TY - CHAP
T1 - 16S rRNA Amplicon Sequencing
AU - Christensen, Henrik
AU - Andersson, Jasmine
AU - Jørgensen, Steffen Lynge
AU - Vogt, Josef Korbinian
PY - 2023
Y1 - 2023
N2 - The 16S rRNA amplicon sequencing technique is a microbiome analysis where different samples are analyzed at the same time using multiplexing. The results can be used to evaluate microbial diversity at genus, family, order, class, and phylum levels. The resolution is normally insufficient to evaluate the species level. The different steps in the bioinformatical analysis allow both the analysis of all samples combined or comparisons between samples. The bioinformatics analysis focuses on quality control of reads, merging of identical reads and grouping of reads into operational taxonomic units (OTUs) with a threshold of 97%. The threshold is inherited from the species threshold for classification of species based on 16S rRNA sequence comparison. The distribution of reads and OTUs within and between samples can be used to estimate α- and β-diversity, respectively. An alternative to OTU dereplication is divisive amplicon denoising algorithm (DADA). This algorithm groups reads according to statistical modeling identifying a most probable central sequence, and Amplicon sequence variants (ASVs) is the term. The relative occurrence of the taxonomic units at the levels of genus, family, order, class, and phylum can be compared between samples. These distributions can be related to metadata by principal component analysis.
AB - The 16S rRNA amplicon sequencing technique is a microbiome analysis where different samples are analyzed at the same time using multiplexing. The results can be used to evaluate microbial diversity at genus, family, order, class, and phylum levels. The resolution is normally insufficient to evaluate the species level. The different steps in the bioinformatical analysis allow both the analysis of all samples combined or comparisons between samples. The bioinformatics analysis focuses on quality control of reads, merging of identical reads and grouping of reads into operational taxonomic units (OTUs) with a threshold of 97%. The threshold is inherited from the species threshold for classification of species based on 16S rRNA sequence comparison. The distribution of reads and OTUs within and between samples can be used to estimate α- and β-diversity, respectively. An alternative to OTU dereplication is divisive amplicon denoising algorithm (DADA). This algorithm groups reads according to statistical modeling identifying a most probable central sequence, and Amplicon sequence variants (ASVs) is the term. The relative occurrence of the taxonomic units at the levels of genus, family, order, class, and phylum can be compared between samples. These distributions can be related to metadata by principal component analysis.
U2 - 10.1007/978-3-031-45293-2_8
DO - 10.1007/978-3-031-45293-2_8
M3 - Book chapter
SN - 978-3-031-45292-5
T3 - Learning materials in biosciences
SP - 153
EP - 181
BT - Introduction to Bioinformatics in Microbiology
A2 - Christensen, Henrik
PB - Springer
ER -