Abstract
Taxonomic profiling among a large number of samples is a fundamental task during amplicon sequencing analysis. The heterogeneity and technical noises in the sample handling, library preparation, and sequencing present a major challenge to how the biological conclusions are drawn from the data analysis, and accordingly, many tools have been developed to address specific issues related to each step of the data analysis. Nowadays, several sophisticated computational pipelines with flexible parameters are made available to provide one-stop comprehensive solutions by integrating various tools, which significantly mitigate the burden imposed by the complexity of the metagenomics data analysis. This chapter discusses the best practices related to the data generation and describes bioinformatics approaches to achieving greater accuracy from data processing. It offers two independent stepwise pipelines using mothur and DADA2 in a parallel way, presents the basic principles in the key steps of the analysis, and enables the comparisons between the two pipelines straightforwardly.
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Wang, D. (2023). Amplicon Sequencing Pipelines in Metagenomics. In: Mitra, S. (eds) Metagenomic Data Analysis. Methods in Molecular Biology, vol 2649. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3072-3_4
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DOI: https://doi.org/10.1007/978-1-0716-3072-3_4
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