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Introduction

TSE Analytics is a data analysis application designed specifically to work with the data output produced by TSE PhenoMaster software. It allows a simplified management of multiple datasets, data sharing and reproducibility of experimental results in a flexible and user-friendly way.

TSE Analytics offers a wide range of tools for easy and convenient processing of large datasets. These include:

  • Integrated Data Handling: TSE Analytics is designed to manage complex datasets like PhenoMaster data and integrates data processing, visualization, and statistical analysis.
  • Flexible Data Customization: The software allows users to tailor data structures to their specific needs by, for example, excluding outliers, defining time frames, merging multiple datasets, and creating new grouping factors.
  • Automated Data Management: TSE Analytics facilitates multi-dataset management with automatic data extraction and dataset processing options.
  • Dynamic Visualization: TSE Analytics allows to quickly visualize data over time using the plot function and quickly screen and compare data across different groups, individual animals, or specific time periods.
  • Comprehensive Statistical Analysis: The software includes a broad range of statistical tools, from data exploration to advanced analyses.
  • User-Friendly, Flexible and Efficient: TSE Analytics stands out for its ease of use and extensive analytical capabilities combined with various export functions.
  • Collaboration: By using TSE Analytics, researchers can generate standardized output reports to ensure the comparability of research findings.

Data Visualization and Statistical Analysis

TSE Analytics hosts various options for data analysis and visualization:

  • Timeline Visualization: Visualize raw data on a timeline or in time bins with the possibility to easily switch between individual animals or apply grouping by factors or runs.
  • Explorative Analysis: Assess and visualize data distribution of selected variables using histograms, violin or box plots, and normality analysis with the possibility to apply grouping by animal, factor or run.
  • Bivariate Analysis: Calculate correlations between two variables using correlation or linear regression analysis.
  • Analysis of Variance (ANOVA) and Analysis of Covariance (ANCOVA): Perform several types of ANOVA (N-way, repeated measures, mixed-design) or ANCOVA, taking into account experimental factors and time bins.
  • Multivariate and High-Dimensional Analysis: Visualize and analyze correlations between multiple variables using matrix plots and dimensionality reduction techniques such as Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE).
  • Time Series Analysis: Perform time series analysis to detect patterns or trends in PhenoMaster data collected at regular time intervals.

In this user manual, we will provide a detailed guide on how to operate TSE Analytics, including how to import, process, and analyze PhenoMaster data. With step-by-step instructions and practical examples, users will be able to quickly get started and make the most of the software's features. Now, let’s begin!