DISSEQT-DIStribution-based modeling of SEQuence space Time dynamics

Virus Evolution
Rasmus HenningssonMagnus Fontes

Abstract

Rapidly evolving microbes are a challenge to model because of the volatile, complex, and dynamic nature of their populations. We developed the DISSEQT pipeline (DIStribution-based SEQuence space Time dynamics) for analyzing, visualizing, and predicting the evolution of heterogeneous biological populations in multidimensional genetic space, suited for population-based modeling of deep sequencing and high-throughput data. The pipeline is openly available on GitHub (https://github.com/rasmushenningsson/DISSEQT.jl, accessed 23 June 2019) and Synapse (https://www.synapse.org/#!Synapse: syn11425758, accessed 23 June 2019), covering the entire workflow from read alignment to visualization of results. Our pipeline is centered around robust dimension and model reduction algorithms for analysis of genotypic data with additional capabilities for including phenotypic features to explore dynamic genotype-phenotype maps. We illustrate its utility and capacity with examples from evolving RNA virus populations, which present one of the highest degrees of genetic heterogeneity within a given population found in nature. Using our pipeline, we empirically reconstruct the evolutionary trajectories of evolving populations in sequence space and geno...Continue Reading

References

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Citations

Oct 31, 2020·Journal of Clinical Medicine·Carlos García-CrespoEsteban Domingo
Jun 9, 2021·Nature Communications·Simeon D CastleThomas E Gorochowski
Sep 30, 2021·Annual Review of Virology·Esteban DomingoCelia Perales

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Methods Mentioned

BETA
single-cell sequencing
MDS
chromosomal aberrations

Software Mentioned

Synapse
MEM
SMSSVD
ShoRAH
Isomap
Phaser
Docker
SynSyn
Talus Plot
Consensus

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