计算基因组学及其在人类学问题中的应用。

IF 1.7 2区 生物学 Q1 ANTHROPOLOGY
Kelsey E Witt, Fernando A Villanea
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引用次数: 0

摘要

经济实惠的基因组测序的出现和新的计算工具的发展已经建立了一个基因组知识的新时代。已测序的人类基因组数量在数万个,其中包括数千个古人类基因组。丰富的数据已经满足了新的分析工具,可以用来了解人口的人口统计和进化历史。因此,现在有各种各样的计算方法可以用来回答人类学问题。这包括新颖的似然和贝叶斯方法,机器学习技术,以及大量的人口模拟器。这些计算工具提供了从基因组数据集获得的强大见解,尽管对于那些缺乏计算经验的人来说,它们通常是无法访问的。在这里,我们概述了计算基因组学方法背后的理论工作,应用这些计算方法时的局限性和其他考虑因素,以及计算方法如何应用于人类学问题的例子。我们希望这篇综述将使其他人类学家在他们自己的研究中利用这些强大的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational Genomics and Its Applications to Anthropological Questions.

The advent of affordable genome sequencing and the development of new computational tools have established a new era of genomic knowledge. Sequenced human genomes number in the tens of thousands, including thousands of ancient human genomes. The abundance of data has been met with new analysis tools that can be used to understand populations' demographic and evolutionary histories. Thus, a variety of computational methods now exist that can be leveraged to answer anthropological questions. This includes novel likelihood and Bayesian methods, machine learning techniques, and a vast array of population simulators. These computational tools provide powerful insights gained from genomic datasets, although they are generally inaccessible to those with less computational experience. Here, we outline the theoretical workings behind computational genomics methods, limitations and other considerations when applying these computational methods, and examples of how computational methods have already been applied to anthropological questions. We hope this review will empower other anthropologists to utilize these powerful tools in their own research.

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