Comparison of Affymetrix GeneChip expression measures.

Area of Science:

• Bioinformatics
• Computational Biology
• Gene Expression Analysis

Background:

• Preprocessing is crucial for Affymetrix GeneChip expression level measurements.
• A growing number of preprocessing methods necessitate benchmarking for user guidance.
• Over 50 methods were submitted to a webtool for procedure benchmarking.

Purpose of the Study:

• To develop a benchmark for evaluating and comparing preprocessing methods for the Affymetrix GeneChip system.
• To identify the best preprocessing methods for specific user applications.
• To provide a resource for developers to benchmark their gene expression data analysis procedures.

Main Methods:

• Benchmarking of 31 probe set algorithms using a U95A dataset with spike-in controls.
• Evaluation of background correction's impact on preprocessing performance.
• Improvement of benchmark metrics for detailed precision and accuracy assessment.

Main Results:

• Background correction, a key preprocessing step, has the largest effect on performance.
• Background correction generally improves accuracy but reduces precision.
• Specific methods demonstrated a favorable balance of accuracy and precision on U95A arrays.

Conclusions:

• The benchmark provides critical insights into the trade-offs between accuracy and precision in gene expression preprocessing.
• The affycomp package (v1.5.2) and associated webtool offer valuable resources for selecting optimal preprocessing methods.
• Results on older arrays may differ on more current Affymetrix platforms, suggesting ongoing evaluation is needed.