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    Data Visualization

    Aleksandra Badaczewska

    Aleksandra Badaczewska

    Alex is a Research Scientist IV at the Genome Informatics Facility at Iowa State University. Her academic background is in Chemistry and Biotechnology, with a Ph.D. in Computational Biology and broad experience in programming and designing web applications. She develops a comprehensive collection of highly customizable visualization solutions for Bioinformatics and supports software optimization for the USDA Geospatial analyses.

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    Nowadays, data visualization is much more than just listing numbers in a table. Infographics and interactive charts perhaps best describe the need for the modern presentation of results. Such visualization is meant to make findings intuitively intelligible and easily understandable at a glance, even to the non-expert. At the same time, it should give the resources to interactively dig deeper into the details for those interested or those evaluating the merits. Let the science-based graphic design kick in the artist in you!

    Table of contents

    1. Introduction to Scientific Graphic Design

    • 1.1 Raster Graphics Tools
    • 1.2 Vector Graphics Tools
    • 1.3 Adobe Creative Cloud
    • 1.4 Template-based Web Tools

    2. Introduction to Scientific Graphing

    • 2.1 Gnuplot – Creating Plots in the UNIX Shell
    • 2.2 Plotly-Dash – Data Processing & Interactive Plotting with Python
      • Introduction to Plotly (Python library)
      • Introduction to Dash (Python library)
      • Interactive Graphing – Local Server with Web-Based Interface
      • Plotly Graphing - Interactive Examples in the JupyterLab
        • Tutorial: Creating XY Scatter Plot
        • Tutorial: Creating 1D Volcano Plot
        • Tutorial: Creating Heatmap
        • Tutorial: Creating Dendrogram
        • Tutorial: Creating Clustergram (Heatmap with Dendrograms)
    • 2.3 RStudio – Data Processing & Plotting with R
      • Setting Up an RStudio Environment
      • Tutorial: Creating Boxplots in R
      • Tutorial: Creating Heatmaps in R
      • Tutorial: Creating Heatmaps in R using ComplexHeatmap

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