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Peschel, S. ; Müller, C.L. ; von Mutius, E. ; Boulesteix, A.L.* ; Depner, M.

NetCoMi: Network construction and comparison for microbiome data in R.

Brief. Bioinform. 22, DOI: 10.1093/bib/bbaa290 (2021)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
MOTIVATION: Estimating microbial association networks from high-throughput sequencing data is a common exploratory data analysis approach aiming at understanding the complex interplay of microbial communities in their natural habitat. Statistical network estimation workflows comprise several analysis steps, including methods for zero handling, data normalization and computing microbial associations. Since microbial interactions are likely to change between conditions, e.g. between healthy individuals and patients, identifying network differences between groups is often an integral secondary analysis step. Thus far, however, no unifying computational tool is available that facilitates the whole analysis workflow of constructing, analysing and comparing microbial association networks from high-throughput sequencing data. RESULTS: Here, we introduce NetCoMi (Network Construction and comparison for Microbiome data), an R package that integrates existing methods for each analysis step in a single reproducible computational workflow. The package offers functionality for constructing and analysing single microbial association networks as well as quantifying network differences. This enables insights into whether single taxa, groups of taxa or the overall network structure change between groups. NetCoMi also contains functionality for constructing differential networks, thus allowing to assess whether single pairs of taxa are differentially associated between two groups. Furthermore, NetCoMi facilitates the construction and analysis of dissimilarity networks of microbiome samples, enabling a high-level graphical summary of the heterogeneity of an entire microbiome sample collection. We illustrate NetCoMi's wide applicability using data sets from the GABRIELA study to compare microbial associations in settled dust from children's rooms between samples from two study centers (Ulm and Munich). AVAILABILITY: R scripts used for producing the examples shown in this manuscript are provided as supplementary data. The NetCoMi package, together with a tutorial, is available at https://github.com/stefpeschel/NetCoMi. CONTACT: Tel:+49 89 3187 43258; stefanie.peschel@mail.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Compositional Data ; Differential Association ; Microbial Association Estimation ; Network Analysis ; Network Comparison ; Sample Similarity Network; Compositional Data; Metagenomic Data; Social Networks; Centrality; Inference; Modularity; Criteria; Package; Design; Models
Sprache englisch
Veröffentlichungsjahr 2021
Prepublished im Jahr 2020
HGF-Berichtsjahr 2020
ISSN (print) / ISBN 1467-5463
e-ISSN 1477-4054
Zeitschrift Briefings in Bioinformatics
Quellenangaben Band: 22, Heft: 4 Seiten: , Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Verlagsort Great Clarendon St, Oxford Ox2 6dp, England
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Asthma and Allergy Prevention (IAP)
Institute of Computational Biology (ICB)
POF Topic(s) 30202 - Environmental Health
30205 - Bioengineering and Digital Health
Forschungsfeld(er) Allergy
Enabling and Novel Technologies
PSP-Element(e) G-503300-001
G-503800-001
Förderungen European Research Council
European Commission
DOI 10.1093/bib/bbaa290
WOS ID WOS:000709466800060
PubMed ID 33264391
Erfassungsdatum 2020-12-16
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