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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 12, 2026

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Published on: August 10, 2009

Washing scaling of GeneChip microarray expression.

Hans Binder¹, Knut Krohn, Conrad J Burden

¹Interdisciplinary Centre for Bioinformatics; Universität Leipzig, D-4107 Leipzig, Haertelstr 16-18, Germany. binder@izbi.uni-leipzig.de

BMC Bioinformatics

|June 1, 2010

Summary

This summary is machine-generated.

Post-hybridization washing significantly impacts microarray expression estimates. A new washing function calibrates probe intensities, improving accuracy and data quality for gene expression analysis.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Post-hybridization washing is a critical step in microarray experiments, influencing expression data quality.
Inadequate washing protocols and calibration can distort expression estimates derived from microarray intensities.

Purpose of the Study:

To investigate probe-level intensity changes during microarray washing cycles.
To develop and validate a method for calibrating microarray probe intensities based on washing effects.

Main Methods:

Experiments conducted on GeneChip microarrays with varied washing, scanning, and staining protocols.
Utilized the 'hook' method for disentangling specific and non-specific hybridization contributions.
Proposed an empirical washing function to estimate probe-bound target survival and calibrate intensities.

Main Results:

Standard washing removes ~90% non-specific background and 30-50% (MM probes) or <10% (PM probes) of specific targets.
Signal-to-noise ratio doubles approximately every ten stringent washing cycles.
Washing calibration markedly increases expression measures, particularly at low and high values.

Conclusions:

Washing is a key factor potentially distorting gene expression measures in microarrays.
A proposed first-order correction method integrates into existing microarray data calibration algorithms.
An experimental 'washing data set' is provided for community use in refining washing correction methods.