DNA microarray experiment, a well-established experimental technique, aims understanding the function of genes in some biological functions and cellular processes. One of the most common experiments in functional genomic research is to compare two groups of microarray data to determine which genes are differentially expressed. In this dissertation, we propose (1) a methodology to estimate the proportion of differentially expressed genes in microarray experiments, (2) parametric and non-parametric methods to estimate error distribution of microarray data, and (3) an optimal scoring method and LDA on HLdata on the DNA barcoding data to cluster the species using COI sequence. We study the performance of our methods using simulation studies where we compare it to other standard methods and apply it on real data sets to show the advantage of our method.For some specimens the classification into known species might be unclear or borderline. ... Another is assigning measures of confidence to new clusters representing new species. ... All species include some level of variation among individuals and in some cases this variation takes the form of splits among local populations and even subspecies. ... The challenge is to provide guidelines for sample size - guidelines that will allow your clustering method and/or classification rule toanbsp;...
|Title||:||Data Analysis for Microarray Experiment and DNA Barcode of Life|
|Publisher||:||ProQuest - 2008|