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GasanalyzeR:使用用于光合作用数据工作流程的新R包推进可重复研究。

GasanalyzeR: advancing reproducible research using a new R package for photosynthesis data workflows.

作者信息

Tholen Danny

机构信息

Department of Integrative Biology and Biodiversity Research, Institute of Botany, the University of Natural Resources and Life Sciences, Vienna, 1180 Vienna, Austria.

出版信息

AoB Plants. 2024 Jun 20;16(4):plae035. doi: 10.1093/aobpla/plae035. eCollection 2024 Jul.

Abstract

The analysis of photosynthetic traits has become an integral part of plant (eco-)physiology. Many of these characteristics are not directly measured, but calculated from combinations of several, more direct, measurements. The calculations of such derived variables are based on underlying physical models and may use additional constants or assumed values. Commercially available gas-exchange instruments typically report such derived variables, but the available implementations use different definitions and assumptions. Moreover, no software is currently available to allow a fully scripted and reproducible workflow that includes importing data, pre-processing and recalculating derived quantities. The R package gasanalyzer aims to address these issues by providing methods to import data from different instruments, by translating photosynthetic variables to a standardized nomenclature, and by optionally recalculating derived quantities using standardized equations. In addition, the package facilitates performing sensitivity analyses on variables or assumptions used in the calculations to allow researchers to better assess the robustness of the results. The use of the package and how to perform sensitivity analyses are demonstrated using three different examples.

摘要

光合特性分析已成为植物(生态)生理学不可或缺的一部分。其中许多特性并非直接测量得到,而是通过几个更直接的测量值组合计算得出。这些派生变量的计算基于基础物理模型,可能会使用额外的常数或假设值。市售的气体交换仪器通常会报告这些派生变量,但现有的实现方式使用不同的定义和假设。此外,目前没有软件可用于实现包括导入数据、预处理和重新计算派生量在内的完全脚本化且可重复的工作流程。R包gasanalyzer旨在通过提供从不同仪器导入数据的方法、将光合变量转换为标准化命名法以及使用标准化方程选择性地重新计算派生量来解决这些问题。此外,该包有助于对计算中使用的变量或假设进行敏感性分析,使研究人员能够更好地评估结果的稳健性。使用三个不同的示例展示了该包的使用方法以及如何进行敏感性分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a02/11261163/30d880b28546/plae035_fig1.jpg

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