Pathway and functional enrichment analysis is a cornerstone of omics data interpretation, enabling researchers to map differentially expressed proteins or genes onto curated biological processes, signaling cascades, and molecular functions. While tools such as Ingenuity Pathway Analysis (IPA), g:Profiler, and Enrichr are widely used to generate ranked enrichment results, translating these tabular outputs into clear, publication-ready figures remains a time-consuming step that typically requires custom scripting and familiarity with visualization libraries — a significant barrier for researchers without a computational background. Here we present EnrichViz, a self-contained, browser-based R Shiny application that enables interactive, code-free visualization of pathway and functional enrichment results from quantitative proteomics and transcriptomics experiments. EnrichViz accepts three standard CSV files as input — a normalized abundance matrix, a sample annotation file, and enrichment results from any platform that exports tabular output — and produces four complementary, publication-ready visualizations: bar and bubble plots for ranking enriched terms by significance, chord diagrams for exploring pathway-molecule connectivity, clustered heatmaps for displaying Z-score normalized expression patterns across experimental groups, and boxplots or violin plots for examining the abundance distribution of individual proteins or genes. The application supports both raw p-values and pre-transformed -log10(p) values through automatic detection, and all plot parameters are adjustable in real time through a graphical sidebar. Every figure can be exported as a high-resolution PNG file at 300 dpi. EnrichViz is implemented in R using the Shiny, ggplot2, pheatmap, and circlize packages, and is freely available at https://rgmilian.shinyapps.io/EnrichViz/ .
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1 to 10 of 12 Results
Tabular Data - 85.2 KB - 10 Variables, 244 Observations - UNF:6:1uu7k9Vm0aeyRkA4fr2WrA==
g:ProfilerGOst enrichment analysis of DEGs comparing Neuronal Progenitor Cells, derived from discordant monozygotic twins with Parkinson’s Disease vs healthy controls. Parameters: version e114_eg62_p19_27110d83, organism hsapiens, source KEGG, REAC, WP, significance threshold method g_SCS, user threshold 0.01
Tabular Data - 1.6 KB - 6 Variables, 12 Observations - UNF:6:fq9jc+qT19XG8WW/j4uLOQ==
GSE185009 metadata was downloaded from GEO Datasets and filtered for Progenitor Cells from Parkinson Disease and Healthy Controls
Tabular Data - 3.3 MB - 14 Variables, 35413 Observations - UNF:6:nQE/3IIopcFH7/jjCc5YNw==
GSE185009 normalized RNA-seq counts downloaded from GREIN database only samples from Progenitor Cells from Parkinson Disease and Healthy Controls were included.
Tabular Data - 228.9 KB - 5 Variables, 3805 Observations - UNF:6:U8bCpUV1I0d7aMg2JUOobQ==
GSE185009 Differentially expressed genes comparing Neuronal Progenitor Cells derived from discordant monozygotic twins with Parkinson’s Disease vs healthy controls. Differential DESeq2 analysis was done using the NCBI GEO2R platform, p-adjusted 0.05
Tabular Data - 121.4 KB - 7 Variables, 869 Observations - UNF:6:3zAsRhXg09Zq955NZi4FyA==
Results of the enrichment analysis from Ingenuity Pathway Analysis of the differentialy abundant metabolites comparing liver of mice Old vs Young- 46 differentially abundant metabolites. Dataset downloaded from: Houtkooper RH, Argmann C, Houten SM, Cantó C, Jeninga EH, Andreux PA, Thomas C, Doenlen R, Schoonjans K, Auwerx J. The metabolic footprint...
Tabular Data - 60.2 KB - 15 Variables, 281 Observations - UNF:6:QrtSe///qY9n1AThZjSxFQ==
Results of the differential analysis (t-test) comparing Old vs Young mice liver metabolites
Tabular Data - 91.3 KB - 20 Variables, 281 Observations - UNF:6:QKEyu2AckBf0VJ+T6wsmag==
Log-transformed liver metabolomics data
Tabular Data - 242 B - 2 Variables, 15 Observations - UNF:6:Nn+T6xaoFcj1+4DVlSotew==
Metadata of samples used in the metabolomics differential analysis
Tabular Data - 258 B - 2 Variables, 6 Observations - UNF:6:L3i+tvRx1+9E5ThTuijNcg==
metadata for samples used in the proteomics visualization example. Data from this manuscript: Sharma A, Atasi T, Collin F, Wang W, Lam TT, Garcia-Milian R, Arroum T, Pham L, Hüttemann M, Moszczynska A. The Proteomic Landscape of Parkin-Deficient and Parkin-Overexpressing Rat Nucleus Accumbens: An Insight into the Role of Parkin in Methamphetamine U...
Tabular Data - 5.4 KB - 13 Variables, 13 Observations - UNF:6:IfMLGuIiJhCGQvAwNN1uOA==
Gene Set Enrichment Analysis results filtered by FDR q<0.05, and signatures of biological interest.
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