通过微生物组数据中的线性判别分析效应大小 (LEfSe) 辅助选择生物标记物。

IF 1.8 3区 哲学 Q2 ETHICS Ethics & Behavior Pub Date : 2022-05-16 DOI:10.3791/61715
Fang Chang, Shishi He, Chenyuan Dang
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引用次数: 0

摘要

人们越来越关注环境和健康中的封闭生物基因组。为了探索和揭示不同样本或环境中的组间差异,发现具有组间统计差异的生物标志物至关重要。线性判别分析效应大小(LEfSe)的应用有助于找到好的生物标志物。在原始基因组数据的基础上,根据类群或基因对不同序列进行质量控制和量化。首先,使用 Kruskal-Wallis 秩检验来区分统计组和生物组之间的特定差异。然后,在上一步得到的两组之间进行 Wilcoxon 秩检验,以评估差异是否一致。最后,进行线性判别分析(LDA),根据 LDA 分数评估生物标志物对明显不同组别的影响。总之,LEfSe 为鉴定基因组生物标志物提供了便利,这些生物标志物可表征生物组间的统计差异。
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Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size (LEfSe) in Microbiome Data.

There is growing attention toward closed biological genomes in the environment and in health. To explore and reveal the intergroup differences among different samples or environments, it is crucial to discover biomarkers with statistical differences among groups. The application of Linear discriminant analysis Effect Size (LEfSe) can help find good biomarkers. Based on the original genome data, quality control, and quantification of different sequences based on taxa or genes are carried out. First, the Kruskal-Wallis rank test was used to distinguish between specific differences among statistical and biological groups. Then, the Wilcoxon rank test was performed between the two groups obtained in the previous step to assess whether the differences were consistent. Finally, a linear discriminant analysis (LDA) was conducted to evaluate the influence of biomarkers on significantly different groups based on LDA scores. To sum up, LEfSe provided the convenience for identifying genomic biomarkers that characterize statistical differences among biological groups.

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来源期刊
Ethics & Behavior
Ethics & Behavior Multiple-
CiteScore
4.40
自引率
0.00%
发文量
38
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