Estimating Viral Haplotypes in a Population Using k-mer Counting
Identifieur interne : 002148 ( Main/Exploration ); précédent : 002147; suivant : 002149Estimating Viral Haplotypes in a Population Using k-mer Counting
Auteurs : Raunaq Malhotra [États-Unis] ; Shruthi Prabhakara [États-Unis] ; Mary Poss [États-Unis] ; Raj Acharya [États-Unis]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: Viral haplotype estimation in a population is an important problem in virology. Viruses undergo a high number of mutations and recombinations during replication for their survival in host cells and exist as a population of closely related genetic variants. Due to this, estimating the number of haplotypes and their relative frequencies in the population becomes a challenging task. The usage of a sequenced reference genome has its limitations due to the high mutational rates in viruses. We propose a method for estimating viral haplotypes based only on the counts of k-mers present in the viral population without using the reference genome. We compute k-mer pairs that are related to each other by one mutation, and compute a minimal set of viral haplotypes that explain the whole population based on these k-mer pairs. We compare our method to the software ShoRAH (which uses a reference genome) on simulated dataset and obtained comparable results, even without using a reference genome.
Url:
DOI: 10.1007/978-3-642-39159-0_24
Affiliations:
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