Decontaminating eukaryotic genome assemblies with machine learning

Decontaminating eukaryotic genome assemblies with machine learning

Abstract Background High-throughput sequencing has made it theoretically possible to obtain high-quality de novo assembled genome sequences but in practice DNA extracts are often contaminated with sequences from other organisms. Currently, there are few existing methods for rigorously decontaminatin...

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Bibliographic Details
Main Authors: Janna L. Fierst, Duncan A. Murdock
Format: Article
Language:English
Published: BMC 2017-12-01
Series:BMC Bioinformatics
Subjects:
DNA sequencing
High-throughput
Genome assembly
Contamination
Sequence filtering
Online Access:http://link.springer.com/article/10.1186/s12859-017-1941-0

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http://link.springer.com/article/10.1186/s12859-017-1941-0

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