Because of its ability to find complex patterns in high dimensional and heterogeneous data, machine learning (ML) has emerged as a critical tool for making sense of the growing amount of genetic and genomic data available. While the complexity of ML models is what makes them powerful, it also makes them difficult to interpret. Fortunately, efforts to develop approaches that make the inner workings of ML models understandable to humans have improved our ability to make novel biological insights. Here, we discuss the importance of interpretable ML, different strategies for interpreting ML models, and examples of how these strategies have been applied. Finally, we identify challenges and promising future directions for interpretable ML in genetics and genomics.

中文翻译：

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打开黑匣子：遗传学家可解释的机器学习。

由于能够在高维和异构数据中找到复杂的模式，因此机器学习（ML）成为一种重要工具，可以用来理解越来越多的遗传和基因组数据。虽然ML模型的复杂性使它们变得强大，但也使它们难以解释。幸运的是，努力开发使人类可以理解ML模型的内部运作的方法的努力提高了我们提出新颖生物学见解的能力。在这里，我们讨论了可解释的ML的重要性，用于解释ML模型的不同策略，以及如何应用这些策略的示例。最后，我们确定了遗传学和基因组学中可解释的ML的挑战和有希望的未来方向。