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OmicsOne: associate omics data with phenotypes in one-click.

Hui Zhang1, Minghui Ao1, Arianna Boja2

  • 1School of Medicine, Johns Hopkins University, Baltimore, MD, 21287, USA.

Clinical Proteomics
|December 13, 2021
PubMed
Summary
This summary is machine-generated.

OmicsOne simplifies multi-omic data analysis for phenotype association. This tool rapidly identifies potential biomarkers like genes and proteins, aiding biological process understanding.

Keywords:
BioinformaticsGlycoproteomicsOvarian cancerPhenotype associationProteomicsSoftware

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Area of Science:

  • Bioinformatics
  • Genomics
  • Proteomics
  • Glycoproteomics

Background:

  • High-throughput omics technologies generate massive datasets requiring advanced analysis.
  • Multi-omic analysis offers deeper insights into biological systems and phenotype associations.
  • Existing tools lack efficient integration for multi-omic phenotype association studies.

Purpose of the Study:

  • To present OmicsOne, an interactive web-based framework for rapid phenotype association analysis of multi-omic data.
  • To integrate quality control, statistical analysis, and interactive visualization for multi-omic data.
  • To enable efficient investigation of phenotypes using multiple omics data.

Main Methods:

  • OmicsOne was applied to proteomic and glycoproteomic datasets of high-grade serous ovarian carcinoma (HGSOC) and lung squamous cell carcinoma (LSCC).
  • Analysis involved six modules: phenotype profiling, data preprocessing/QC, knowledge annotation, feature discovery, correlation/regression modeling, and enrichment analysis.
  • The framework facilitates one-click analysis for phenotype association.

Main Results:

  • OmicsOne was developed as an integrated software solution for multi-omic phenotype association analysis.
  • Application to HGSOC data confirmed previous findings and identified HNRNPU and a HYOU1 glycopeptide as potential biomarkers.
  • Performance was further validated using LSCC proteome data for tumor and normal tissue comparison.

Conclusions:

  • OmicsOne effectively simplifies multi-omic data analysis.
  • The tool reveals significant associations between phenotypes and potential biomarkers (genes, proteins, glycopeptides).
  • OmicsOne assists users in understanding aberrant biological processes rapidly.