Trials and tribulations of statistical significance in biochemistry and omics

Olimpio Montero; Mikael Hedeland; David Balgoma

doi:10.1016/j.tibs.2023.01.009

Trials and tribulations of statistical significance in biochemistry and omics

Trends Biochem Sci. 2023 Jun;48(6):503-512. doi: 10.1016/j.tibs.2023.01.009. Epub 2023 Feb 24.

Authors

Olimpio Montero¹, Mikael Hedeland², David Balgoma³

Affiliations

¹ Unidad de Excelencia, Instituto de Biología y Genética Molecular (IBGM), Universidad de Valladolid, Consejo Superior de Investigaciones Científicas (CSIC), Valladolid, Spain.
² Analytical Pharmaceutical Chemistry, Department of Medicinal Chemistry, Uppsala University, Sweden.
³ Unidad de Excelencia, Instituto de Biología y Genética Molecular (IBGM), Universidad de Valladolid, Consejo Superior de Investigaciones Científicas (CSIC), Valladolid, Spain; Analytical Pharmaceutical Chemistry, Department of Medicinal Chemistry, Uppsala University, Sweden. Electronic address: david.balgoma@ilk.uu.se.

PMID: 36842858
DOI: 10.1016/j.tibs.2023.01.009

Abstract

Over recent years many statisticians and researchers have highlighted that statistical inference would benefit from a better use and understanding of hypothesis testing, p-values, and statistical significance. We highlight three recommendations in the context of biochemical sciences. First recommendation: to improve the biological interpretation of biochemical data, do not use p-values (or similar test statistics) as thresholded values to select biomolecules. Second recommendation: to improve comparison among studies and to achieve robust knowledge, perform complete reporting of data. Third recommendation: statistical analyses should be reported completely with exact numbers (not as asterisks or inequalities). Owing to the high number of variables, a better use of statistics is of special importance in omic studies.

Keywords: Storey's q-values; hypothesis testing; p-values; selective reporting.

Publication types

Review