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Author
Date
2019-06-28Type
- Master Thesis
ETH Bibliography
yes
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Abstract
Migration dynamics of viral sub-populations are usually analysed by applying the
structured coalescent theory to genetic sequence data. This is, however, not trivial
for reassorting viruses that have segmented genomes. Recently, a coalescent
with reassortment approach was developed, allowing to use the full segmented
genome for phylodynamic analysis. We combine the two techniques into the
structured coalescent with reassortment model for exact and approximate inference.
We show that this method can accurately estimate sub-population dependent
effective populations sizes, reassortment and migration rates. Additionally,
we apply the new model on a seasonal influenza A/H3N2 dataset with 150 genomic
sequences for four viral segments, sampled at three distinct locations. We
contrast our results with a structured coalescent without reassortment inference
conducted using genetic sequences of one out of four segments. This revealed that
taking into account segment reassortment and using sequencing data from several
viral segments for joint phylodynamic inference leads to different estimates for
effective population sizes, migration and evolutionary rates, and the height of a
segment tree root node.
The discussed model is implemented as Structured COalescent with REassortment
(SCORE) package for BEAST 2 and its source code available at
https://github.com/jugne/SCORE. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000475112Publication status
publishedPublisher
ETH ZurichSubject
influenza; structured coalescent; reassortmentOrganisational unit
09490 - Stadler, Tanja / Stadler, Tanja
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ETH Bibliography
yes
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