Function reference • Omix

Pre-processing functions
`batch_correction_protein()`	Calling different proteomics correction methods. Internal to `process_protein()`
`combat_correction()`	Proteomics normalisation batch correction using Combat
`filter_protein()`	Data filtering function
`generate_multiassay()`	Generate a MultiAssayExperiment object from multiple single-omics data
`median_centering_correction()`	Proteomics normalisation batch correction using median centering method
`process_protein()`	Process bulk proteomics data
`process_rna()`	Process batch transcriptomics data
Single-omic analysis function
`DE_multiomics()`	Performs DE on the multimodal object from the processed slots
`protein_DE_analysis()`	Performs single omic analysis of proteomic layer.
`rna_DE_analysis()`	Performs single omic analysis of transcriptomics layer.
`single_omic_comparisons()`	Compare differential expressed genes and proteins
`spls_wrapper()`	Performs sparse partial least squares regression on processed slots (rna and protein)
`wgcna_wrapper()`	Performs WGCNA on processed slots (rna and protein)
Multi-omic integration function
`getClustNum()`	Get estimation of optimal clustering number
`integrate_with_DIABLO()`	Vertical integration with DIABLO including model tuning
`integrate_with_MBPLS()`	Vertical integration with MBPLS
`integrate_with_MEFISTO()`	Vertical integration with MEFISTO
`integrate_with_MOFA()`	Vertical integration with MOFA
`integrate_with_iCluster()`	Vertical integration with iCluster
`integrate_with_sMBPLS()`	Vertical integration with SMBPLS
`vertical_integration()`	Patient specific vertical integration
Multi-omic integration downstream analysis
`OpenTarget_dataframe()`	Interface to OpenTargets database
`Transcription_Factor_enrichment()`	Transcription factor target enrichment test
`Transcription_Factor_enrichment_supervised()`	Transcription factor target enrichment test
`circos_TF()`	Creates a circos plot of identified TF and gene targets in modules
`clustering_DE_analysis()`	Performs differential expression between clusters
`extract_loadings()`	Extract loadings
`extract_multiomic_signature()`	Extracts a multi-omics signature from loadings
`extract_weigths()`	Extract_weigths from MOFA model for a given factor of interest at a defined absolute threshold
`integrative_results_clustering()`	Downstream analysis for integrated multi-omics data - Clustering models
`integrative_results_sparse_supervised()`	Downstream analysis for integrated multi-omics data - Sparse Supervised models
`integrative_results_supervised()`	Downstream analysis for integrated multi-omics data
`integrative_results_unsupervised()`	Downstream analysis for integrated multi-omics data
`multiomics_modules()`	Compute the module eigen value (PC1 of scaled transcriptomics/proteomics expression) and correlates it to chosen covariates
`multiomics_network()`	Get multiomics networks from multiassay object
`multiomics_network_matrix()`	Get multiomics networks from multimodal object
`plot_module_trajectory()`	PLot scaled changes in modules eigenvalue alongside inferred_psuedotime
`posterior_probability()`	Retrieves posterior probabilities from iCluster integration
`pseudotime_inference()`	Pseudotime_inference based on integrated embeddings and clusters
`sign_signature()`	Extract sign
Pseudotime inference functions
Helper functions
`counts_rna()`	Adds custom processed dataset to multiassay object
`format_res_deseq()`	Formatting differential expression results from DESEQ2
`format_res_limma()`	Formatting differential expression results from limma
`get_background()`	Get background genes
`get_metadata()`	Get metadata
`processed_proteomics()`	Adds a custom processed proteomics dataset to multiassay object
`processed_rna()`	Adds a custom processed transcriptomics slot to multiassay object
Plotting functions
`circular_corrplot()`	Circular heatmap of module-trait correlations and module-cell type enrichments
`communities_network()`	Detects communities in multi-omics network
`community_graph()`	Creates a subnetwork graph based on detected communities
`correlation_heatmap()`	Correlation heatmap between Factors and covariates of interest
`correlation_heatmap_clusters()`	Correlation heatmap between Factors and covariates of interest
`correlation_heatmap_supervised()`	Correlation heatmap between Factors and covariates of interest
`getStdiz()`	Get standardized omics data
`interactive_network()`	Get interactive network from igraph object
`multiomics_heatmap()`	Multi-omics heatmap
`plot_OpenTarget()`	Plot Interface to OpenTargets database
`plot_communities()`	Plots multi-ommics network communities
`plot_components()`	Plot components
`plot_loadings()`	Plot loadings
`plot_optimal_cluster()`	plot_optimal_cluster
`visualise_pathway()`	visualise_pathway
`volcano_interactive()`	Builds an interactive volcano plot using plotly
`volcano_interactive_comparison()`	Builds an interactive comparison plot using plotly
`volcano_plot_deseq()`	Builds a volcano plot from DESEQ2 results
`volcano_plot_limma()`	Builds a volcano plot from limma results
Functional enrichment functions
`GSEA()`	Performs functional gene set enrichment analysis
`cell_type_enrichment()`	Cell type enrichment of communities
`enrichment_custom()`	Functional enrichment based on given reference annotations
`integrated_enrichment_mutliGSEA()`	Integrated pathway enrichment with multiGSEA
`pathway_analysis_enrichr()`	Functional enrichment analysis using enrichR
Generate report functions
`multi_omic_report()`	Generate a report for single omic analysis
`multi_omics_qc()`	Generate multi-omics QC results
`pathway_report()`	Generate a report for single omic analysis
`proteomics_report()`	Generate a report for single omic analysis
`qc_report()`	Generate a report for single omic analysis
`single_omic_report()`	Generate a report for single omic analysis

Reference

Pre-processing functions

Single-omic analysis function

Multi-omic integration function

Multi-omic integration downstream analysis

Pseudotime inference functions

Helper functions

Plotting functions

Functional enrichment functions

Generate report functions