Correlation between metabolite significance, module membership and maximum adjacency ratio for modules of weighted network analysis.

<p>Correlation between metabolite significance, module membership and maximum adjacency ratio for modules of weighted network analysis.</p

Accuracy parameters and number of metabolites with significant variable importance (VI) and maximal VI per trait according to random forest regression.

<p>Accuracy parameters and number of metabolites with significant variable importance (VI) and maximal VI per trait according to random forest regression.</p

Descriptive statistics and phenotypic correlations between meat quality traits.

<p>Descriptive statistics and phenotypic correlations between meat quality traits.</p

Selection of metabolites for joint analysis based on their ranking in top 30 metabolites in correlation analysis, metabolite significance of weighted network analysis and variable importance of random forest regression.

<p>Selection of metabolites for joint analysis based on their ranking in top 30 metabolites in correlation analysis, metabolite significance of weighted network analysis and variable importance of random forest regression.</p

Venn-diagram of significant correlated metabolites.

<p>Drip loss measured in <i>Musculus longissimus dorsi</i> (LD) 24 h post-mortem (p.m.); pH1 measured in LD 45 minutes p.m.; pH24 measured in LD 24 h p.m.; color = meat color measured in LD 24 h p.m.</p

Correlation coefficients and corresponding p-values of module-trait relationship.

<p>Correlations of traits drip loss, pH1, pH24 and meat color to modules are characterized by color range from red (‘1’—positive correlation) to green (‘-1’—negative correlation). In parenthesis below correlation coefficients the p-value is given. Drip loss is measured in <i>Musculus longissimus dorsi</i> (LD) 24 h post-mortem (p.m.); pH1 measured in LD 45 minutes p.m.; pH24 measured in LD 24 h p.m.; meat color measured in LD 24 h p.m.; ME = module eigenvalues.</p

Cumulative proportion of explained variance by principal component one to 10.

<p>PC = principal component.</p

Variable importance boxplot of important metabolites by random forest regression of Strobl et al. (2009) [29].

<p>Drip loss measured in <i>Musculus longissimus dorsi</i> (LD) 24 h post-mortem (p.m.); pH1 measured in LD 45 minutes p.m.; pH24 measured in LD 24 h p.m.; color = meat color measured in LD 24 h p.m.</p

Selection of significant modules for meat quality traits in weighted network analysis.

<p>Selection of significant modules for meat quality traits in weighted network analysis.</p

Predictive power of principal component analysis, weighted network analysis and random forest regression in drip loss, pH1, pH24 and meat color based on a multiple regression model.

<p>Predictive power of principal component analysis, weighted network analysis and random forest regression in drip loss, pH1, pH24 and meat color based on a multiple regression model.</p