Print Email Facebook Twitter SARS-CoV-2 lineage abundance quantification in wastewater: a benchmark study for the identification of optimal reference set design Title SARS-CoV-2 lineage abundance quantification in wastewater: a benchmark study for the identification of optimal reference set design Author Nika, Ioanna (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Baaijens, J.A. (mentor) Hildebrandt, K.A. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2022-01-28 Abstract Lineage abundance estimation of SARS-CoV-2 in wastewater is a technique that aims to monitor the lineage prevalence in communities and help contain the COVID-19 pandemic. Lineages are collections of closely related mutants of a virus. It is suggested that the genome sequences of lineages differ across the globe due to random mutations or distinct immune responses of populations that mutate the virus. In order to estimate the lineage abundance in a specific community, wastewater data collected from the community are compared to reference SARS-CoV-2 genome sequences of different lineages. However, such region-related variation in the genome sequences of lineages could impact the abundance estimates. The main aim of this study is to identify an optimal way of sourcing reference genome sequences such that the lineage abundance estimates are improved. For the purpose of evaluating the performance of different reference sets, simulated wastewater data are used. We demonstrate that continent-specific reference sets are the most reliable option. The overall country interactions with other parts of the world could be considered for constructing an optimal reference set. Additionally, results show that considering immune-response related mutations for the reference set construction does not influence performance. Finally, it is suggested that a higher number of sequences per lineage and the inclusion of recently sourced sequences in the reference set improve results. Subject sars-cov-2wastewaterlineage abundance predictionRegion-based reference set designCovid-19 pandemickallistobenchmark study To reference this document use: http://resolver.tudelft.nl/uuid:c548336f-1698-47b8-9560-e40fac9397e8 Part of collection Student theses Document type bachelor thesis Rights © 2022 Ioanna Nika Files PDF research_project_with_fro ... _final.pdf 606.23 KB Close viewer /islandora/object/uuid:c548336f-1698-47b8-9560-e40fac9397e8/datastream/OBJ/view