268 research outputs found

    Bespoke data visualization using R and ggplot2

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    Scalable visualisation methods for modern Generalized Additive Models

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    In the last two decades the growth of computational resources has made it possible to handle Generalized Additive Models (GAMs) that formerly were too costly for serious applications. However, the growth in model complexity has not been matched by improved visualisations for model development and results presentation. Motivated by an industrial application in electricity load forecasting, we identify the areas where the lack of modern visualisation tools for GAMs is particularly severe, and we address the shortcomings of existing methods by proposing a set of visual tools that a) are fast enough for interactive use, b) exploit the additive structure of GAMs, c) scale to large data sets and d) can be used in conjunction with a wide range of response distributions. All the new visual methods proposed in this work are implemented by the mgcViz R package, which can be found on the Comprehensive R Archive Network

    DotMapper: an open source tool for creating interactive disease point maps

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    BACKGROUND: Molecular strain typing of tuberculosis isolates has led to increased understanding of the epidemiological characteristics of the disease and improvements in its control, diagnosis and treatment. However, molecular cluster investigations, which aim to detect previously unidentified cases, remain challenging. Interactive dot mapping is a simple approach which could aid investigations by highlighting cases likely to share epidemiological links. Current tools generally require technical expertise or lack interactivity. RESULTS: We designed a flexible application for producing disease dot maps using Shiny, a web application framework for the statistical software, R. The application displays locations of cases on an interactive map colour coded according to levels of categorical variables such as demographics and risk factors. Cases can be filtered by selecting combinations of these characteristics and by notification date. It can be used to rapidly identify geographic patterns amongst cases in molecular clusters of tuberculosis in space and time; generate hypotheses about disease transmission; identify outliers, and guide targeted control measures. CONCLUSIONS: DotMapper is a user-friendly application which enables rapid production of maps displaying locations of cases and their epidemiological characteristics without the need for specialist training in geographic information systems. Enhanced understanding of tuberculosis transmission using this application could facilitate improved detection of cases with epidemiological links and therefore lessen the public health impacts of the disease. It is a flexible system and also has broad international potential application to other investigations using geo-coded health information

    iSEE: Interactive SummarizedExperiment Explorer

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    Data exploration is critical to the comprehension of large biological data sets generated by high-throughput assays such as sequencing. However, most existing tools for interactive visualisation are limited to specific assays or analyses. Here, we present the iSEE (Interactive SummarizedExperiment Explorer) software package, which provides a general visual interface for exploring data in a SummarizedExperiment object. iSEE is directly compatible with many existing R/Bioconductor packages for analysing high-throughput biological data, and provides useful features such as simultaneous examination of (meta)data and analysis results, dynamic linking between plots and code tracking for reproducibility. We demonstrate the utility and flexibility of iSEE by applying it to explore a range of real transcriptomics and proteomics data sets.German Federal Ministry of Education and Researc

    DotMapper: an open source tool for creating interactive disease point maps

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    NetPanorama: A Declarative Grammar for Network Construction, Transformation, and Visualization

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    This paper introduces NetPanorama, a domain-specific language and declarative grammar for interactive network visualizations. Exploring complex networks with multivariate, geographical, or temporal information often require bespoke visualization designs, such as adjacency matrices, arc-diagrams, small multiples, timelines, or geographic map visualizations. However, creating these requires implementing data loading, data transformations, visualization, and interactivity, which is time-consuming and slows down the iterative exploration of this huge design space. With NetPanorama, a developer specifies a network visualization design as a pipeline of parameterizable steps. Our specification and reference implementation aims to facilitate visualization development and reuse; allow for easy design exploration and iteration; and make data transformation and visual mapping decisions transparent. Documentation, source code, examples, and an interactive online editor can be found online: https://netpanorama.netlify.app

    SCImago Graphica: a new tool for exploring and visually communicating data

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    Despite the increasing number of data visualization authoring systems in recent years, it remains a challenge to simultaneously achieve high expressive power and ease of use in a single tool. In this paper we present SCImago Graphica, a no-code tool which allows the creation of complex visualizations by simple drag-and-drop interactions. Users bind the data variables to the different encoding channels, and specify the settings of each binding, from which the tool generates the interactive graphical display. Due to its efficiency of use, SCImago Graphica is not only suitable for visually communicating data, but also for exploratory data analysis. We evaluate the expressiveness and ease of use of SCImago Graphica through various examples of chart construction and a catalog of visualizations. The results show that SCImago Graphica makes it possible to create a wide variety of data visualizations quickly and easily
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