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Published on: August 10, 2009
Quality assessment of Affymetrix GeneChip data
1Department of Computer Science, North Carolina State University, Raleigh, North Carolina, USA.
Omics : a Journal of Integrative Biology
|October 31, 2006
Summary
This review covers methods and software for assessing Affymetrix GeneChip microarray data quality. It focuses on identifying corrupted chips and evaluating RNA quality for complex samples.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- Affymetrix GeneChips are a widely used platform for simultaneous gene expression analysis.
- Microarray experiments are complex and prone to variations that can impact results.
- Assessing data quality is crucial due to increasing data volume and complexity.
Purpose of the Study:
- To provide an overview of current quality assessment methods and software for Affymetrix GeneChip data.
- To highlight techniques for identifying corrupted chips and evaluating RNA quality.
Main Methods:
- Review of quality metrics and diagnostic plots.
- Description of probe-level methods and pseudo-images for chip quality assessment.
- Discussion of RNA quality assessment for challenging sample types.
Main Results:
- Current methods and software tools enable robust quality assessment of microarray data.
- Identification of corrupted chips can be achieved through various computational approaches.
- RNA quality assessment is vital for reliable gene expression analysis from difficult samples.
Conclusions:
- Effective quality assessment is essential for the validity of Affymetrix GeneChip experiments.
- A range of computational tools are available to ensure data integrity.
- Standardized RNA quality checks improve the reliability of gene expression profiling.
