Comprehensive Guideline for Microbiome Analysis Using R.

Autor:	Boctor J; Biotechnology Program, American University in Cairo (AUC), Cairo, Egypt., Oweda M; Bioinformatics Group, Center of Informatics Sciences (CIS), Nile University, Giza, Egypt., El-Hadidi M; Bioinformatics Group, Center of Informatics Sciences (CIS), Nile University, Giza, Egypt. melhadidi@nu.edu.eg.
Jazyk:	angličtina
Zdroj:	Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2023; Vol. 2649, pp. 393-436.
DOI:	10.1007/978-1-0716-3072-3_20
Abstrakt:	The need for a comprehensive consolidated guide for R packages and tools that are used in microbiome data analysis is significant; thus, we aim to provide a detailed step-by-step dissection of the most used R packages and tools in the field of microbiome data integration and analysis. The guideline aims to be a user-friendly simplification and tutorial on five main packages, namely phyloseq, MegaR, DADA2, Metacoder, and microbiomeExplorer due to their high efficiency and benefit in microbiome data analysis. (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)
Databáze:	MEDLINE
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