<p>Phaedra is an open source platform for data capture and analysis of high-content screening data. With the release of <a rel="nofollow" href="https://www.phaedra.io/downloads/#102" target="_blank">Phaedra 1.0.2</a>, we are taking another step towards our goal of unprecedented flexibility in supported setups, ranging from a single small Mac desktop to a cloud-based infrastructure with multiple servers and an array of mixed Windows/Mac/Linux clients.</p>
<p>The initial release of Phaedra supported only the Windows platform. Update 1.0.1 introduced Phaedra on the Mac and Linux desktops, and allowed you to deploy a <a rel="nofollow" href="https://www.phaedra.io/addons/dcserver/" target="_blank">DataCapture server</a> on Linux servers as well. With update 1.0.2, stability was improved across all platforms, and cloud-based infrastructures are now also supported in the form of pluggable filestore backends. Amazon S3 is supported out-of-the box, as is any S3-compatible store such as <a rel="nofollow" href="https://www.minio.io/" target="_blank">Minio</a>. We intend to add more backends, to offer a true choice that can mesh with any corporate infrastructure.</p>
<p>But that’s not all! Take a look at the examples below that showcase other new or improved features in Phaedra 1.0.2.</p>
<h2>Creating charts with Python</h2>
<p>The <a rel="nofollow" href="https://www.phaedra.io/addons/python/" target="_blank">Python addon</a> offers a lot of interesting options. It can be used to create advanced calculated features, or for batch operations such as modifying large sets of plates. But with the new <a rel="nofollow" href="https://www.phaedra.io/howtos/scripting/#scripted-charts" target="_blank">Scripted Chart</a> view, you can also use Python scripts to generate charts and display them in Phaedra.</p>
<p><img border="0" alt="Scripted Python Chart" width="auto" src="https://www.r-bloggers.com/blog-img/charting1.png"></p>
<p>Many views in Phaedra are <em>reportable</em>, which means you can include them into a PDF report. The Scripted Chart view is no exception: you can save it and insert it into a report with a few clicks.</p>
<p><img border="0" alt="Scripted Python Chart in PDF report" width="auto" src="https://www.r-bloggers.com/blog-img/charting2.png"></p>
<h2>R-based workflows</h2>
<p>Phaedra contains the <a rel="nofollow" href="https://www.phaedra.io/addons/workflows/" target="_blank">Knime workflow engine</a> to empower users with an advanced data mining and processing toolbox.<br>
While Knime already has a big scientific community that has created hundreds of free <a rel="nofollow" href="https://www.knime.com/knime-community" target="_blank">addons</a>, there are still scenarios where you’d want to include your own R-based calculations in a workflow.</p>
<p>For that purpose, there is the R Snippet node: a workflow node that can execute arbitrary R code on a set of input data tables.</p>
<p><img border="0" alt="Example workflow with R snippet" width="auto" src="https://www.r-bloggers.com/blog-img/workflow1.png"></p>
<p>This R Snippet node uses Phaedra’s embedded R engine, which was just upgraded to version R-3.4.3.</p>
<h2>Image rendering with OpenJPEG</h2>
<p>At the core of Phaedra’s features are its image rendering capabilities. The ability to view data alongside the image that was the source of the data, is a concept we believe is fundamental to the Phaedra experience.</p>
<p><img border="0" alt="Various views with image rendering" width="auto" src="https://www.r-bloggers.com/blog-img/rendering1.png"></p>
<p>As these screenshots illustrate, Phaedra places high requirements on the image rendering component. Rendering a huge image in real-time (with the possibility of panning and zooming the image), or rendering dozens of small image crops at once, is no easy task for any image rendering codec.</p>
<p>Phaedra ships with the <a rel="nofollow" href="http://www.openjpeg.org/" target="_blank">OpenJPEG</a> codec, which has recently been updated with significant <a rel="nofollow" href="https://github.com/uclouvain/openjpeg/blob/v2.2.0/CHANGELOG.md" target="_blank">performance improvements</a>.</p>
<p>Documentation has been updated on the <a rel="nofollow" href="https://www.phaedra.io/" target="_blank">project homepage</a> and as always community support on this new release is available on our <a rel="nofollow" href="https://support.openanalytics.eu/" target="_blank">support site</a>.</p>
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