Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip stu

Background: The choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with known concentration are often used to assess the relative performance of probe set algorithms. Given the fact that the spiked-in cRNAs do not represent endogenously expressed genes in experiments, it becomes increasingly important to have methods to study whether a particular probe set algorithm is more appropriate for a specific dataset, without using such external reference data. Results: We propose the use of the probe set redundancy feature for evaluating the performance of probe set algorithms, and have presented three approaches for analyzing data variance and result bias using two sample t-test statistics from redundant probe sets. These approaches are as follows: 1) analyzing redundant probe set variance based on t-statistic rank order, 2) computing correlation of t-statistics between redundant probe sets...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Zihua Hu, Gail R. Willsky
• Keywords: Algorithms, BMCBI 2006, Redundant Probe, Redundant Probe Sets