wastewaterSPAdes: SARS-CoV-2 strain deconvolution using SPAdes toolkit

Abstract

MotivationSARS-CoV-2 wastewater samples are extensively collected and studied because it allows quantitatively assess a viral load in surrounding populations. Additionally, SARS-CoV-2 strain deconvolution gives more insights into pandemic dynamics, and the uprising of new strains. Usually, the solution to the strain deconvolution problem starts with read alignment of wastewater short read sequencing data to the SARS-CoV-2 reference genome. After variants are called and their abundances are estimated, a reference database is used to assign variants to strains, select a subset of strains, and infer relative abundance of these strains based on some mathematical model. Assembly-based methods have its own strengths, but currently reside in the shadow of alignment-based methods. ResultsIn this paper we propose a new assembly-based approach based on SPAdes toolkit codebase --- wastewaterSPAdes, that is able to deconvolve wastewater without a need of read alignment. Our results show that watewaterSPAdes is able to accurately identify strains presented in a sample, and correctly estimate abundances for most of the samples. Availabilityhttps://cab.spbu.ru/software/wastewaterspades/ Contacta.korobeynikov@spbu.ru Supplementary informationSupplementary data are available at Bioinformatics