TY  - BOOK
AU  - Mohamed Omar Moawad Fares
TI  - BENCHMARKING SEVERAL CLUSTERING AND DENOISING APPROACHES FOR OTUs/ASVs INFERENCE FROM AMPLICON BASED SEQUENCING
U1  - 610 
PY  - 2023///
KW  - Informatics-IFM
KW  - NULIB
KW  - Dissertation, Academic
N1  - Thesis (M.A.)—Nile University, Egypt, 2023; "Includes bibliographical references"; Contents:
Dedication................................................................................................................... iii
Acknowledgments....................................................................................................... iv
List of Tables .............................................................................................................. vi
List of Figures............................................................................................................ vii
Abstract..................................................................................................................... viii
Introduction................................................................................................................... 1
Background .................................................................................................................. 4
Methods ...................................................................................................................... 18
Results......................................................................................................................... 32
Discussion................................................................................................................... 44
References................................................................................................................... 53
N2  - Abstract:
Amplicon sequencing is an indispensable tool for microbiome studies 
needed to unravel the taxonomical composition and relative abundance of 
microbial community. Yet, several artifacts are introduced at different 
processing steps, including sequencing errors necessitating the use of 
computational methods to eliminate those errors. Distance-based 
clustering into operational taxonomic units (OTUs) and sequence reads 
denoising into Amplicon Sequence Variants (ASVs) are two main 
approaches to handle this issue. Varying experimental setups and complex 
pipeline parameters have hindered unbiased comparisons between 
different approaches, resulting in divergent findings across separate 
studies. In this study, we aimed to conduct a comprehensive benchmarking 
analysis via an unbiased head-to-head comparison of eight different 
clustering and denoising algorithms by using a collection of various mocks 
from the Mockrobiota database. Using unified preprocessing steps for 
quality filtering and chimera removal, a fair comparison between DADA2, 
Deblur, MED, UNOISE3, UPARSE, DGC, Average neighborhood and 
Opticlust was conducted. DADA2 and UPARSE were the most efficient
algorithms, producing comparable results in terms of overall error rate, 
percentage of exact matches to the mock reference and percentage of 
taxonomical over-splitting and over-merging. These results suggest that at 
the same level of quality preprocessing, sequence abundance filtering and 
chimera detection parameters, OTU clustering and ASV denoising 
produce comparable results with minor approach-dependent traits.
Keywords: Amplicon Sequence Analysis, Denoising, Clustering, 
OTU, ASV, Benchmarking
ER  -