Abstract
The development of modern high-throughput instrumentation and improved core facility infrastructures leads to an accumulation of large amounts of scientific data. However, for a majority of scientists the comprehensive analysis and visualization of their data goes beyond their expertise. To reduce this hurdle, we developed a software suite called Instant Clue that helps scientists to visually analyze data and to gain insights into biological processes from their high-dimensional dataset. Instant Clue combines the power of visual and statistical analytics using a straight forward drag & drop approach making the software highly intuitive. Additionally, it offers a comprehensive portfolio of statistical tools for systematic analysis such as dimensional reduction, (un)-supervised learning, clustering, multi-block (omics) integration and curve fitting. Charts can be combined with high flexibility into a main figure template for direct usage in scientific publications. Even though Instant Clue was developed with the omics-sciences in mind, users can analyze any kind of data from low to high dimensional data sets. The open-source software is available for Windows and Mac OS (http://www.instantclue.uni-koeln.de) and is accompanied by a detailed video tutorial series.
Highlights
We address this gap by developing a software suite that enables scientists independent of their computational background to analyze their own complex data
In Instant Clue all activities are initiated via the Graphical User Interface (GUI) that is explained in Figs S1 and S2
The routine generation of high dimensional datasets demands the cooperative work between bioinformaticist and biological researcher
Summary
We address this gap by developing a software suite that enables scientists independent of their computational background to analyze their own complex data. The application of a statistical test requires the visual inspection of the data by the user. This workflow was implemented to help the user to interpret the test results. (v) Facilitate the collection of charts to generate figures with little post-processing prior to publication. To address these aims, we have created a software suite called Instant Clue which is available for Mac OS and Windows at http://www.instantclue.uni-koeln.de including detailed tutorials and working examples. The python source code is freely available making Instant Clue editable and available on any platform with a working Python version (>=3.4)
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