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ViVaMBC: estimating viral sequence variation in complex populations from illumina deep-sequencing data using model-based clustering

Bie Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
2015 BMC Bioinformatics  
Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations.  ...  A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second best base calls for identifying and quantifying viral variants.  ...  We are gratefull to Tobias Verbeke from OpenAnalytics who provided the IT infrastructure.  ... 
doi:10.1186/s12859-015-0458-7 pmid:25887734 pmcid:PMC4369097 fatcat:cf22jgf2ejfdzflyzylbg7qopu

Recent advances in inferring viral diversity from high-throughput sequencing data

Susana Posada-Cespedes, David Seifert, Niko Beerenwinkel
2017 Virus Research  
However, analysis of HTS data from virus populations is challenging due to short, error-prone reads.  ...  Advances in high-throughput sequencing (HTS) technologies have facilitated the assessment of the genetic diversity of such virus populations at an unprecedented level of detail.  ...  Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.virusres.2016.09. 016.  ... 
doi:10.1016/j.virusres.2016.09.016 pmid:27693290 fatcat:mgjzhmio5fhhzpedajjfsskmnu