To the top

Page Manager: Webmaster
Last update: 9/11/2012 3:13 PM

Tell a friend about this page
Print version

HirBin: high-resolution i… - University of Gothenburg, Sweden Till startsida
Sitemap
To content Read more about how we use cookies on gu.se

HirBin: high-resolution identification of differentially abundant functions in metagenomes

Journal article
Authors Tobias Österlund
Viktor Jonsson
Erik Kristiansson
Published in BMC Genomics
Volume 18
ISSN 1471-2164
Publication year 2017
Published at Department of Mathematical Sciences
Language en
Links dx.doi.org/10.1186/s12864-017-3686-...
Keywords Metagenomics, Next-generation sequencing, Functional annotation, Binning, TIGRFAM, Differential abundance, Statistical analysis, human gut microbiome, generation sequencing data, alignment, database, catalog, pathway, genes, blast, Biotechnology & Applied Microbiology, Genetics & Heredity
Subject categories Mathematics

Abstract

Background: Gene-centric analysis of metagenomics data provides information about the biochemical functions present in a microbiome under a certain condition. The ability to identify significant differences in functions between metagenomes is dependent on accurate classification and quantification of the sequence reads (binning). However, biological effects acting on specific functions may be overlooked if the classes are too general. Methods: Here we introduce High-Resolution Binning (HirBin), a new method for gene-centric analysis of metagenomes. HirBin combines supervised annotation with unsupervised clustering to bin sequence reads at a higher resolution. The supervised annotation is performed by matching sequence fragments to genes using well-established protein domains, such as TIGRFAM, PFAM or COGs, followed by unsupervised clustering where each functional domain is further divided into sub-bins based on sequence similarity. Finally, differential abundance of the sub-bins is statistically assessed. Results: We show that HirBin is able to identify biological effects that are only present at more specific functional levels. Furthermore we show that changes affecting more specific functional levels are often diluted at the more general level and therefore overlooked when analyzed using standard binning approaches. Conclusions: HirBin improves the resolution of the gene-centric analysis of metagenomes and facilitates the biological interpretation of the results.

Page Manager: Webmaster|Last update: 9/11/2012
Share:

The University of Gothenburg uses cookies to provide you with the best possible user experience. By continuing on this website, you approve of our use of cookies.  What are cookies?