BioRender Graphing provides a comprehensive suite of statistical analysis tools to help you interpret your experimental data with confidence.
Not sure which test to run? Graphing’s analysis guidance recommends the most appropriate test based on your data - running normality and equal variance checks in the background so you don’t have to look them up or ask an expert. If you choose a different test, BioRender will explain the trade-off so you can run analyses consistently, every time.
In this article, you'll learn how to:
- Get guidance to choose the right test - built-in pre-tests evaluate your data and recommend the most appropriate analysis, with a plain-language explanation of why
- Detect and remove outliers automatically - outliers are flagged instantly, so you can preview their impact and exclude them in one click
- Run statistical analyses - t-tests, ANOVAs, regressions, and more
- Compare graphs side-by-side - explore multiple analyses in one place and quickly spot patterns
Learn more about analysis guidance
See how BioRender recommends the right test for your data:
→ Statistical analysis: Available tests and how to run them
Outlier detection
The full outlier detection article covers how detection works and how to work with results, including:
- How the ROUT method works and why it handles multiple outliers better than simpler tests
- How to interpret outlier results
- How to adjust sensitivity or exclude data points
- Requirements and limits (minimum 4 observations per group, up to 28 groups)
→ Outlier detection in BioRender Graphing
How to run a statistical analysis
- On the Graph editing page, click + Run new analysis
- A structured form appears with three sections:
Section 1
When possible, BioRender Graphing’s analysis guidance automatically recommends the most appropriate statistical test based on your data. The recommended test is marked with a badge.
- You can override the recommendation by opening the dropdown to see all available options.
- If you select a test that doesn't match your data's assumptions (e.g., choosing a parametric test when the data isn't normal), a note explaining why the recommended test is still preferable.
- Some tests may appear grayed out if your data doesn't meet the requirements - to understand why, check out the tooltip.
Select categorical groups
- By default, all groups from the graph are included.
- Deselect any groups you don't want to include in this particular analysis.
Example (based on a one-way ANOVA)
Section 2 - Fine-tune your analysis
This section allows you to adjust statistical settings for your analysis. The available options may vary depending on the type of analysis you select. BioRender will recommend settings based on pre-tests run on your data, but you can modify them if needed.
- Data setup -Define how your data is organized for analysis. The available options will depend on your selected method.
- Advanced options- Expand this section to access additional configuration settings, if available.
- Assumptions- Some analyses include configurable assumptions about your data. Where applicable, you can review and adjust these settings.
Example (based on a one-way ANOVA)
Section 3 - Options and additional settings
Some analyses include additional options that let you refine how results are compared and calculated. These settings are only shown when relevant to your selected analysis, and recommended options are automatically applied.
- Comparisons
Where applicable, choose how groups or conditions are compared. This may include comparing all groups or selecting specific comparisons. - Follow-up tests
Some analyses include optional follow-up tests to explore differences between groups. You can select a method or use the recommended option. - Automatic recommendations
BioRender will suggest appropriate settings based on your analysis type and data, but you can adjust them if needed.
Example (based on a one-way ANOVA)
Viewing results
Once the analysis runs:
- A full results table and descriptive statistics appear in the Analysis panel
- Significant comparisons are automatically added to the graph with significance markers
- Use the checkboxes in the Analysis panel to toggle which results show on the graph
- You can run multiple analyses on the same graph and control which ones are displayed
Available analysis types
Ready to learn more? The next article covers analysis types and how to run a statistical analysis in BioRender's Graphing tool, including:
- t-tests
- One-way and Two-way ANOVAs
- Multiple comparisons tests
- Linear and dose-response regressions
- Survival analysis, logistic regression, and correlation
→ Statistical analysis: Available tests and how to run them
Compare graphs side-by-side with Graph Grid view
As your file grows, use the Graph Grid View (Graph tab) to see all graphs in the file at a glance.
Navigating the view
- Search for a graph by name
- Filter by dataset to narrow down to graphs from a specific data table
- Sort by name, created date, or last modified
Note: Graph Grid View shows only the graphs within the current file. Graphs from other files will not appear here.
What’s next
Your analysis is complete - now it's time to make it presentation-ready. Head to Presenting your graphs in BioRender Graphing to learn how to:
- Fine-tune your graph's appearance with live editing and Style Match
- Insert your graphs directly into PowerPoint or Google Slides
- Keep your graphs up to date as your data changes - with one click
Need help? Reach out to our support team at support@biorender.com or start a live chat by clicking the "Chat With Us" bubble in the bottom right corner.
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Articles in this section
- Statistical tests in BioRender Graphing: Methods, assumption checks, and R packages
- Statistical analysis: Available tests and how to run them
- Running statistical analyses in BioRender Graphing
- How BioRender recommends the right statistical test for your data
- Understanding outlier detection (ROUT method)
- How to plot and analyze continuous (XY) data in BioRender Graphing