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ggpicrust2 vignettes

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install.packages('ggpicrust2')

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583

Version

2.5.10

License

MIT + file LICENSE

Issues

85

Pull Requests

3

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181

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26

Maintainer

Chen Yang

Last Published

February 12th, 2026

Functions in ggpicrust2 (2.5.10)

generate_nested_colors

Generate colors for nested grouping variables
get_available_themes

Get Available Color Themes
import_MicrobiomeAnalyst_daa_results

Import Differential Abundance Analysis (DAA) results from MicrobiomeAnalyst
.build_continuous_scale

Internal: build a continuous ggplot2 scale layer from colors or ggplot2 scale
ko_abundance

KO Abundance Dataset
kegg_abundance

KEGG Abundance Dataset
ko_reference

KEGG Orthology (KO) Reference Dataset
ggpicrust2

This function integrates pathway name/description annotations, ten of the most advanced differential abundance (DA) methods, and visualization of DA results.
gsea_pathway_annotation

Annotate GSEA results with pathway information
ko2kegg_abundance

Convert KO abundance in picrust2 export files to KEGG pathway abundance
get_color_theme

Get Color Theme
kegg_pathway_reference

KEGG Pathway Name Reference Dataset
pathway_daa

Differential Abundance Analysis for Predicted Functional Pathways
pathway_errorbar

The function pathway_errorbar() is used to visualize the results of functional pathway differential abundance analysis as error bar plots.
legend_annotation_utils

Legend and Annotation Utilities for ggpicrust2
pathway_annotation

Pathway information annotation
metacyc_abundance

MetaCyc Abundance Dataset
metacyc_reference

MetaCyc Pathway Reference Dataset
ko_to_kegg_reference

KO to KEGG Pathway Reference Data
metacyc_to_ec_reference

MetaCyc Pathway to EC Number Mapping Dataset
ko_to_go_reference

KO to GO Reference Mapping Dataset
metadata

Metadata for ggpicrust2 Demonstration
pathway_volcano

Volcano Plot for Pathway Differential Abundance Analysis
pathway_gsea

Gene Set Enrichment Analysis for PICRUSt2 output
prepare_gene_sets

Prepare gene sets for GSEA
pathway_errorbar_table

Generate Abundance Statistics Table for Pathway Analysis
preview_color_theme

Preview Color Theme
resolve_annotation_overlaps

Detect and Resolve Annotation Overlaps
require_column

Require a column exists in a data frame
pathway_heatmap

Create pathway heatmap with support for multiple grouping variables
pathway_ridgeplot

Ridge Plot for GSEA Results
pathway_pca

Perform Principal Component Analysis (PCA) on functional pathway abundance data
visualize_gsea

Visualize GSEA results
validate_daa_results

Validate DAA results data frame
run_fgsea

Run fgsea using the recommended fgseaMultilevel method
validate_group_sizes

Validate group sizes for statistical analysis
safe_extract

Safely Extract Elements from a List
smart_color_selection

Smart Color Selection
run_limma_gsea

Run limma-based gene set analysis (camera/fry)
calculate_log2_fold_change

Calculate log2 fold change with consistent pseudocount handling
compare_gsea_daa

Compare GSEA and DAA results
compare_metagenome_results

Compare Metagenome Results
color_themes

Color Theme System for ggpicrust2
compare_daa_results

Compare the Consistency of Statistically Significant Features
calculate_smart_text_size

Smart Text Size Calculator
create_pathway_class_theme

Create Pathway Class Annotation Theme
build_design_matrix

Build design matrix for limma analysis
daa_results_df

DAA Results Dataset
calculate_abundance_stats

Helper function to calculate abundance statistics for differential analysis
daa_annotated_results_df

Differentially Abundant Analysis Results with Annotation
create_dendrogram

Create dendrogram plot from hierarchical clustering
calculate_pseudocount

Calculate data-driven pseudocount for log transformation
data_utils

Data Utilities for ggpicrust2
calculate_rank_metric

Calculate rank metric for GSEA
create_empty_plot

Create empty plot for edge cases
.as_color_vector

Internal: coerce user 'scale' input to a vector of colors (or NULL) Accepts character vector or function(n)->colors. Returns character vector or NULL.
create_gradient_colors

Create Gradient Colors
create_legend_theme

Create Enhanced Legend Theme
.is_ggplot_scale

Internal: detect if an object is a ggplot2 Scale
create_network_plot

Create network visualization of GSEA results
create_heatmap_plot

Create heatmap visualization of GSEA results
.build_discrete_fill_for_direction

Internal: build a discrete fill scale for barplot direction
ec_reference

EC Number Reference Dataset
.build_heatmap_col_fun

Internal: build a circlize colorRamp2 function for ComplexHeatmap from user scale
format_pvalue_smart

Smart P-value Formatting
get_significance_stars

Get Significance Stars
get_significance_colors

Get Significance Colors