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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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BioWardrobe: an integrated platform for analysis of epigenomics and transcriptomics data.

Andrey V Kartashov1, Artem Barski2,3

  • 1Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center and Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, USA. Andrey.Kartashov@cchmc.org.

Genome Biology
|August 8, 2015
PubMed
Summary

BioWardrobe offers a biologist-friendly web platform for analyzing epigenomics and transcriptomics data. This tool democratizes high-throughput sequencing analysis, requiring no programming expertise for genome-wide studies.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencing technologies have advanced biological research capabilities for genome-wide studies.
  • A significant barrier to adopting these technologies is the lack of specialized bioinformatics expertise in many laboratories.

Purpose of the Study:

  • To present the BioWardrobe platform, a user-friendly web interface designed for storing, visualizing, and analyzing epigenomics and transcriptomics data.
  • To enable biologists to perform complex genomic analyses without requiring programming skills.

Main Methods:

  • The BioWardrobe platform provides a web-based interface for data management and analysis.
  • It includes predefined pipelines for common tasks such as data download, visualization, RPKM calculation, and peak identification.
  • Advanced features encompass differential gene expression analysis, binding analysis, and generation of average tag density profiles and heatmaps.

Main Results:

  • Users can store and analyze large-scale epigenomics and transcriptomics datasets through an intuitive interface.
  • The platform facilitates visualization of results using a genome browser.
  • Key analyses like differential gene expression and peak calling are accessible to users without bioinformatics backgrounds.

Conclusions:

  • BioWardrobe lowers the barrier to entry for utilizing high-throughput sequencing data in biological research.
  • It empowers laboratories lacking bioinformatics expertise to conduct advanced genome-wide analyses.
  • The platform supports a wide range of analyses, from basic data processing to complex differential analyses, enhancing research capabilities.