A graphical approach for quality control of oligonucleotide array data.
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.
Chen
Dung-Tsa
DT
Biostatistics and Bioinformatics Unit, University of Alabama at Birmingham, Birmingham, AL 35294, USA. dtchen@uab.edu
D000465:Algorithms; D003627:Data Interpretation, Statistical; D006801:Humans; D009154:Mutation; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*; D009841:Oligonucleotides / Q000235:genetics*; D011786:Quality Control
D009841:Oligonucleotides