IBDIRP

IBDIRP integrates and organizes literature, metagenomics, metabolomics, genomic, transcriptomic, and single-cell datasets related to inflammatory bowel diseases (IBD), including ulcerative colitis and Crohn's disease, to enable integrative analyses of disease mechanisms and biomarkers.

Key Features:

• Comprehensive Data Integration: Aggregates resources and data from PubMed, Google, GMrepo, gutMega, gutMDisorder, Single Cell Portal, Gene Expression Omnibus, and other databases and web resources.
• Genomic Insights: Systematically catalogs over 320 unique risk single-nucleotide polymorphisms (SNPs) associated with IBD.
• Gene and Transcriptome Data: Provides a collection of more than 289 IBD-related genes and manually curated transcriptomics datasets from the Gene Expression Omnibus comprising 12,388 samples.
• Microbiota Analysis: Offers access to sorted microbiota data from GMrepo, gutMega, and gutMDisorder encompassing 23,149 taxonomic records.
• Metabolomics Studies: Includes data from 24 metabolomics studies covering 2,896 participants.
• Single-Cell Data Visualization: Introduces two interactive single-cell data plug-in units for visualization and interrogation by cells and genes.
• Resource Directory: Lists 18 web resources related to IBD, including organizational websites, scoring tools, genetic and multi-omics resources, and biobanks.

Scientific Applications:

• Integrative multi-omics analysis: Enables cross-domain integration of literature, genomic, transcriptomic, microbiome, metabolomic, and single-cell data for holistic IBD studies.
• Genetic risk assessment: Supports investigation of IBD-associated SNPs and their relationships to annotated IBD-related genes.
• Microbiome research: Facilitates analysis of gut microbiota taxonomic records from GMrepo, gutMega, and gutMDisorder in relation to IBD.
• Metabolomic biomarker exploration: Allows interrogation of metabolomics datasets from 24 studies to identify metabolic alterations associated with IBD.
• Single-cell heterogeneity analysis: Enables visualization and gene-/cell-level interrogation of single-cell datasets to study cellular heterogeneity in IBD.

Methodology:

Aggregates and integrates data from PubMed, Google, GMrepo, gutMega, gutMDisorder, Single Cell Portal and other databases; manually curates transcriptomics from the Gene Expression Omnibus; systematically catalogs >320 IBD-associated SNPs; sorts microbiota records from the three microbiome databases; includes 24 metabolomics studies and two interactive single-cell plug-in units, and compiles a directory of 18 web resources.