The size of a subplot is determined by the underlying grid (more information can be found at – commented video tutorial). (ii) add subplot at desired position and size. (i) Create a main figure of fixed size (A4 paper). (a) Workflow to create a main figure template consists of three steps that allows the collection of charts made in Instant Clue or from the user’s documents (Portable Network Graphics (png) files). Ĭollecting charts in a main figure template. Due to its diversity and complexity all functions cannot be described here and further information and examples can be found at. (top-left) Row-wise curve fitting as well as correlation-based analysis can be performed in a customizable and versatile way. Time series data can also be explored and techniques such as base line correction and measuring the area under curve (AUC) are implemented in an interactive way. Moreover, principal component analysis and cluster analysis can be initialized by one simple drag & drop event. A comprehensive toolbox for supervised learning has been implemented using the scikit-learn library allowing the user to set up pipelines with data-preprocessing, feature selection and prediction (bottom). To integrate multiple omics data, users can use method such as sparse generalized canonical correlation analysis (SGCCA)³⁵ to select features such as genes, proteins, miRNAs that strongly contribute to the multi-omics signature (right). Up to a three-way ANOVA design is available with and without repeated measurements (top-right). t- and U-test) or multiple groups (ANOVA, Kruskal Wallis). The statistical toolbox offers functionality to compare two-groups using non-parametric and parametric tests (e.g. Description clockwise starting from top-right. The open-source software is available for Windows and Mac OS ( ) and is accompanied by a detailed video tutorial series. 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. Charts can be combined with high flexibility into a main figure template for direct usage in scientific publications. 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. Instant Clue combines the power of visual and statistical analytics using a straight forward drag & drop approach making the software highly intuitive. 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. However, for a majority of scientists the comprehensive analysis and visualization of their data goes beyond their expertise. The development of modern high-throughput instrumentation and improved core facility infrastructures leads to an accumulation of large amounts of scientific data.
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