Clustering metagenome contigs using coverage with CONCOCT

Clustering metagenome contigs using coverage with CONCOCT

Metagenomics allows studying genetic potentials of microorganisms without prior cultivation. Since metagenome assembly results in fragmented genomes, a key challenge is to cluster the genome fragments (contigs) into more or less complete genomes. The goal of this project was to investigate how well...

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Bibliographic Details
Main Author: Bjarnason, Brynjar Smári
Format: Others
Language:English
Published: KTH, Skolan för datavetenskap och kommunikation (CSC) 2017
Subjects:
metagenomics
coverage
composition
k-mer
clustering
mixture model
gaussian
dirichlet process
machine learning
Computer Sciences
Datavetenskap (datalogi)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208944

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208944

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