Vihinen Mauno
Department of Experimental Medical Science, BMC D10, Lund University, Lund, Sweden.
Hum Mutat. 2014 Aug;35(8):912-4. doi: 10.1002/humu.22600. Epub 2014 Jun 28.
Computational tools are essential for most of our research. To use these tools, one needs to know how they work. Problems in application of computational methods to variation analysis can appear at several stages and affect, for example, the interpretation of results. Such cases are discussed along with suggestions how to avoid them. The applications include incomplete reporting of methods, especially about the use of prediction tools; method selection on unscientific grounds and without consulting independent method performance assessments; extending application area of methods outside their intended purpose; use of the same data several times for obtaining majority vote; and filtering of datasets so that variants of interest are excluded. All these issues can be avoided by discontinuing the use software tools as black boxes.
计算工具对我们的大多数研究至关重要。要使用这些工具，人们需要了解它们的工作原理。在将计算方法应用于变异分析时，问题可能出现在几个阶段，并影响例如结果的解释。本文将讨论这些情况，并提出如何避免这些情况的建议。这些应用包括方法报告不完整，特别是关于预测工具的使用；基于不科学的理由选择方法，且未参考独立的方法性能评估；将方法的应用领域扩展到其预期目的之外；多次使用相同的数据以获得多数投票；以及对数据集进行筛选，从而排除感兴趣的变异。通过不再将软件工具当作黑箱使用，所有这些问题都可以避免。
