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油棕植物化学研究统计工具的比较分析

Comparative analysis of statistical tools for oil palm phytochemical research.

作者信息

Ishak Nur Ain, Tahir Noor Idayu, Mohd Sa'id Syafi'ah Nadiah, Gopal Kathiresan, Othman Abrizah, Ramli Umi Salamah

机构信息

Advanced Biotechnology and Breeding Centre (ABBC), Malaysian Palm Oil Board (MPOB), No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia.

Faculty of Chemical Engineering, Universiti Teknologi MARA (UiTM) 40450 Shah Alam, Selangor, Malaysia.

出版信息

Heliyon. 2021 Feb 1;7(2):e06048. doi: 10.1016/j.heliyon.2021.e06048. eCollection 2021 Feb.

DOI:10.1016/j.heliyon.2021.e06048
PMID:33553773
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7856480/
Abstract

Recent advances in phytochemical analysis have allowed the accumulation of data for crop researchers due to its capacity to footprint and distinguish metabolites that are present within an organisms, tissues or cells. Apart from genotypic traits, slight changes either by biotic or abiotic stimuli will have significant impact on the metabolite abundances and will eventually be observed through physicochemical characteristics. Apposite data mining to interpret the mounds of phytochemical information from such a dynamic system is thus incumbent. In this investigation, several statistical software platforms ranging from exploratory and confirmatory technique of multivariate data analysis from four different statistical tools of COVAIN, SIMCA-P+, MetaboAnalyst and RIKEN Excel Macro were appraised using an oil palm phytochemical data set. As different software tool encompasses its own advantages and limitations, the insights gained from this assessment were documented to enlighten several aspects of functions and suitability for the adaptation of the tools into the oil palm phytochemistry pipeline. This comparative analysis will certainly provide scientists with salient notes on data assessment and data mining that will later allow the depiction of the overall oil palm status in-situ and ex-situ.

摘要

植物化学分析的最新进展使作物研究人员能够积累数据，因为它能够对生物体、组织或细胞内存在的代谢物进行特征分析和区分。除了基因型特征外，生物或非生物刺激引起的微小变化都会对代谢物丰度产生重大影响，并最终通过物理化学特征观察到。因此，进行恰当的数据挖掘以解释来自这样一个动态系统的大量植物化学信息是必不可少的。在这项研究中，使用油棕植物化学数据集对来自COVAIN、SIMCA-P+、MetaboAnalyst和RIKEN Excel Macro这四种不同统计工具的探索性和验证性多变量数据分析技术的几个统计软件平台进行了评估。由于不同的软件工具都有其自身的优点和局限性，因此记录了从该评估中获得的见解，以阐明这些工具在功能和适用于油棕植物化学流程方面的几个方面。这种比较分析肯定会为科学家提供有关数据评估和数据挖掘的重要提示，这将有助于描绘油棕在原地和异地的总体状况。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdfc/7856480/0d4193110060/gr16.jpg
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