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Sequence Classification using Reference Taxonomies

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If you have a question about this talk, please contact Mustapha Amrani.


Next generation sequencing technologies have opened up an unprecedented opportunity for microbiology by enabling the culture-independent genetic study of complex microbial communities, which were so far largely unknown. The analysis of metagenomic data is challenging, since a sample may contain a mixture of many different microbial species, whose genome has not necessarily been sequenced beforehand. In this talk, we address the problem of analyzing metagenomic data for which databases of reference sequences are already known. We discuss both composition and alignment-based methods for the classification of sequence reads, and present recent results on the assignment of ambiguous reads to microbial species at the best possible taxonomic rank.

This talk is part of the Isaac Newton Institute Seminar Series series.

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