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OpenXGR: a web-server update for genomic summary data interpretation.

Chaohui Bao1, Shan Wang1, Lulu Jiang2

  • 1Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai200025, China.

Nucleic Acids Research
|May 9, 2023
PubMed
Summary
This summary is machine-generated.

OpenXGR is a new web server for human genomics research. It helps researchers discover knowledge from genomic summary data through enrichment and subnetwork analyses.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genomic summary data interpretation is a significant challenge in human genomics.
  • Existing tools may not offer comprehensive or real-time analysis for diverse genomic data types.

Purpose of the Study:

  • To introduce OpenXGR, a novel web server designed for efficient and effective knowledge discovery from human genomic summary data.
  • To provide a user-friendly platform for near real-time enrichment and subnetwork analyses.

Main Methods:

  • OpenXGR leverages ontologies, biological networks, and functional genomic datasets (e.g., promoter capture Hi-C, e/pQTL, enhancer-gene maps).
  • It incorporates six specialized analyzers: three for enrichment analysis and three for subnetwork analysis.
  • The server accepts various input types including gene lists, Single Nucleotide Polymorphisms (SNPs), and genomic regions.

Main Results:

  • OpenXGR offers near real-time enrichment analysis to identify enriched ontology terms for input genes or genes linked from SNPs/genomic regions.
  • It provides subnetwork analysis to identify gene networks from gene-, SNP-, or genomic region-level summary data.
  • The platform is designed to be user-friendly with a comprehensive manual.

Conclusions:

  • OpenXGR provides an integrated and effective platform for interpreting human genomic summary data.
  • The tool facilitates downstream knowledge discovery by connecting genomic variations to biological insights.
  • It empowers researchers to conduct advanced analyses for a deeper understanding of genomic research findings.