How to plot and analyze continuous (XY) data in BioRender Graph

In this guide, you'll learn how to plot and interpret continuous data using BioRender Graph. Continuous data shows the relationship between values on two axes: the X-axis (independent variable) and the Y-axis (dependent variable). Each point on the graph represents a specific relationship between these two values.

Note: Upload a spreadsheet directly to create graphs faster using our Smart Data Import tool.

Step-by-step guide

Step 1: Select your preferred visualization

1. After creating a new graph file, select the XY Analysis or Dose Response option and click Create.
2. Once your dataset is ready, choose from the following visualization options in the Graph Options dropdown menu:
   • Scatterplot
   • Mean/Median Point
   • Lineplot

The same plotting and display options apply to both linear and nonlinear trends and analyses.

Step 2: Select the right graph type for your use case

Scatterplot

• Displays individual data points on the X and Y axes.
• Supports multiple or unique observations for each X-axis value.

Mean/Median Points

• Displays the mean or median of multiple observations for each X-axis value.
• By default, shows the mean with standard deviation error bars.
• You can switch to standard error of the mean or 95% confidence intervals.

Lineplot

• Connects individual data points with a line.
• Supports multiple or unique observations per X-axis value.
• If you have multiple observations per X-axis value, it displays their mean/median, similar to Mean/Median Points.

Step 3: Visualize analysis results

1. If you selected Scatterplot or Mean/Median Point, you can also plot the line of best fit.
2. Access the analysis menu by:
   • Clicking Run Analysis under the graph.
   • Going to the Display Analysis section.
   • Clicking Add Analysis nested within the Dataset.
3. After running the analysis, display the line of best fit by clicking on Graph.
4. The best-fit line will automatically appear, and you can also:
   • Display 95% confidence intervals around the line.
   • Add details such as the equation, p-value, R-squared value, and standard error to your plot.

Troubleshooting

Can’t see the Graph?

• If you only have one group in your data, you may have skipped entering the Legend Categories variable.
• You still need to enter a variable name even if you have only one group; otherwise, the graph will not be displayed.
• Once you add this variable, the graph will appear.
• If you don’t want the variable name displayed in the legend, toggle legend visibility off.

Can’t see the line of best fit?

• If you selected Lineplot, the line of best fit is not available to avoid confusion with overlapping lines.
• Instead, create a new Graph under the same Dataset, select Scatterplot, and run a regression analysis to add the best-fit line.
• If your analysis did not converge (returned NA values), the line of best fit cannot be estimated. This is typically due to atypical data distribution, especially in dose response analysis.
• Inspect your data to identify potential nonlinearity issues.