Package index • TOmicsVis

Package Utilities

Core package functions for loading and launching applications

load_TOmicsVis(): Load TOmicsVis package without display warnings
tomicsvis(): TOmicsVis shiny app start function.

① Samples Statistics

Statistical sample outliers, correlation among samples, distance among samples, etc.

quantile_plot(): Quantile plot for visualizing data distribution.
box_plot(): Box plot support two levels and multiple groups with P value.
violin_plot(): Violin plot support two levels and multiple groups with P value.
survival_plot(): Survival plot for analyzing and visualizing survival data.

② Traits Analysis

Statistical analysis of traits, such as adding R and P values to box plots and violin plots, and more dimensionality reduction analysis.

corr_heatmap(): Correlation Heatmap for samples/groups based on Pearson algorithm.
pca_analysis(): PCA dimensional reduction analysis for RNA-Seq.
pca_plot(): PCA dimensional reduction visualization for RNA-Seq.
tsne_analysis(): TSNE analysis for analyzing and visualizing TSNE algorithm.
tsne_plot(): TSNE plot for analyzing and visualizing TSNE algorithm.
umap_analysis(): UMAP analysis for analyzing RNA-Seq data.
umap_plot(): UMAP plot for analyzing and visualizing UMAP algorithm.
dendro_plot(): Dendrograms for multiple samples/groups clustering.

③ Differential Expression Analysis

Analysis and visualization based on gene expression data and differentially expressed genes.

venn_plot(): Venn plot for stat common and unique gene among multiple sets.
upsetr_plot(): UpSet plot for stat common and unique gene among multiple sets.
flower_plot(): Flower plot for stat common and unique gene among multiple sets.
volcano_plot(): Volcano plot for visualizing differentailly expressed genes.
ma_plot(): MversusA plot for visualizing differentially expressed genes.
heatmap_group(): Heatmap group for visualizing grouped gene expression data.
circos_heatmap(): Circos heatmap plot for visualizing gene expressing in multiple samples.
chord_plot(): Chord plot for visualizing the relationships of pathways and genes.

④ Advanced Analysis

Advanced analysis of Transcriptome includes exploring gene expression trends of multiple groups of samples, constructing co-expression modules for genes, and exploring genes related to traits in expression modules.

gene_rank_plot(): Gene ranking dotplot for visualizing differentailly expressed genes.
gene_cluster_trend(): Gene cluster trend plot for visualizing gene expression trend profile in multiple samples.
trend_plot(): Trend plot for visualizing gene expression trend profile in multiple traits.
wgcna_pipeline(): WGCNA analysis pipeline for RNA-Seq.
network_plot(): Network plot for analyzing and visualizing relationship of genes.
heatmap_cluster(): Heatmap cluster for visualizing clustered gene expression data.

⑤ GO and KEGG Enrichment

GO and KEGG enrichment analysis and visualization.

go_enrich(): GO enrichment analysis based on GO annotation results (None/Exist Reference Genome).
go_enrich_stat(): GO enrichment analysis and stat plot (None/Exist Reference Genome).
go_enrich_bar(): GO enrichment analysis and bar plot (None/Exist Reference Genome).
go_enrich_dot(): GO enrichment analysis and dot plot (None/Exist Reference Genome).
go_enrich_net(): GO enrichment analysis and net plot (None/Exist Reference Genome).
kegg_enrich(): KEGG enrichment analysis based on KEGG annotation results (None/Exist Reference Genome).
kegg_enrich_bar(): KEGG enrichment analysis and bar plot (None/Exist Reference Genome).
kegg_enrich_dot(): KEGG enrichment analysis and dot plot (None/Exist Reference Genome).
kegg_enrich_net(): KEGG enrichment analysis and net plot (None/Exist Reference Genome).

⑥ Tables Operations

Quickly manipulate specific Transcriptome data structures.

table_split(): Table split used for splitting a grouped column to multiple columns.
table_merge(): Table merge used to merge multiple variables to on variable.
table_filter(): Table filter used to filter row by column condition.
table_cross(): Table cross used to cross search and merge results in two tables.

Example datasets in TOmicsVis

Example datasets included in TOmicsVis for testing and demonstration.

weight_sex: Weight and Sex traits dataframe.
traits_sex: Length, Width, Weight, and Sex traits dataframe.
survival_data: Survival data as example data for survival_plot function.
gene_expression: All genes in all samples expression dataframe of RNA-Seq.
gene_expression2: Shared DEGs of all paired comparisons in all samples expression dataframe of RNA-Seq.
gene_expression3: Shared DEGs of all paired comparisons in all groups expression dataframe of RNA-Seq.
samples_groups: Samples and groups for gene expression.
degs_lists: Paired comparisons differentially expressed genes (degs) among groups.
degs_stats: All DEGs of paired comparison CT-vs-LT12 stats dataframe.
degs_stats2: All DEGs of paired comparison CT-vs-LT12 stats2 dataframe.
network_data: Network data from WGCNA tan module top-200 dataframe.
gene_go_kegg: GO and KEGG annotation of background genes.
gene_go_kegg2: GO and KEGG annotation of background genes.