Bioinformatics
Statistics
Statistics Overview
Statistics included within Metabolon’s Integrated Bioinformatics Platform provide additional utility and control for exploring and interpreting your data. As your research grows, the statistics tool supports further hypothesis testing and analyses using key features such as outlier removal and modifying metadata and enables researchers to run additional statistical tests such as T-tests and ANOVAs, all following an easy, step-by-step process.
Researchers handling large sample datasets often need help filtering out unnecessary data and focusing on what’s important. Statistics within the Bioinformatics Platform includes easy-to-use features that help simplify data analysis, allowing for deeper insights—even without experience in bioinformatics or statistical methods.
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Statistics within Our Bioinformatics Platform
The Statistics tool plays a critical role in supporting complex research initiatives. It enables users to design and execute customized analyses, manage diverse metadata configurations, and visualize results in intuitive and insightful ways.
Outlier Removal
The outlier removal feature enables you to remove samples manually by selecting them from the sample metadata table. Alternatively, you can remove outliers in the PCA and PLS-DA modules for a data-driven approach to outlier removal.
Metadata Management
Scientific research is iterative, and what you derive from your sample data may evolve. The Statistics tool allows a flexible approach to updating sample metadata while retaining original and intermediate copies of the metadata table. Statistical analyses are associated with distinct instances of sample metadata, so you can keep exploring every facet of your dataset and always trace back what you did.
Custom Comparison With Advanced Statistics
Statistics forms the foundation of scientific research, enabling researchers to align their methods with the research objectives and the underlying data structure for reliable and meaningful results. The Statistics tool guides you through a step-by-step process to create comparisons and employ the most appropriate statistics for the research question. Select from T-tests, One-way ANOVA, and Two-way ANOVA to quickly iterate and test hypotheses and maintain a complete record of your analysis work.
Powerfully Customizable Statistics for High-Impact Analysis
Hypothesis Testing
Statistics offers advanced tools for hypothesis testing, enabling rigorous testing of research questions against complex datasets, essential for validating findings and ensuring scientific accuracy.
Immediate Results Visualization
Users can immediately view the results of their statistics across all integrated visualization tools, allowing for immediate interpretation and decision-making.
Customizable Reporting
The Statistics tool enables the generation of comprehensive reports tailored to specific aspects of the analysis, which is particularly useful for sharing findings with stakeholders or for publications.
Dynamic Metadata Integration
The Statistics tool supports seamless integration and adjustment of metadata. Users can update factors, customize names, and modify levels, directly influencing the resultant analyses and visual outputs. This ensures accuracy and relevance as new data or hypotheses emerge.
Address Outliers
Not all data is relevant to your research and may hinder the identification of common traits among sample groups. The Outlier Removal feature allows you to select samples for exclusion and queue a new job, refining your analysis by focusing on high-impact trends and reducing noise.
Statistics Features
Analyses
The “Analyses” tab allows you to monitor the status and review the specific details of analyses in the current project. Completed analyses’ can be activated for visualization in the other modules of the Integrated Bioinformatics Platform. Keep track of your entire statistical workflow in one place and maintain clear traceability of your research activity.
Define New Analysis
The “Define Analysis” tab follows a step-by-step guide to quickly launch advanced analysis on your data by configuring test selection (e.g., T-Test, One-way ANOVA, and Two-way ANOVA), data selection, analysis settings, and, finally, specific sample group comparisons.
Modify Sample Metadata
The “Modify Sample Metadata” tab lets you view and edit original and modified metadata for samples in a project. The updated sample metadata can power new statistical analyses and comparisons while maintaining persistent copies of previous metadata for traceability.
Outlier Removal
This tab allows you to remove samples or outliers from the sample metadata table to create a new sample set. New sample sets are reanalyzed, and the results are then available for visualization in the other modules of the Integrated Bioinformatics Platform, such as Volcano Plot or PCA. Outliers can also be automatically detected in PCA and PLS-DA and selected for removal.
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