Meta anlaytical health and disease of coral microbiome.xls (204 kB)
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454 data used in the paper 'On the importance of the microbiome and pathobiome in coral health and disease'

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modified on 09.01.2017, 18:05

Examples of visualisations of microbial networks associated with Acorpora muricata collected at four different locations (Australia, Fiji, Maldives and Solomon Islands). Networks with vertices representing individual OTUs, and edges representing absolute values of correlation coefficients of greater than 0.6, were derived from OTU abundances in a) healthy corals and b) diseased corals.  Edges shown in green show positive correlations, whereas those shown in red represent negative correlations.  Networks were derived using the qgraph function in the qgraph package (Epskamp et al., 2012).  c) shows the network derived from the healthy coral arranged according to a community clustering algorithm (fastgreedy.community from the igraph package; (Csardi and Nepusz, 2006)).  The algorithm tries to identify clusters of OTUs which show similar patterns of abundance across samples. d) Shows the relationship between the cut-off correlation value (x-axis) determining which of the correlations between OTU abundances should be included and the proportion of all the pair wise edges included in the network. All network analysis was done using the R statistical programming language (R Core Team, 2016).  Methods: Acropora muricata samples were collected and preserved in 100% molecular grade ethanol (Sweet and Séré, 2016). All samples were extracted using the Qiagen DNeasy Extraction kit, amplified with primers 357 and 518 and sequenced on the 454 platform. All samples were pooled on the same run with barcodes for a complete list of methods including downstream processing of the sequencing run please refer to Sweet and Bythell, (2015).