Protocols for the assurance of microarray data quality and process control
Open Access
- 24 October 2005
- journal article
- Published by Oxford University Press (OUP) in Nucleic Acids Research
- Vol. 33 (19) , e172
- https://doi.org/10.1093/nar/gni167
Abstract
Microarrays represent a powerful technology that provides the ability to simultaneously measure the expression of thousands of genes. However, it is a multi-step process with numerous potential sources of variation that can compromise data analysis and interpretation if left uncontrolled, necessitating the development of quality control protocols to ensure assay consistency and high-quality data. In response to emerging standards, such as the minimum information about a microarray experiment standard, tools are required to ascertain the quality and reproducibility of results within and across studies. To this end, an intralaboratory quality control protocol for two color, spotted microarrays was developed using cDNA microarrays from in vivo and in vitro dose-response and time-course studies. The protocol combines: (i) diagnostic plots monitoring the degree of feature saturation, global feature and background intensities, and feature misalignments with (ii) plots monitoring the intensity distributions within arrays with (iii) a support vector machine (SVM) model. The protocol is applicable to any laboratory with sufficient datasets to establish historical high- and low-quality data.Keywords
This publication has 16 references indexed in Scilit:
- Immobilized probe and glass surface chemistry as variables in microarray fabricationBMC Genomics, 2004
- Are data from different gene expression microarray platforms comparable?Genomics, 2004
- Overview of an interlaboratory collaboration on evaluating the effects of model hepatotoxicants on hepatic gene expression.Environmental Health Perspectives, 2004
- Array-A-Lizer: A serial DNA microarray quality analyzerBMC Bioinformatics, 2004
- Maintaining data integrity in microarray data managementBiotechnology & Bioengineering, 2003
- A novel strategy for microarray quality control using Bayesian networksBioinformatics, 2003
- The Stanford Microarray Database: data access and quality assessment toolsNucleic Acids Research, 2003
- Statistical process control for large scale microarray experimentsBioinformatics, 2002
- Quantitative quality control in microarray image processing and data acquisitionNucleic Acids Research, 2001
- Microarrays: lost in a storm of data?Nature Reviews Neuroscience, 2001