Additional file 6 - dataset and scripts for correlations microbiota-metabolome

Correlation analyses between microbiota and metabolome data were conducted using Python. Only metabolites within the quantification range for each sample and bacterial genera with an average abundance above 0.05% were included in the analyses. The Shapiro-Wilk test was used to assess the normality of the metabolite and bacterial genera distributions. For pairs where both variables followed a normal distribution, Pearson's correlation coefficient was employed. Otherwise, Spearman's correlation was used. To account for the risk of false positives associated with multiple comparisons, the Benjamini-Hochberg correction was applied. A global analysis was first performed across all samples, considering all metabolites and bacterial genera, followed by a targeted analysis focusing on the metabolites and bacterial genera that showed significant differences between IUGR and NORM pigs.