Biology has become a highly mathematical discipline in which probabilistic models play a central role. As a result, research in the biological sciences is now dependent on computational tools capable of carrying out complex analyses. These tools must be validated before they can be used, but what is understood as validation varies widely among methodological contributions. This may be a consequence of the still embryonic stage of the literature on statistical software validation for computational biology. Our manuscript aims to advance this literature. Here, we describe, illustrate and introduce new good practices for assessing the correctness of a model implementation, with an emphasis on Bayesian methods. We also introduce a suite of functionalities for automating validation protocols. It is our hope that the guidelines presented here help sharpen the focus of discussions on (as well as elevate) expected standards of statistical software for biology.

中文翻译：

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如何验证贝叶斯进化模型


生物学已成为一门高度数学化的学科，其中概率模型起着核心作用。因此，生物科学的研究现在依赖于能够进行复杂分析的计算工具。这些工具在使用之前必须经过验证，但理解为验证的内容在方法论贡献之间差异很大。这可能是关于计算生物学统计软件验证的文献仍处于萌芽阶段的结果。我们的手稿旨在推进这些文献。在这里，我们描述、说明和介绍评估模型实现正确性的新良好实践，重点是贝叶斯方法。我们还介绍了一套用于自动化验证协议的功能。我们希望这里介绍的指南有助于加强对（以及提升）生物学统计软件预期标准的讨论重点。