A snapshot of statistical methods used in experimental immunoblotting: a scoping review

Background: Among the many avenues considered to make life science more reproducible, the improvement of the quality and openness of statistical methods has taken centre stage. However, although disparities across research fields and techniques are not unknown, they remain largely unexplored. Objectives: Provide an overview of statistical methods used in biochemical research involving immunoblotting (also referred to as western blotting), a technique frequently used to quantify proteins of interest. Source of evidence: PubMed. Eligibility criteria: Studies reporting immunoblots with quantitative interpretation (statistical inference). Charting Methods: A reverse chronological systematic sampling was implemented to analyse 2932 experimental conditions (i.e., experimental groups) from 64 articles published at the end of 2021. The statistical test (actual study size n = 67) and software (actual study size n = 61) used for each article and the sample size for each experimental condition were documented. Results: The results indicate an overhelming number of parametric tests, mostly one-way analysis of variance (ANOVA, 15/67) and Student’s t-test (13/67), but for many articles the statistical procedure was not clearly stated (23/67). GraphPad Prism was the most commonly used statistical package (36/61), but many (14/61) articles did not reveal the package used. Finally, the sample size was disclosed in only 1054/2932 conditions in which its median value was 3 (IQR = [3–6]). Conclusion: This study suggests that the transparency of reporting might be suboptimal in immunoblotting research and prompts the need for more comprehensive reviews in the future.