License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.GCB.2013.1
URN: urn:nbn:de:0030-drops-42380
Go to the corresponding OASIcs Volume Portal

AƟhauer, Kathrin Petra ; Meinicke, Peter

On the estimation of metabolic profiles in metagenomics

p001-asshauer.pdf (0.7 MB)


Metagenomics enables the characterization of the specific metabolic potential of a microbial community. The common approach towards a quantitative representation of this potential is to count the number of metagenomic sequence fragments that can be assigned to metabolic pathways by means of predicted gene functions. The resulting pathway abundances make up the metabolic profile of the metagenome and several different schemes for computing these profiles have been used. So far, none of the existing approaches actually estimates the proportion of sequences that can be assigned to a particular pathway. In most publications of metagenomic studies, the utilized abundance scores lack a clear statistical meaning and usually cannot be compared across different studies.
Here, we introduce a mixture model-based approach to the estimation of pathway abundances that provides a basis for statistical interpretation and fast computation of metabolic profiles. Using the KEGG database our results on a large-scale analysis of data from the Human Microbiome Project show a good representation of metabolic differences between different body sites. Further, the results indicate that our mixture model even provides a better representation than the dedicated HUMAnN tool which has been developed for metabolic analysis of human microbiome data.

BibTeX - Entry

  author =	{Kathrin Petra A{\ss}hauer and Peter Meinicke},
  title =	{{On the estimation of metabolic profiles in metagenomics}},
  booktitle =	{German Conference on Bioinformatics 2013},
  pages =	{1--13},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-59-0},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{34},
  editor =	{Tim Bei{\ss}barth and Martin Kollmar and Andreas Leha and Burkhard Morgenstern and Anne-Kathrin Schultz and Stephan Waack and Edgar Wingender},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-42380},
  doi =		{10.4230/OASIcs.GCB.2013.1},
  annote =	{Keywords: metagenomics, metabolic profiling, taxonomic profiling, abundance estimation, mixture modeling}

Keywords: metagenomics, metabolic profiling, taxonomic profiling, abundance estimation, mixture modeling
Collection: German Conference on Bioinformatics 2013
Issue Date: 2013
Date of publication: 09.09.2013

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI