Mohamed Omar Moawad Fares <br/><br/>
BENCHMARKING SEVERAL CLUSTERING AND DENOISING APPROACHES FOR OTUs/ASVs INFERENCE FROM AMPLICON BASED SEQUENCING/ 
Mohamed Omar Moawad Fares 
 -  2023 
 - 74 p.   ill.   21 cm.  
<br/><br/>Supervisor: Mohamed El-Helw 
<br/><br/>Thesis (M.A.)—Nile University, Egypt, 2023 . 
<br/><br/>"Includes bibliographical references" 
<br/><br/>Contents:<br/>Dedication................................................................................................................... iii<br/>Acknowledgments....................................................................................................... iv<br/>List of Tables .............................................................................................................. vi<br/>List of Figures............................................................................................................ vii<br/>Abstract..................................................................................................................... viii<br/>Introduction................................................................................................................... 1<br/>Background .................................................................................................................. 4<br/>Methods ...................................................................................................................... 18<br/>Results......................................................................................................................... 32<br/>Discussion................................................................................................................... 44<br/>References................................................................................................................... 53 
<br/><br/> Abstract:<br/>Amplicon sequencing is an indispensable tool for microbiome studies <br/>needed to unravel the taxonomical composition and relative abundance of <br/>microbial community. Yet, several artifacts are introduced at different <br/>processing steps, including sequencing errors necessitating the use of <br/>computational methods to eliminate those errors. Distance-based <br/>clustering into operational taxonomic units (OTUs) and sequence reads <br/>denoising into Amplicon Sequence Variants (ASVs) are two main <br/>approaches to handle this issue. Varying experimental setups and complex <br/>pipeline parameters have hindered unbiased comparisons between <br/>different approaches, resulting in divergent findings across separate <br/>studies. In this study, we aimed to conduct a comprehensive benchmarking <br/>analysis via an unbiased head-to-head comparison of eight different <br/>clustering and denoising algorithms by using a collection of various mocks <br/>from the Mockrobiota database. Using unified preprocessing steps for <br/>quality filtering and chimera removal, a fair comparison between DADA2, <br/>Deblur, MED, UNOISE3, UPARSE, DGC, Average neighborhood and <br/>Opticlust was conducted. DADA2 and UPARSE were the most efficient<br/>algorithms, producing comparable results in terms of overall error rate, <br/>percentage of exact matches to the mock reference and percentage of <br/>taxonomical over-splitting and over-merging. These results suggest that at <br/>the same level of quality preprocessing, sequence abundance filtering and <br/>chimera detection parameters, OTU clustering and ASV denoising <br/>produce comparable results with minor approach-dependent traits.<br/>Keywords: Amplicon Sequence Analysis, Denoising, Clustering, <br/>OTU, ASV, Benchmarking 
<br/><br/><br/>Text in English, abstracts in English and Arabic 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Informatics-IFM
<br/><br/><label>Index Terms--Genre/Form: </label><br/>Dissertation, Academic
<br/><br/><label>Dewey Class. No.: </label>610