Robust Designs against Missing Data in Two-Color cDNA Microarray Experiments
Date Issued
2009
Date
2009
Author(s)
Chen, Yong-Yu
Abstract
Microarray has been an increasingly popular biotechnology in measuring gene expression of a biological sample. In contrast to the traditional methods, it enables biologists to evaluate ten thousands of mRNA sequences in expression simultaneously. Statistical methods developed for such large-scale and complex data from microarray experiments have been intensively explored within recent years. On the other hand, the studies on the design issues need further investigation. In the current study, we focus on one of the important design issues in two-color mciroarray experiments. We propose a new criterion to evaluate the robustness of designs against missing data. Furthermore, we construct the robust designs suitable for the two-color microarray experiments. issing data are frequently confronted during a microarray experiment. Conventionally, one performs analysis either estimating or ignoring missing data.owever, we are currently interested in selection of good designs that may provide high robustness against missing data. We first present two linear models in characterizing the data of a two-color microarray experiment according to whether or not take into account the variation between two fluorescent dyes. Then we seek for the robust designs based on the proposed models and the robustness criterion. The criterion we proposed is to compute the proportions of the connected residual designs for the class of block designs of size two and that of row-column designs with two rows. The robust designs are defined as those who have the maximal proportions if a number of blocks (columns) are missing. In specificity, we investigate two kinds of experiments in this thesis, including treatment comparative experiments and test-control experiments. Two classes of practical designs are respectively proposed for these two kinds of experiments using two-color microarrays.
Subjects
robustness, gene expression
comparative experiment
test-control experiment
block design
row-column design
Type
thesis
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