GigaScienceBioinformaticsPeer-reviewed journal article
Impact of reference design on estimating SARS-CoV-2 lineage abundances from wastewater sequencing data
Eva AßmanniD, Shelesh AgrawaliD, Laura OrschleriD, Sindy BöttcheriD, Susanne LackneriD, Martin HölzeriD
Abstract
BackgroundSequencing of SARS-CoV-2 RNA from wastewater samples has emerged as a valuable tool for detecting the presence and relative abundances of SARS-CoV-2 variants in a community. By analyzing the viral genetic material present in wastewater, public health officials can gain early insights into the spread of the virus and inform timely intervention measures. The construction of reference datasets from known SARS-CoV-2 lineages and their mutation profies has become state-of-the-art for assigning viral lineages and their relative abundances from wastewater sequencing data. However, the selection of reference sequences or mutations directly affects the predictive power. ResultsHere, we show the impact of a mutation- and sequence-based reference reconstruction for SARS-CoV-2 abundance estimation. We benchmark three data sets: 1) synthetic "spike-in" mixtures, 2) German samples from early 2021, mainly comprising Alpha, and 3) samples obtained from wastewater at an international airport in Germany from the end of 2021, including 1rst signals of Omicron. The two approaches differ in sub-lineage detection, with the marker-mutation-based method, in particular, being challenged by the increasing number of mutations and lineages. However, the estimations of both approaches depend on selecting representative references and optimized parameter settings. By performing parameter escalation experiments, we demonstrate the effects of reference size and alternative allele frequency cutoffs for abundance estimation. We show how different parameter settings can lead to different results for our test data sets, and illustrate the effects of virus lineage composition of wastewater samples and references. ConclusionsHere, we compare a mutation- and sequence-based reference construction and assignment for SARS-CoV-2 abundance estimation from wastewater samples. Our study highlights current computational challenges, focusing on the general reference design, which significantly and directly impacts abundance allocations. We illustrate advantages and disadvantages that may be relevant for further developments in the wastewater community and in the context of higher standardization.
- assay: whole-genome sequencing
- research focus: differential expression
- research focus: benchmarking
- research focus: variant calling
- research focus: variant effect prediction
- approach: statistical model
- approach: benchmark study
- Citations
- 12
- FWCI
- 4.13
- Field percentile
- top 5%
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