Integrated Exposure-Omics Analysis Powered by Tidy Principles

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Documentation for package ‘tidyexposomics’ version 0.99.12

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

build_ont_annot_app	Build the Ontology Annotation Shiny app
create_exposomicset	Create an Exposomicset Object
download_dataset	Download and cache a tidyexposomics dataset
extract_omics_exposure_df	Extract Merged Omics and Exposure Data Frame
extract_results	Extract Results from 'MultiAssayExperiment' Metadata
extract_results_excel	Export tidyexposomics Results to Excel
extract_top_factor_features	Extract Top Contributing Features for Factors
filter_missing	Filter Features and Variables with High Missingness
filter_non_normal	Filter Non-Normal Exposure Variables
filter_omics	Filter low-quality features in omics assays
filter_sample_outliers	Filter Sample Outliers
load_annotation_data	Load Ontology Data
make_example_data	Generate Example Data for Testing
pivot_exp	Pivot a selected omics dataset from a MultiAssayExperiment into tidybulk format
pivot_feature	Extract Feature Metadata from a MultiAssayExperiment
pivot_sample	Extract Sample Metadata from MultiAssayExperiment or SummarizedExperiment
plot_association	Plot Association Results (Unified Forest Plot)
plot_circos_correlation	Plot Circular Network of Exposure Relationships
plot_correlation_summary	Plot Correlation Summary from Exposure-Feature Correlations
plot_correlation_tile	Plot Correlation Tilemap
plot_enrichment	Plot Enrichment Results from exposomicset
plot_exposures	Plot Exposure Distributions by Category or Group
plot_exposure_impact	Plot Exposure Impact on Network Centrality Metrics
plot_factor_summary	Plot Summary of Factor Contributions from Multi-Omics Integration
plot_manhattan	Plot a Manhattan-style ExWAS summary across omics categories
plot_missing	Plot Missing Data Across Exposure and Omic Layers
plot_network	Plot Network Graph of Features or Exposures
plot_normality_summary	Plot Normality Summary of Exposure Variables
plot_pca	Plot PCA Results for Features and Samples
plot_sample_clusters	Plot Sample Clusters
plot_sensitivity_summary	Plot Sensitivity Analysis Summary
plot_top_factor_features	Plot Top Features by Factor from Integration Results
plot_volcano	Volcano Plot of Differential Abundance
run_association	Run Association Analysis
run_cluster_samples	Cluster Samples Based on Exposure Data
run_correlation	Run Correlation Analysis
run_create_network	Create Correlation Network from Feature Data
run_differential_abundance	Run Differential Abundance Analysis
run_enrichment	Perform enrichment analysis on selected features from a exposomicset object
run_exposome_score	Compute Composite Exposome Scores
run_exposure_impact	Calculate Exposure Impact from Feature-Exposure Correlation Networks
run_factor_overlap	Identify and Annotate Shared Top Features Across Integration Factors
run_impute_missing	Impute Missing Exposure and Omics Data in a MultiAssayExperiment
run_multiomics_integration	Run Multi-Omics Integration
run_normality_check	Assess Normality of Exposure Variables
run_pca	Perform Principal Component Analysis (PCA)
run_pipeline_summary	Summarize and Visualize Analysis Pipeline Steps
run_sensitivity_analysis	Run Sensitivity Analysis for Differential Abundance
run_summarize_exposures	Summarize Exposure Variables
tidyexposomics_example	Example exposome multi-omics dataset
transform_exposure	Transform Exposure Variables for Normality