标题： 注意所谓的“良好”相关性：对个体mRNA-蛋白质预测的统计现实检查 显示英文标题

标题： Beware of so-called 'good' correlations: a statistical reality check on individual mRNA-protein predictions

摘要： 在生命科学的研究中，常常将信使核糖核酸（mRNA）的定量作为功能分析的独立方法。然而，尽管测得的mRNA水平和蛋白质水平之间的相关性是正的，但实际观察到的相关系数并不完整，因此在做出无偏推断时需要谨慎。本文对转录组学-蛋白质组学研究中相关强度的概念进行了统计反思和警示。它强调了在给定的经验相关值下，即使mRNA的数量精确，可能的蛋白质水平也存在变异性，并突出了mRNA-蛋白质对中，其丰度处于各自分布相反端的显著比例。细胞生物学家、数据科学家和生物统计学家应认识到，仅凭mRNA-蛋白质相关性不足以证明使用单一mRNA定量来推断其对应蛋白质的数量或功能是合理的。 显示英文摘要

摘要： Research in the life sciences often employs messenger ribonucleic acids (mRNA) quantification as a standalone approach for functional analysis. However, although the correlation between the measured levels of mRNA and proteins is positive, correlation coefficients observed empirically are incomplete, necessitating caution in making agnostic inferences. This essay provides a statistical reflection and caveat on the concept of correlation strength in the context of transcriptomics-proteomics studies. It highlights the variability in possible protein levels at given empirical correlation values, even for precise mRNA amount, and underscores the notable proportion of mRNA-protein pairs with abundances at opposite ends of their respective distributions. Cell biologists, data scientists, and biostatisticians should recognise that mRNA-protein correlation alone is insufficient to justify using a single mRNA quantification to infer the amount or function of its corresponding protein.