Avoiding common problems with statistical analysis of biological experiments using a simple nested data simulator

Abstract

Despite an extensive literature on statistical methods and their proper application to biological data, incorrect analyses remain a critical and widely spread problem in research papers. Inherently hierarchical (nested, clustered) structure of biological measurements is often erroneously neglected, leading to pseudo-replication and false positive results. This, in turn, complicates the correct assessment of statistical power and impairs optimal planning of experiments. In order to attract more attention to this problem and to illustrate the importance of direct account for the nested structure of biological data, in this article we present a simple open-source simulator of two-level normally distributed stochastic data. By defining 'true' mean values and 'true' intraand inter-cluster variances of the simulated data, users of the simulator can test various scenarios, appreciate the importance of using correct multi-level analysis and the danger of neglecting the information about the data structure. Here we apply our nested data simulator to highlight some commonly arising mistakes with data analysis and propose a workflow, in which our simulator could be employed to correctly compare two nested groups of experimental data and to optimally plan new experiments in order to increase statistical power when necessary.

Longitudinal multiparametric characterization of platelet dysfunction in COVID-19: Effects of disease severity, anticoagulation therapy and inflammatory status

“…Statistical information is given in the figure legends. For comparison between patient groups we have performed the nested [39] data analysis. Briefly, the data corresponding to each patient was averaged and an intercluster correlation [39] (ICC) was calculated.…”

“…For comparison between patient groups we have performed the nested [39] data analysis. Briefly, the data corresponding to each patient was averaged and an intercluster correlation [39] (ICC) was calculated. For the missing data linear interpolation was used.…”

“…For the missing data linear interpolation was used. For our data ICC was less than 0.5, therefore, we further analyzed only the averaged patients points using standard statistical approaches, as the risk for false-positive result in this case was significantly lesser than upon analysis of the data without taking nested structure into account [39] .…”

Systems Biology and Physiology Reports in 2021: a yearly report

“…The three major sections of the edition are related to the three major levels of understanding of the biological systems: molecular [1,2], cellular [3,4], and organism [5,6] levels. The papers published in the four issues during this year include original articles [1,2,4,6], reviews [5,[7][8][9], and methodological studies [10,11]. In addition, two large abstract collections Systems Biology and Systems Physiology Congress 2021 and International Congress devoted to the Memory of the Founders of Biophysics Department of Physics Faculty of Lomonosov Moscow State Universityprofessor L.A. Blumenfeld and professor S.E.…”