Two problems that dog current microarrays analyses are (i) the relatively arbitrary nature of data preprocessing and (ii) the inability to incorporate spot quality information in inference except by all-or-nothing spot filtering. In this chapter we propose an approach based on using weights to overcome these two problems. The first approach uses weighted p-values to make inference robust to normalization and the second approach uses weighted spot intensity values to improve inference without any filtering.
|Title of host publication
|University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science
|Number of pages
|Published - 2007