Package index • VISTA

VISTA Class & Constructors

Create and manage VISTA objects for differential expression analysis.

VISTA-class: VISTA S4 Class Definition
create_vista(): Create a VISTA Object with Internal DE Analysis
as_vista(): Coerce SummarizedExperiment to VISTA
validate_vista(): Validate a VISTA object
run_deseq_analysis() run_edger_analysis() run_limma_analysis(): Run Differential Expression Analysis with DESeq2, edgeR, or limma-voom
set_rowdata(): Set or append rowData annotations on a VISTA object
print(<VISTA>): Print a VISTA object like a SummarizedExperiment

Extract components from a VISTA object.

comparisons(<VISTA>) deg_summary(<VISTA>) cutoffs(<VISTA>) norm_counts(<VISTA>) sample_info(<VISTA>) row_data(<VISTA>) group_colors(<VISTA>) group_palette(<VISTA>): Accessor Methods for VISTA Object
set_de_source(): Set active DE source in a VISTA object
set_vista_group_colors(): Set manual group colors in a VISTA object
set_vista_comparison_colors(): Set manual comparison colors in a VISTA object

Sample-level quality control and exploratory visualizations.

Visualize differential expression results across comparisons.

get_volcano_plot(): Generate a volcano plot for a comparison in a VISTA object
get_ma_plot(): Generate MA plot from a VISTA object
get_deg_count_barplot(): Barplot of DEG counts (Up/Down) across comparisons
get_deg_count_pieplot(): Pie chart of DEG counts (Up/Down) across comparisons
get_deg_count_donutplot(): Donut chart of DEG counts (Up/Down) across comparisons
get_deg_venn_diagram(): DEG Venn diagram
plot_deg_alluvial(): Plot alluvial diagram showing gene regulation transitions across comparisons
get_genes_by_regulation(): Get Genes by Regulation

Visualize gene expression patterns across samples and groups.

get_expression_heatmap(): Expression heatmap
get_expression_barplot(): Plot gene expression means with optional statistics
get_expression_boxplot(): Plot gene expression distributions as boxplots
get_expression_violinplot(): Violin plot of expression values
get_expression_density(): Plot expression distributions as density curves
get_expression_scatter(): Compare normalized expression between two samples or groups
get_expression_lineplot(): Gene expression line plot
get_expression_lollipop(): Plot mean expression per group as a lollipop chart
get_expression_joyplot(): Plot expression distributions as ridgelines
get_expression_raincloud(): Raincloud plot of expression values
get_expression_matrix(): Retrieve an expression matrix from a VISTA object
get_expression_chromosome_plot(): Chromosome plot for expression

Visualize and compare log2 fold-changes across comparisons.

get_foldchange_heatmap(): Fold-change heatmap
get_foldchange_scatter(): Fold-change scatterplot between two comparisons
get_foldchange_barplot(): Plot fold-change barplots across comparisons for selected genes
get_foldchange_boxplot(): Plot fold-change distributions across comparisons
get_foldchange_lineplot(): Fold-change line plot across comparisons
get_foldchange_lollipop(): Fold-change plotting helpers (overview)
get_foldchange_matrix(): Extract a log2 fold-change matrix
get_foldchange_chromosome_plot(): Chromosome plot for fold change

Gene set enrichment and pathway analysis.

get_msigdb_enrichment(): Run MSigDB enrichment directly from a VISTA comparison
get_go_enrichment(): Run GO enrichment directly from a VISTA comparison
get_kegg_enrichment(): Run KEGG enrichment directly from a VISTA comparison
get_gsea(): Gene set enrichment analysis (GSEA) from a VISTA comparison
enrichMsigDB(): Perform MSigDB over-representation analysis on a VISTA object
get_enrichment_plot(): Plot enrichment results using -log10(FDR)
get_pathway_genes(): Extract genes from enriched pathways
get_pathway_heatmap(): Plot pathway-specific expression heatmaps from enrichment output
get_enrichment_chord(): Chord diagram of enrichment gene–pathway relationships

Estimate and visualize cell-type composition from bulk RNA-seq.

run_cell_deconvolution(): Run Cell Deconvolution on Bulk RNA-seq from VISTA Object
get_cell_fractions(): Retrieve stored cell fraction estimates
plot_celltype_barplot(): Plot cell-type composition as stacked bars
get_celltype_group_dotplot(): Plot group-level deconvolution scores as dot plot
get_celltype_heatmap(): Plot cell-type deconvolution heatmap

Generate automated analysis reports.

Save publication-ready plots, tables, and reproducible asset bundles.

Built-in datasets for examples and testing.

count_data: Example RNA-seq count matrix shipped with VISTA
sample_metadata: Sample metadata accompanying the VISTA airway example counts