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DNA Microarrays

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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Updated: Jun 10, 2026

A Rapid High-throughput Method for Mapping Ribonucleoproteins (RNPs) on Human pre-mRNA

A Rapid High-throughput Method for Mapping Ribonucleoproteins (RNPs) on Human pre-mRNA

Published on: December 2, 2009

A framework for oligonucleotide microarray preprocessing.

Benilton S Carvalho¹, Rafael A Irizarry

¹Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. benilton.carvalho@cancer.org.uk

Bioinformatics (Oxford, England)

|August 7, 2010

Summary

This summary is machine-generated.

The new oligo package offers a flexible, open-source solution for gene expression data analysis. It enhances existing tools for preprocessing, visualization, and downstream analysis, improving reproducibility and efficiency.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Open-source software has accelerated gene expression data analysis, but existing tools have limitations with expanding microarray applications.
The development of preprocessing methods has been facilitated by flexible software, yet limitations persist.

Purpose of the Study:

To develop a more general and versatile software solution for gene expression raw level data analysis.
To extend existing tools and leverage established code for enhanced preprocessing, visualization, and data access.

Main Methods:

Development of the 'oligo' package based on BioConductor principles.
Implementation of a unified paradigm for data preprocessing.
Integration with existing BioConductor tools for seamless downstream analysis.

Main Results:

The 'oligo' package provides a general solution supporting diverse applications.
It enhances transparency, reproducibility, and development efficiency in data analysis.
The package's infrastructure is designed for broad usability within the BioConductor ecosystem.

Conclusions:

The 'oligo' package offers a robust and extensible platform for gene expression data analysis.
It addresses limitations of existing tools, promoting reproducible and efficient research.
The software is freely available, fostering wider adoption and contribution in the bioinformatics community.