters at each position illustrate models with multi-nucleotide features and symbols extending below the x-axis may represent a binding energy penalty for a residue or a negative weight output from a neural network. Web-based visualization tools for genomic data are increasingly taking advantage of modern web technology to offer dynamic, interactive figures to users, but support for sequence logos remains limited. Here, we present LogoJS, a Javascript package for rendering customizable, interactive, vector-graphic sequence logos and embedding them in web applications. LogoJS supports all the aforementioned logo extensions and is bundled with a companion web application for creating and sharing logos. LogoJS is implemented both in plain Javascript and ReactJS, a popular user-interface framework. The web application is hosted at logojs.wenglab.org. All major browsers and operating systems are supported. The package and application are open-source; code is available at GitHub. zhiping.weng@umassmed.edu. Supplementary data are available at Bioinformatics online.

Using GARDEN-NET and ChAseR to explore human haematopoietic 3D chromatin interaction networks.

We introduce an R package and a web-based visualization tool for the representation, analysis and integration of epigenomic data in the context of 3D chromatin interaction networks. GARDEN-NET allows for the projection of user-submitted genomic features on pre-loaded chromatin interaction networks, exploiting the functionalities of the ChAseR package to explore the features in combination with chromatin network topology properties. We demonstrate the approach using published epigenomic and chromatin structure datasets in haematopoietic cells, including a collection of gene expression, DNA methylation and histone modifications data in primary healthy myeloid cells from hundreds of individuals. These datasets allow us to test the robustness of chromatin assortativity, which highlights which epigenomic features, alone or in combination, are more strongly associated with 3D genome architecture. We find evidence for genomic regions with specific histone modifications, DNA methylation, and gene expression levels to be forming preferential contacts in 3D nuclear space, to a different extent depending on the cell type and lineage. Finally, we examine replication timing data and find it to be the genomic feature most strongly associated with overall 3D chromatin organization at multiple scales, consistent with previous results from the literature.

AntVis: A web-based visual analytics tool for exploring ant movement data

We present AntVis, a web-based visual analytics tool for exploring ant movement data collected from the video recording of ants moving on tree branches. Our goal is to enable domain experts to visually explore massive ant movement data and gain valuable insights via effective visualization, filtering, and comparison. This is achieved through a deep learning framework for automatic detection, segmentation, and labeling of ants, ant movement clustering based on their trace similarity, and the design and development of five coordinated views (the movement, similarity, timeline, statistical, and attribute views) for user interaction and exploration. We demonstrate the effectiveness of AntVis with several case studies developed in close collaboration with domain experts. Finally, we report the expert evaluation conducted by an entomologist and point out future directions of this study.

VisBicluster: A Matrix-Based Bicluster Visualization of Expression Data.

One of the main methods to analyze gene expression data is biclustering, a nonsupervised technique, which consists of selection subgroups of genes that co-expressed under subgroups of experimental conditions. A large number of biclustering algorithms have been developed to classify gene expression data. These algorithms can give as output a large number of overlapped biclusters, whose visualization still requires deeper studies. We present VisBicluster, a web-based interactive visualization tool for displaying biclustering results. The developed visualization technique consists of laying out the generated biclusters in a two-dimensional matrix where each bicluster is represented as a column and each overlap between a set of biclusters is represented as a row. A search interface for the user is developed to query the matrix of bicluster intersection and visualize the results matching the queries. Our tool supports many interactive features such as sorting, zooming, and details-on-demand. We proved the usefulness of VisBicluster with biclustering results from real and synthetic datasets. Besides, we performed a user study with 14 participants to illustrate the clarity and simplicity of overlap representation with our tool.

A National-Scale Framework for Visualizing Riverine Concentrations of Microplastics Released from Municipal Wastewater Treatment Incorporating Generalized Instream Losses.

Down-the-drain exposure models provide a valuable tool for estimating environmental exposure to substances which are treated and discharged by municipal wastewater-treatment plants (WWTPs). Microplastics may enter WWTPs from consumer activities and disposal. An exposure framework was developed using the iSTREEM® model, which estimates spatially explicit concentrations of substances in riverine systems across the United States and portions of Ontario, Canada. One hundred simulations covering a range of WWTP removal and instream loss rates (proxy for net sedimentation) were incorporated into a Web-based visualization tool for user exploration of relative concentrations across simulations. Surface water concentrations specific to user-supplied tonnage were examined via interactive heat maps and cumulative distributions. Exploring the spatial aspect of iSTREEM results showed that modeling 90% WWTP removal and no instream loss resulted in 8.5% of the mass entering WWTPs discharged to marine estuaries (7.4%) or Great Lakes (1.1%) environments, with the remainder of the mass discharged (1.5%) in inland sinks or exiting the United States via rivers. Modeling an example instream loss of k = 0.1 d-1 (i.e., half-life = 7 d), terminal river segments contained 3.3% of influent mass (2.3% marine estuaries, 1.0% Great Lakes). Varying instream loss rates had substantial impacts on the total mass exported. The Web-based tool provided a user-based mechanism to visualize relative freshwater concentrations of microplastics across a large geographic area by varying simplified particle fate assumptions. Environ Toxicol Chem 2019;39:210-219. © 2019 SETAC.

ISB recommendations on the reporting of intersegmental forces and moments during human motion analysis

The International Society of Biomechanics (ISB) has charged this committee with development of a standard similar in scope to the kinematic standard proposed in Wu et al. (2002) and Wu et al. (2005). Given the variety of purposes for which intersegmental forces and moments are used in biomechanical research, it is not possible to recommend a particular set of analysis standards that will be acceptable in all applications. Instead, it is the purpose of this paper to recommend a set of reporting standards that will result in an understanding of the differences between investigations and the ability to reproduce the research. The end products of this standard are (1) a critical checklist that can be used during submission of manuscripts and abstracts to insure adequate description of methods, and (2) a web based visualization tool that can be used to alter the coordinate system, normalization technique and internal/external perspective of intersegmental forces and moments during walking and running so that the shape and magnitude of the curves can be compared to one’s own data.

Real-time health monitoring through urine metabolomics

Current healthcare practices are reactive and based on limited physiological information collected months or years apart. By enabling patients and healthy consumers access to continuous measurements of health, wearable devices and digital medicine stand to realize highly personalized and preventative care. However, most current digital technologies provide information on a limited set of physiological traits, such as heart rate and step count, which alone offer little insight into the etiology of most diseases. Here we propose to integrate data from biohealth smartphone applications with continuous metabolic phenotypes derived from urine metabolites. This combination of molecular phenotypes with quantitative measurements of lifestyle reflect the biological consequences of human behavior in real time. We present data from an observational study involving two healthy subjects and discuss the challenges, opportunities, and implications of integrating this new layer of physiological information into digital medicine. Though our dataset is limited to two subjects, our analysis (also available through an interactive web-based visualization tool) provides an initial framework to monitor lifestyle factors, such as nutrition, drug metabolism, exercise, and sleep using urine metabolites.

The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities.

The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.

Evaluation of Visualisation of Scanpath Trend Analysis (ViSTA) Tool

Eye tracking plays a key role in user behaviour understanding and usability studies. We previously proposed an algorithm called STA (Scanpath Trend Analysis) that analyses multiple individual scanpaths on a web page to discover their trending path in terms of the areas of interest (AOIs). This algorithm provides the most representative path of multiple users and compared to other algorithms (i.e., provides the most similar path to individual scanpaths). However, its current implementation has no graphical user interface and provides a sequence of characters that represent AOIs. Some external modules should also be installed in advance to run it. In our previous work, we presented the first web-based visualisation tool for the STA algorithm called ViSTA along with its initial evaluation. This tool allows to visualise individual scanpaths on a particular web page with gaze plots, visually draw AOIs, apply the STA algorithm, and visualise the result of the algorithm. In this paper, we present the extended version of ViSTA with a follow up user evaluation. The first version of ViSTA uses the STA algorithm which identifies trending AOIs based on all individual scanpaths. However, the extended one uses the STA algorithm with the tolerance level parameter which means trending elements can be identified based on a subset of individual scanpaths for discovering a more representative path. Both of our initial and follow up evaluations show that the workload in terms of NASA Task Load Index (TLX) is lower with ViSTA compared to the current implementation of the STA algorithm.

A Performant Web-Based Visualization, Assessment, and Collaboration Tool for Multidimensional Biosignals.

Biosignal-based research is often multidisciplinary and benefits greatly from multi-site collaboration. This requires appropriate tooling that supports collaboration, is easy to use, and is accessible. However, current software tools do not provide the necessary functionality, usability, and ubiquitous availability. The latter is particularly crucial in environments, such as hospitals, which often restrict users' permissions to install software. This paper introduces a new web-based application for interactive biosignal visualization and assessment. A focus has been placed on performance to allow for handling files of any size. The proposed solution can load local and remote files. It parses data locally on the client, and harmonizes channel labels. The data can then be scored, annotated, pseudonymized and uploaded to a clinical data management system for further analysis. The data and all actions can be interactively shared with a second party. This lowers the barrier to quickly visually examine data, collaborate and make informed decisions.

GEDS: A Gene Expression Display Server for mRNAs, miRNAs and Proteins.

High-throughput technologies generate a tremendous amount of expression data on mRNA, miRNA and protein levels. Mining and visualizing the large amount of expression data requires sophisticated computational skills. An easy to use and user-friendly web-server for the visualization of gene expression profiles could greatly facilitate data exploration and hypothesis generation for biologists. Here, we curated and normalized the gene expression data on mRNA, miRNA and protein levels in 23,315, 9009 and 9244 samples, respectively, from 40 tissues (The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GETx)) and 1594 cell lines (Cancer Cell Line Encyclopedia (CCLE) and MD Anderson Cell Lines Project (MCLP)). Then, we constructed the Gene Expression Display Server (GEDS), a web-based tool for quantification, comparison and visualization of gene expression data. GEDS integrates multiscale expression data and provides multiple types of figures and tables to satisfy several kinds of user requirements. The comprehensive expression profiles plotted in the one-stop GEDS platform greatly facilitate experimental biologists utilizing big data for better experimental design and analysis. GEDS is freely available online.

Abstract 911: UCSC Xena for cancer genomics visualization and interpretation

Abstract UCSC Xena (http://xena.ucsc.edu/) is a web-based visual integration and exploration tool for multi-omic data and associated clinical and phenotypic annotations. Our unique Visual Spreadsheet shows multiple data types side-by-side enabling discovery of correlations across and within genes and genomic regions. We offer dynamic Kaplan-Meier survival analysis, powerful filtering and subgrouping, charts, statistical analyses, genomic signatures, comparative transcript views, and bookmarks. We link out to the UCSC Genome Browser, giving users additional genomic context for any gene or coordinate, as well as MuPIT/CRAVAT and TumorMap, to give users complementary views of the same data. Xena showcases seminal cancer genomics datasets from TCGA, the Pan-Cancer Atlas, PCAWG, GDC, GTEx, ICGC, and more; a total of more than 1500 datasets across 50 cancer types. We support virtually any type of functional genomics data. In addition to the commonly available SNPs, INDELs, copy number variation, and gene expression datasets, we support DNA methylation, exon-, transcript-, miRNA-, lncRNA-expression and structural variants. We also support clinical data such as phenotypes, subtype classifications and biomarkers. A recompute of TCGA, TARGET and GTEx datasets through the same bioinformatics pipeline allows users to compare expression between tumor and normal tissues. All of our data is available for download via our python API or through AWS S3 buckets. A researcher can host their own data securely via private hubs running on a laptop or behind a firewall, with visual and analytical integration occurring only within the Xena Browser. The lightweight Xena Data Hubs are straightforward to install on Windows, Mac and Linux. Loading data is easy using either our application or command line interface. Our newest features include: * a new, more intuitive wizard to load your data into a local Hub * URL bookmarks to save interactive views for yourself or to share with collaborators * genomic signatures: dynamically build as a weighted sum over a set of genes * hierarchically cluster a list of genes, regulons or probes * upper vs lower quartile in a KM plot Citation Format: Mary Goldman, Brian Craft, Jingchun Zhu, David Haussler. UCSC Xena for cancer genomics visualization and interpretation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 911.

NX4: a web-based visualization of large multiple sequence alignments.

Multiple Sequence Alignments (MSAs) are a fundamental operation in genome analysis. However, MSA visualizations such as sequence logos and matrix representations have changed little since the nineties and are not well suited for displaying large-scale alignments. We propose a novel, web-based MSA visualization tool called NX4, which can handle genome alignments comprising thousands of sequences. NX4 calculates the frequency of each nucleotide along the alignment and visually summarizes the results using a color-blind friendly palette that helps identifying regions of high genetic diversity. NX4 also provides the user with additional assistance in finding these regions with a 'focus + context' mechanism that uses a line chart of the Shannon entropy across the alignment. The tool offers geneticists an easy-to-use and scalable analysis for large MSA studies. NX4 is freely available at https://www.nx4.io, and its source code at https://github.com/NX4/nx4. Supplementary data are available at Bioinformatics online.

VCF-Server: A web-based visualization tool for high-throughput variant data mining and management.

BackgroundNext‐generation sequencing (NGS) has been widely used in both clinics and research. It has become the most powerful tool for diagnosing genetic disorders and investigating disease etiology through the discovery of genetic variants. Variants identified by NGS are stored in variant call format (VCF) files. However, querying and filtering VCF files are extremely difficult for researchers without programming skills. Furthermore, as the mutation data are increasing exponentially, there is an urgent need to develop tools to manage these variant data in a centralized way.MethodsThe VCF‐Server was developed as a web‐based visualization tool to support the interactive analysis of genetic variant data. It allows researchers and medical geneticists to manage, annotate, filter, query, and export variants in a fast and effective way.ResultsIn this study, we developed the VCF‐Server, a powerful and easily accessible tool for researchers and medical geneticists to perform variant analysis. Users can query VCFs, annotate, and filter variants without knowing programming code. Once the VCF file is uploaded, VCF‐Server allows users to annotate the VCF with commonly used databases or user‐defined variant annotations (including variant blacklist and whitelist). Variant information in the VCF is shown visually via the interactive graphical interface. Users can filter the variants with flexible filtering rules, and the prioritized variants can be exported locally for further analysis. As VCF‐Server adopts a web file system, files in the VCF‐Server can be stored and managed in a centralized way. Moreover, VCF‐Server allows direct web‐based analysis (accessible through either desktop computers or mobile devices) as well as local deployment.ConclusionsWith an easy‐to‐use graphical interface, VCF‐Server allows researchers with little bioinformatics background to explore and mine mutation data, which may broaden the application of NGS technology in clinics and research. The tool is freely available for use at https://www.diseasegps.org/VCF-Server?lan = eng.

A spatial risk assessment model framework for incursion of exotic animal disease into the European Union Member States

Disease incursion and transmission modelling can play an important role in elucidating important pathways and dynamics of transboundary diseases. It is an important pre-requisite for preparedness and rapid response. A model framework has been developed which makes use of global datasets to predict the probability of entry of exotic animal pathogens to European Union (EU) member states (MSs) via some of the most likely routes of introduction: legal trade of livestock and meat products, illegal trade of red meat, wild animal dispersion, windborne vector dispersion and human introduction of pets. The model was designed to be applicable for a wide range of pathogens, many of which have limited data. We demonstrate its application through four case study pathogens: African swine fever, Classical swine fever, Bluetongue and classical rabies.The model results highlight the differences in probability between EU MSs; the absolute values for entry via a given route differed across MSs whilst different pathogens were predicted as having the highest probability of entry for the same route across MSs. Scenario analyses suggested that the probability of entry was heavily influenced by the pathogen prevalence in the country of origin and the extent to which EU MSs pose a risk to each other; the greatest risk was predominantly from countries within the EU. While we believe the input data are obtained from high quality sources, there are still big issues with regards uncertainty in some areas, in particular with regards to prevalence of pathogens in vector populations and consistency of reporting of pathogen prevalence in animals across all countries of the world. Thus, it is inevitable that there is a high degree of uncertainty associated with the absolute values. However, the main strength of the model is the broad range of analyses over pathogens, EU MSs and routes of entry. The model is also relatively easy to update with new data and a web based visualisation tool has been developed which allows users to interrogate the results of the model. As such, we believe that the model proposed here can be a useful quantitative complement to current qualitative early warning systems, helping to drive risk-based surveillance activities, by providing detailed quantitative comparisons to indicate which pathogens are most likely to enter the EU, by which route and into which areas within Europe.

DiVenn: An Interactive and Integrated Web-Based Visualization Tool for Comparing Gene Lists.

Gene expression data generated from multiple biological samples (mutant, double mutant, and wild-type) are often compared via Venn diagram tools. It is of great interest to know the expression pattern between overlapping genes and their associated gene pathways or gene ontology (GO) terms. We developed DiVenn (Dive into the Venn diagram and create a force directed graph)—a novel web-based tool that compares gene lists from multiple RNA-Seq experiments in a force-directed graph, which shows the gene regulation levels for each gene and integrated KEGG pathway and gene ontology knowledge for the data visualization. DiVenn has four key features: (1) informative force-directed graph with gene expression levels to compare multiple data sets; (2) interactive visualization with biological annotations and integrated pathway and GO databases, which can be used to subset or highlight gene nodes to pathway or GO terms of interest in the graph; (3) Pathway and GO enrichment analysis of all or selected genes in the graph; and (4) high resolution image and gene-associated information export. DiVenn is freely available at http://divenn.noble.org/.

Visual Analysis of a Smart City’s Energy Consumption

Through the use of open data portals, cities, districts and countries are increasingly making available energy consumption data. These data have the potential to inform both policymakers and local communities. At the same time, however, these datasets are large and complicated to analyze. We present the activity-centered-design, from requirements to evaluation, of a web-based visual analysis tool to explore energy consumption in Chicago. The resulting application integrates energy consumption data and census data, making it possible for both amateurs and experts to analyze disaggregated datasets at multiple levels of spatial aggregation and to compare temporal and spatial differences. An evaluation through case studies and qualitative feedback demonstrates that this visual analysis application successfully meets the goals of integrating large, disaggregated urban energy consumption datasets and of supporting analysis by both lay users and experts.

Aspectus: A Flexible Collaboration Tool for Multimodal and Multiscalar 3D Data Exploitation


 High density remote survey technologies have become widespread practices. In recent years, we have seen a tenfold increase in volume of digital data acquired. Beyond this sheer amount of data, multimodal three-dimensional data exploitation has become another common challenge for specialists. The Aspectus project aims to ease the access to complex three-dimensional data and to promote collaborative work and remote expert assessment. Thus, we can get past the problem of distance and availability of the “object of expertise”, ranging from cultural heritage sites to artefacts. By extension, it enables us to circumvent the ever-present problem of destruction. Aspectus takes advantage of available open source solutions to produce a flexible web-based visualization and collaboration tool. After an overview of the theoretical framework and its technical implementation, we will discuss a practical application as part of the “Bibracte Numérique” project.