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Related Experiment Video

Updated: Jun 7, 2026

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer
08:20

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer

Published on: May 21, 2019

EMA - A R package for Easy Microarray data analysis.

Nicolas Servant1, Eleonore Gravier, Pierre Gestraud

  • 1Institut Curie, Paris F-75248, France. Nicolas.Servant@curie.fr.

BMC Research Notes
|November 5, 2010
PubMed
Summary
This summary is machine-generated.

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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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This study introduces the EMA R package, offering a user-friendly strategy and tools for analyzing gene expression microarray data. It simplifies complex analyses for non-specialist users, enhancing data interpretation.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Gene expression microarray analysis involves numerous complex methodologies and tools.
  • Non-specialist users often find these diverse options confusing and difficult to navigate.

Purpose of the Study:

  • To provide a clear analysis strategy for gene expression microarray data.
  • To offer a curated selection of validated R functions for microarray analysis.
  • To improve the ease of use, visualization, and interpretation of results for microarray data.

Main Methods:

  • Development of the easy-to-use R package named EMA (Expression Microarray Analysis).
  • Validation and improvement of existing R functions relevant to gene expression microarray analysis.
  • Integration of functions into a cohesive package for streamlined workflow.

Related Experiment Videos

Last Updated: Jun 7, 2026

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer
08:20

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer

Published on: May 21, 2019

Main Results:

  • The EMA R package offers a consolidated and simplified approach to gene expression microarray analysis.
  • Improved functions enhance data visualization and the interpretation of analytical results.
  • The package is designed for accessibility and practical application by a wider user base.

Conclusions:

  • The proposed strategy and tools within the EMA R package serve as a valuable starting point for microarray data analysis.
  • The EMA R package is available on the Comprehensive R Archive Network (CRAN).
  • The package is freely accessible, promoting wider adoption and utilization in the field.