Time-course Differential Expression analysis of omics data

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Documentation for package ‘TiDEomics’ version 0.99.4

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

Help Pages

calc_feature_property	Calculate feature property
calc_mean_sd	Calculate mean and SD
create_input	Create object
decomp_variance	Variance decomposition
DE_between_group	DE between groups
DE_between_time	DE between time points
enrichGO_list	GO enrichment with gene sets
enrichGO_rank	GO enrichment with ranked gene list
enrichR_list	Gene-set enrichment via enrichR
enrich_msigdb	Gene set enrichment via MSigDB
example_go	'enrichGO_list()' output object for runnable examples
example_net	'run_WGCNA()' output object for runnable examples
example_obj	SummarizedExperiment object for runnable examples
example_res_list	'run_Trendy' output object for runnable examples
extract_hubs	Extract hub features from WGCNA modules
extract_segment_trends	Extract feature trends
flatten_DE	Flatten nested differential expression results
flatten_enrich	Flatten nested enrichment results
get_custom_palette	Get custom color palette
group_specific_features	Group specific features
impute_groups	Impute missing values
merge_groups	Merge groups into one object
merge_replicates	Merge replicates
normalise_to_start	Normalise to starting time point
plot_breakpoints	Plot breakpoint distribution
plot_cor_matrix	Plot correlation matrix
plot_cv	Plot coefficient of variation (CV)
plot_DE_between_group	DE number between groups
plot_DE_between_time	DE number between time points
plot_distribution	Abundance distribution plot
plot_GO	Plot GO enrichment
plot_ID	Plot number of identified features
plot_missing	Plot missing rate
plot_modules_h	Plot modules (horizontal layout)
plot_modules_v	Plot modules (vertical layout)
plot_pca	Plot PCA
plot_pca_3D	Plot PCA in 3D
plot_pca_arrows	Plot PCA with arrows
plot_pca_by_group	Plot PCA by group
plot_segments	Plot segmented regression
plot_trend	Plot feature abundance over time
plot_umap	Plot UMAP
plot_umap_by_group	Plot UMAP by group
plot_variance	Plot variance decomposition
plot_volcano	Volcano plot of DE results
plot_WGCNA	Plot WGCNA results
prepare_tide	Prepare TiDEomics input
prepare_WGCNA	Prepare data and choose power for WGCNA
run_Trendy	Segmented regression analysis
run_WGCNA	Weighted gene co-expression network analysis
set_custom_palette	Set custom color palette
split_groups	Split groups
summarise_feature_property	Summarise feature properties
summarise_module_metrics	Summarise WGCNA module metrics
summarise_module_pattern	Summarise module patterns
summarise_Trendy	Summarise Trendy results
theme_custom	Custom ggplot2 theme
tutorial_data	Dataset for TiDEomics tutorial, expression matrix
tutorial_sample_info	Dataset for TiDEomics tutorial, sample information
WGCNA_module	Convert WGCNA output to feature-module data frame