Continuous Embeddings of DNA Sequencing Reads and Application to Metagenomics | Zendy

Romain Menegaux | Zendy; JeanPhilippe Vert | Zendy

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Continuous Embeddings of DNA Sequencing Reads and Application to Metagenomics

Author(s) -

Romain Menegaux,

JeanPhilippe Vert

Publication year - 2019

Publication title -

journal of computational biology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.585

H-Index - 95

eISSN - 1557-8666

pISSN - 1066-5277

DOI - 10.1089/cmb.2018.0174

Subject(s) - metagenomics , dna sequencing , scalability , computer science , computational biology , k mer , dna , biology , artificial intelligence , genetics , gene , database

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 k -mers it contains. We show on metagenomics benchmarks that it outperforms the state-of-the-art methods in terms of accuracy and scalability.

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