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Full-Text Articles in Physical Sciences and Mathematics
Survival Analysis Of Microarray Data With Microarray Measurement Subject To Measurement Error, Juan Xiong
Survival Analysis Of Microarray Data With Microarray Measurement Subject To Measurement Error, Juan Xiong
Electronic Thesis and Dissertation Repository
Microarray technology is essentially a measurement tool for measuring expressions of genes, and this measurement is subject to measurement error. Gene expressions could be employed as predictors for patient survival, and the measurement error involved in the gene expression is often ignored in the analysis of microarray data in the literature. Efforts are needed to establish statistical method for analyzing microarray data without ignoring the error in gene expression. A typical microarray data set has a large number of genes far exceeding the sample size. Proper selection of survival relevant genes contributes to an accurate prediction model. We study the …
Comparison Of Rna Quality From Stressed And Unstressed Recombinant Escherichia Coli, Mary Alice Salazar
Comparison Of Rna Quality From Stressed And Unstressed Recombinant Escherichia Coli, Mary Alice Salazar
All Theses
High quality, intact RNA is required for DNA microarray studies, cloning, and reverse transcriptase polymerase chain reaction (rt-PCR) analysis. There are several analytical methods used to assess the RNA quality. The RNA Integrity Number (RIN) from the Agilent Bioanalyzer is one quality control assay used to evaluate RNA. For recombinant Escherichia coli cultured under stressful conditions the RNA profiles obtained using the Agilent Bioanalyzer indicate RNA degradation; however, RNA obtained and purified in parallel from unstressed recombinant cultures indicate acceptable RNA values without significant degradation. We proposed that for stressed E. coli the RIN value is not necessarily indicative of …
A Mixture Model Based Approach For Estimating The Fdr In Replicated Microarray Data, Shuo Jiao, Shunpu Zhang
A Mixture Model Based Approach For Estimating The Fdr In Replicated Microarray Data, Shuo Jiao, Shunpu Zhang
Shuo Jiao
One of the mostly used methods for estimating the false discovery rate (FDR) is the permutation based method. The permutation based method has the well-known granularity problem due to the discrete nature of the permuted null scores. The granularity problem may produce very unstable FDR estimates. Such instability may cause scientists to over- or under-estimate the number of false positives among the genes declared as significant, and hence result in inaccurate interpretation of biological data. In this paper, we propose a new model based method as an improvement of the permutation based FDR estimation method of SAM [1] The new …