Lefser:用 R 语言实现元基因组生物标记物发现工具 LEfSe。

Asya Khleborodova, Samuel D Gamboa-Tuz, Marcel Ramos, Nicola Segata, Levi Waldron, Sehyun Oh
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引用次数: 0

摘要

摘要:LEfSe 是一个广泛使用的 Python 软件包和 Galaxy 模块,它利用 Kruskal-Wallis 检验、Wilcoxon Rank-Sum 检验和线性判别分析发现元基因组生物标志物并将其可视化。R/Bioconductor 提供了大量用于元基因组数据分析的工具,但却缺少这种广泛使用的算法的实现,从而阻碍了与其他工具的基准比较和纳入 R 工作流程。我们推出了 lefser 软件包,在 R/Bioconductor 统计分析工具生态系统中提供了类似的功能,并对原始算法的性能、准确性和可重复性进行了改进。我们使用人类和小鼠元基因组数据集对lefser与原始算法的性能进行了基准测试:我们的软件 lefser 是通过 Bioconductor 项目 (https://www.bioconductor.org/packages/release/bioc/html/lefser.html) 发布的,所有源代码均可在 GitHub 存储库 https://github.com/waldronlab/lefser.Contact 获取:纽约市立大学公共卫生学院流行病学与生物统计学系人口健康实施科学研究所,美国纽约州纽约市。电子邮件: (S.O.)Sehyun.Oh@sph.cuny.edu (S.O.)。补充资料:补充数据可在 Bioinformatics online 上获取。
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Lefser: Implementation of metagenomic biomarker discovery tool, LEfSe, in R.

Summary: LEfSe is a widely used Python package and Galaxy module for metagenomic biomarker discovery and visualization, utilizing the Kruskal-Wallis test, Wilcoxon Rank-Sum test, and Linear Discriminant Analysis. R/Bioconductor provides a large collection of tools for metagenomic data analysis but has lacked an implementation of this widely-used algorithm, hindering benchmarking against other tools and incorporation into R workflows. We present the lefser package to provide comparable functionality within the R/Bioconductor ecosystem of statistical analysis tools, with improvements to the original algorithm for performance, accuracy, and reproducibility. We benchmark the performance of lefser against the original algorithm using human and mouse metagenomic datasets.

Availability and implementation: Our software, lefser, is distributed through the Bioconductor project (https://www.bioconductor.org/packages/release/bioc/html/lefser.html), and all the source code is available in the GitHub repository https://github.com/waldronlab/lefser.

Contact: Institute for Implementation Science in Population Health, Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, United States. E-mail: Sehyun.Oh@sph.cuny.edu (S.O.).

Supplementary information: Supplementary data are available at Bioinformatics online.

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Phasing Nanopore genome assembly by integrating heterozygous variations and Hi-C data. STRprofiler: efficient comparisons of short tandem repeat profiles for biomedical model authentication. Virtual Tissue Expression Analysis. Fast Polypharmacy Side Effect Prediction Using Tensor Factorisation. Lefser: Implementation of metagenomic biomarker discovery tool, LEfSe, in R.
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