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OmicsView: Omics data analysis through interactive visual analytics.

Fergal Casey1, Soumya Negi1, Jing Zhu1

  • 1Translational Biology, Research Development, Biogen, Inc., Cambridge, MA 02142, USA.

Computational and Structural Biotechnology Journal
|March 31, 2022
PubMed
Summary
This summary is machine-generated.

OmicsView is a new open-source platform that helps researchers analyze gene expression data. It simplifies mining large datasets to find disease biomarkers and understand treatment effects.

Keywords:
DEG, Differentially Expressed GeneExpression databasesExpression profilingMeta-analysisNGS, Next Generation SequencingRNASeq, RNA SequencingRNAseqVisual analytics

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) generates vast amounts of human tissue transcriptional data.
  • Bench scientists require accessible tools to analyze this data for disease research.
  • Public repositories house petabytes of expression data, necessitating user-friendly mining platforms.

Purpose of the Study:

  • To introduce OmicsView, an open-source analytics and visualization platform for gene expression data.
  • To enable bench scientists with limited computational expertise to access and analyze large omics datasets.
  • To facilitate the identification of disease biomarkers and the effects of interventions.

Main Methods:

  • Development of the OmicsView platform, an open-source tool for expression data analysis.
  • Preloading OmicsView with thousands of samples from diverse disease areas and normal tissues, including the GTEx database.
  • Processing all included data with a harmonized bioinformatics pipeline.
  • Demonstrating platform utility through a Crohn's disease data mining case study.

Main Results:

  • OmicsView provides a user-friendly interface for accessing and analyzing large-scale transcriptional data.
  • The platform successfully facilitated a data mining exercise for Crohn's disease.
  • Key disease pathologies and significant biomarkers for disease and treatment response were rapidly identified.

Conclusions:

  • OmicsView empowers researchers, particularly those with limited computational backgrounds, to effectively mine public expression datasets.
  • The platform streamlines the discovery of disease mechanisms and therapeutic targets.
  • OmicsView represents a valuable resource for advancing translational research in various disease areas.