评估基因组预测的实验设计原则

IF 6.3 2区 环境科学与生态学 Q1 ECOLOGY Methods in Ecology and Evolution Pub Date : 2024-07-10 DOI:10.1111/2041-210X.14379
Katie E. Lotterhos
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引用次数: 0

摘要

在过去的十年中,分子生态学、基因组学和全球变化交叉领域的预测模型发展迅速。这些 "基因组预测 "模型的共同目标是将基因组数据与环境和生态数据整合到一个模型中,对种群易受气候变化影响的程度进行定量预测。尽管方法学发展迅速,进行基因组预测的系统也越来越多,但预测本身却很少通过地面实况实验进行严格评估。本研究回顾了已完成的评估实验,介绍了有关基因组预测模型评估的重要术语,并讨论了设计和报告地面实况实验的重要因素。迄今为止,对基因组预测的实验评估发现,预测的准确性差异很大,但由于方法和实验设计不同,很难在共同基础上对研究进行比较。此外,由于训练数据和测试数据并不独立,一些评估可能会偏向于更高的性能。除了训练数据和测试数据之间的独立性之外,评价实验设计的重要因素还包括预测模型的构建和参数化、测试数据的适配性代用指标的选择、评价模型的构建、评价指标的选择、对新环境或基因型的外推程度以及预测的敏感性、不确定性和可重复性。虽然基因组预测方法越来越容易获得,但要评估其在特定研究系统中的局限性,还需要仔细规划和实验。精心设计的评估实验可以明确预测在管理中应用的稳健性。明确报告实验设计的基本要素将提高评估的严谨性,进而提高我们对模型在某些情况下有效而在其他情况下无效的原因的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Principles in experimental design for evaluating genomic forecasts

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来源期刊
CiteScore
11.60
自引率
3.00%
发文量
236
审稿时长
4-8 weeks
期刊介绍: A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas. MEE publishes methodological papers in any area of ecology and evolution, including: -Phylogenetic analysis -Statistical methods -Conservation & management -Theoretical methods -Practical methods, including lab and field -This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual. A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.
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