A big data approach to metagenomics for all-food-sequencing

A big data approach to metagenomics for all-food-sequencing

Abstract Background All-Food-Sequencing (AFS) is an untargeted metagenomic sequencing method that allows for the detection and quantification of food ingredients including animals, plants, and microbiota. While this approach avoids some of the shortcomings of targeted PCR-based methods, it requires...

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Bibliographic Details
Main Authors: Robin Kobus, José M. Abuín, André Müller, Sören Lukas Hellmann, Juan C. Pichel, Tomás F. Pena, Andreas Hildebrandt, Thomas Hankeln, Bertil Schmidt
Format: Article
Language:English
Published: BMC 2020-03-01
Series:BMC Bioinformatics
Subjects:
Next-generation sequencing
Metagenomics
Species identification
Eukaryotic genomes
Locality sensitive hashing
Big data
Online Access:http://link.springer.com/article/10.1186/s12859-020-3429-6

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http://link.springer.com/article/10.1186/s12859-020-3429-6

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