Continuous Embeddings of DNA Sequencing Reads and Application to Metagenomics.
Identifieur interne : 000639 ( PubMed/Curation ); précédent : 000638; suivant : 000640Continuous Embeddings of DNA Sequencing Reads and Application to Metagenomics.
Auteurs : Romain Menegaux [France] ; Jean-Philippe Vert [France]Source :
- Journal of computational biology : a journal of computational molecular cell biology [ 1557-8666 ] ; 2019.
Abstract
We propose a new model for fast classification of DNA sequences output by next-generation sequencing machines. The model, which we call fastDNA, embeds DNA sequences in a vector space by learning continuous low-dimensional representations of thek-mers it contains. We show on metagenomics benchmarks that it outperforms the state-of-the-art methods in terms of accuracy and scalability.
DOI: 10.1089/cmb.2018.0174
PubMed: 30785347
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<front><div type="abstract" xml:lang="en"><b>We propose a new model for fast classification of DNA sequences output by next-generation sequencing machines. The model, which we call fastDNA, embeds DNA sequences in a vector space by learning continuous low-dimensional representations of the</b>
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