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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

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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Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity
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BEAT: Bioinformatics Exon Array Tool to store, analyze and visualize Affymetrix GeneChip Human Exon Array data from

Arianna Consiglio1, Massimo Carella, Giorgio De Caro

  • 1Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.

BMC Bioinformatics
|April 28, 2012
PubMed
Summary

Alternative splicing (AS) is crucial for gene expression and disease. BEAT is a new bioinformatics tool that analyzes exon array data, offering insights into AS events in human diseases without requiring programming knowledge.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Alternative splicing (AS) generates transcript diversity from single genes, impacting cellular differentiation and disease.
  • Exon array technology provides detailed gene expression profiles, enabling analysis at both gene and exon levels.
  • Existing analysis tools often lack advanced statistical features or require programming expertise.

Purpose of the Study:

  • To introduce BEAT, an integrated, user-friendly bioinformatics framework for storing, analyzing, and visualizing exon array datasets.
  • To provide a platform for comprehensive study of AS events in human diseases.
  • To offer advanced statistical features for AS analysis without programming knowledge.

Main Methods:

  • Development of BEAT, a web-based bioinformatics framework combining a data warehouse approach with statistical methods.
  • Integration of exon and gene level expression plots with annotations (alternative names, IDs, Gene Ontology, pathways).
  • Implementation of meta-statistics for novel exploration of analysis results and multivariate AS analysis using clinical data.

Main Results:

  • BEAT is a web tool with a graphical front-end for uploading and analyzing exon array data.
  • The tool was tested on 173 samples and refined with colorectal and renal cell cancer datasets.
  • BEAT displays analysis results through interactive tables and graphics, customizable with user-defined thresholds.

Conclusions:

  • BEAT addresses the need for user-friendly, statistically advanced tools for exon array data analysis.
  • The platform facilitates comprehensive studies of alternative splicing in human diseases.
  • BEAT enhances the interpretation of AS events through interactive visualizations and customizable analyses.