Journal of Data Science

Abstract: High density oligonucleotide arrays have become a standard research tool to monitor the expression of thousands of genes simultaneously. Affymetrix GeneChip arrays are the most popular. They use short oligonucleotides to probe for genes in an RNA sample. However, important challenges remain in estimating expression level from raw hybridization in tensities on the array. In this paper, we deal with the problem of estimating gene expression based on a statistical model. The present method is like Li and Wong model (2001a), but assumes more generality. More precisely, we show how the model introduced by Li and Wong can be generalized to provide new measure of gene expression. Moreover, we provide a comparison between these two models.