Wisconsin Cooperative Fishery Research Unit, College of Natural Resources, University of Wisconsin-Stevens Point, Stevens Point, WI, USA.
Departamento de Biología Vegetal y Ecología, Facultad de Biología, Universidad de Sevilla, Sevilla, Spain.
Mol Ecol Resour. 2020 Jul;20(4):841-843. doi: 10.1111/1755-0998.13203. Epub 2020 Jul 2.
As molecular ecologists, we have by necessity become adept at working across computational platforms. A diverse community of scientists has developed a broad array of analytical resources spanning command line to graphical user interface across Linux, Mac, and Windows environments and a dizzying array of program-specific input formats. In light of this, we often explore our data like free divers - filling our lungs with air and descending for a short period of time into one part of our data set before resurfacing, reformatting, and preparing for our next analysis. In this issue of Molecular Ecology Resources, Meirmans (2020) presents an updated version of GenoDive, a program with a toolkit that provides users with the opportunity to stay a while and delve deeper into the diverse portfolio of information provided by a genomic data set. The comprehensive nature of GenoDive coupled with its unique capability to handle both diploid and polyploid data also provides an opportunity to reflect on the unevenness of resources available for the analysis of polyploid versus diploid data. Since new updates include the addition of plug-ins for genotype-environment association analyses, we limit the observations presented here to the common tools used for landscape genomics analyses.
作为分子生态学家，我们必须精通跨计算平台的工作。一个多样化的科学家社区开发了广泛的分析资源，涵盖了从命令行到图形用户界面的 Linux、Mac 和 Windows 环境，以及令人眼花缭乱的各种特定于程序的输入格式。有鉴于此，我们经常像自由潜水员一样探索我们的数据——在数据集的一个部分中短暂停留，吸入空气，然后浮出水面，重新格式化，并为下一次分析做好准备。在本期《分子生态学资源》中，Meirmans（2020）介绍了 GenoDive 的更新版本，该程序有一个工具包，为用户提供了深入研究基因组数据集所提供的各种信息的机会。GenoDive 的综合性及其独特的处理二倍体和多倍体数据的能力，也为分析多倍体与二倍体数据的资源不平衡提供了一个机会。由于新的更新包括增加了用于基因型-环境关联分析的插件，我们在这里的观察仅限于用于景观基因组学分析的常用工具。
