Package index
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View_diffNetworks() - Interactive visualisation of differential networks
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calc_pvalues_network() - Calculate the p values for specific category network samples
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calc_pvalues_percentile() - Compute interaction p values for a single percentile value
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cat_parallel() - cat_parallel (from nestedcv)
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.predict_multiDEGGs() - Predict method for multiDEGGs_filter objects
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get_diffNetworks() - Generate multi-omic differential networks
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get_diffNetworks_singleOmic() - Generate differential networks for single omic analysis
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get_multiOmics_diffNetworks() - Get a table of all significant interactions across categories
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get_sig_deggs() - Get a table of all the significant interactions across categories
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multiDEGGs_combined_filter() - Combined multiDEGGs filter
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multiDEGGs_filter() - multiDEGGs_filter
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my_palette() - Internal function for colors
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node_boxplot() - Boxplots of single nodes (genes,proteins, etc.)
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plot_regressions() - Plot differential regressions for a link
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predict(<multiDEGGs_filter>) - Wrapper of .predict_multiDEGGs for multiDEGGs_filter()
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predict(<multiDEGGs_filter_combined>) - Wrapper of .predict_multiDEGGs for multiDEGGs_filter_combined()
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synthetic_OlinkData - Synthetic RNA-seq count data
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synthetic_metadata - Synthetic clinical data
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synthetic_proteomicData - Synthetic RNA-seq count data
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synthetic_rnaseqData - Synthetic RNA-seq count data
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tidy_metadata() - Tidying up of metadata. Samples belonging to undesidered categories (if specified) will be removed as well as categories with less than five samples, and NAs.