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SuperPlots: Communicating reproducibility and variability in cell biology
Samuel J Lord1, Katrina B Velle2, R Dyche Mullins1
1Department of Cellular and Molecular Pharmacology, Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA.
Statistical significance and error bars are crucial for interpreting scientific findings. This study offers practical guidance on creating figures that clearly show both cell variability and experimental reproducibility.
Area of Science:
- Biostatistics
- Scientific Visualization
- Experimental Design
Background:
- P values and error bars are essential for assessing the reliability of reported differences in scientific research.
- Sample size (n) in statistical tests denotes biological replicates, representing independent measurements from separate experiments.
Purpose of the Study:
- To provide practical guidance and examples for generating figures.
- To enhance the communication of cell-level variability and experimental reproducibility in scientific data.
Main Methods:
- Demonstration of figure creation techniques.
- Tutorials for implementing statistical visualizations.
Main Results:
- Figures effectively communicate cell-level variability.
- Figures clearly illustrate experimental reproducibility.
Conclusions:
- Improved figure design aids in the interpretation of statistical significance.
- Clear visualization of variability and reproducibility enhances scientific rigor.
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