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Sökning: onr:"swepub:oai:DiVA.org:oru-69996" > A computational fra...

A computational framework to integrate high-throughput '-omics' datasets for the identification of potential mechanistic links

Pedersen, Helle Krogh (författare)
The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
Forslund, Sofia K. (författare)
Experimental and Clinical Research Centre, a joint center of Max Delbrück Centre for Molecular Medicine & Charité University Hospital, Berlin, Germany; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
Gudmundsdottir, Valborg (författare)
Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark
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Østergaard Petersen, Anders (författare)
Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark
Hildebrand, Falk (författare)
Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
Hyötyläinen, Tuulia, 1971- (författare)
Örebro universitet,Institutionen för naturvetenskap och teknik,MTM Research Centre
Nielsen, Trine (författare)
The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
Hansen, Torben (författare)
The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
Bork, Peer (författare)
Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
Ehrlich, S. Dusko (författare)
MetaGénoPolis (MGP), INRA, Université Paris-Saclay, Jouy-en-Josas, France; Centre for Host-Microbiome Interactions, Dental Institute Central Office, Guy’s Hospital, King’s College London, London, UK
Brunak, Søren (författare)
Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark; Novo Nordisk Foundation Center for Protein Research, Disease Systems Biology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
Oresic, Matej, 1967- (författare)
Örebro universitet,Institutionen för medicinska vetenskaper,Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
Pedersen, Oluf (författare)
The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
Nielsen, Henrik Bjørn (författare)
Clinical Microbiomics A/S, Copenhagen, Denmark
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 (creator_code:org_t)
2018-10-31
2018
Engelska.
Ingår i: Nature Protocols. - : Nature Publishing Group. - 1754-2189 .- 1750-2799. ; 13:12, s. 2781-2800
Relaterad länk:
https://urn.kb.se/re...
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https://doi.org/10.1...
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  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • We recently presented a three-pronged association study that integrated human intestinal microbiome data derived from shotgun-based sequencing with untargeted serum metabolome data and measures of host physiology. Metabolome and microbiome data are high dimensional, posing a major challenge for data integration. Here, we present a step-by-step computational protocol that details and discusses the dimensionality-reduction techniques used and methods for subsequent integration and interpretation of such heterogeneous types of data. Dimensionality reduction was achieved through a combination of data normalization approaches, binning of co-abundant genes and metabolites, and integration of prior biological knowledge. The use of prior knowledge to overcome functional redundancy across microbiome species is one central advance of our method over available alternative approaches. Applying this framework, other investigators can integrate various '-omics' readouts with variables of host physiology or any other phenotype of interest (e.g., connecting host and microbiome readouts to disease severity or treatment outcome in a clinical cohort) in a three-pronged association analysis to identify potential mechanistic links to be tested in experimental settings. Although we originally developed the framework for a human metabolome-microbiome study, it is generalizable to other organisms and environmental metagenomes, as well as to studies including other -omics domains such as transcriptomics and proteomics. The provided R code runs in ~1 h on a standard PC.

Ämnesord

NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Medicinsk bioteknologi -- Medicinsk bioteknologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Medical Biotechnology -- Medical Biotechnology (hsv//eng)

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