The correlation between exposures, in terms of intra-family and inter-family exposures, is interesting to take into account. The correlation of the exposome can be computed using ds.correlation
. The correlation could be disclosive, for that reason there's the argument fam
to select the families to compute the correlation subsetting the exposome dataset by families, typical complete exposome datasets will fail as the correlation matrix could be disclosive.
ds.exposome_correlation("exposome_object")[[1]][[1]]$`Correlation Matrix`[1:5,1:5]
When subsetting the exposome set by families the correlation succeeds.
ds.exposome_correlation("exposome_object", c("Metals", "Noise"))[[1]][[1]]$`Correlation Matrix`[1:5,1:5]
The output from the ds.correlation
consists of the correlation matrix and a vector that contains the names of exposures and families on the correlation table, this second item is used by the corPlot
function to display the results of the correlation study.
corr_data <- ds.exposome_correlation("exposome_object", c("Metals", "Noise")) corPlot(corr_data)
The best option to see the inter-family correlations is the circos of correlations while the matrix of correlations is a better way for studying the intra-family correlations.
corPlot(corr_data, type = "circos")
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