A Graphical Approach for Quality Control of Oligonucleotide Array Data

Abstract

In studies of quality control of oligonucleotide array data, one objective is to screen out ineligible arrays. Incomparable arrays (one type of ineligible arrays) arise as the experimental factors are poorly controlled. Due to the high volume of data in gene arrays, examination of array comparability requires special treatments to reduce data dimension without distortion. This paper proposes a graphical approach to address these issues. The proposed approach uses percentile methods to group data, and applies the 2D image plot to display the grouped data. Moreover, an invariant band is employed to quantify degrees of array comparability. We use two publicly available oligonucleotide array datasets from Affymetrix GeneChip System for evaluation. The results demonstrate the utility of our approach to examine data quality and also as an exploratory tool to verify differentially expressed genes selected by vigorous statistical methods.

Key Words:

• Oligonucleotide array
• Comparability
• Normalization
• Scatterplot
• 2D image plot
• Invariant band

Mathematics Subject Classification:

• 62P10

Acknowledgment

This work was supported by grants from the National Cancer Institute (5P30 CA-13148 and 1P50 CA89019). The author gratefully acknowledges the helpful discussions and comments by Dr. James Chen and also the constructive criticisms of an earlier draft of the manuscript by two anonymous referees.