Physical Sciences and Mathematics Commons^™

Focus On Rna Isolation: Obtaining Rna For Microrna (Mirna) Expression Profiling Analyses Of Neural Tissue, Wang-Xia Wang, Bernard R. Wilfred, Donald A. Baldwin, R. Benjamin Isett, Na Ren, Arnold J. Stromberg, Peter T. Nelson

Sanders-Brown Center on Aging Faculty Publications

MicroRNAs (miRNAs) are present in all known plant and animal tissues and appear to be somewhat concentrated in the mammalian nervous system. Many different miRNA expression profiling platforms have been described. However, relatively little research has been published to establish the importance of 'upstream' variables in RNA isolation for neural miRNA expression profiling. We tested whether apparent changes in miRNA expression profiles may be associated with tissue processing, RNA isolation techniques, or different cell types in the sample. RNA isolation was performed on a single brain sample using eight different RNA isolation methods, and results were correlated using a conventional …

On Correcting The Overestimation Of The Permutation Based False Discovery Rate Estimator., Shuo Jiao, Shunpu Zhang

Shuo Jiao

Motivation: Recent attempts to account for multiple testing in the analysis of microarray data have focused on controlling the false discovery rate (FDR), which is defined as the expected percentage of the number of false positive genes among the claimed significant genes. As a consequence, the accuracy of the FDR estimators will

be important for correctly controlling FDR. Xie et al. found that the standard permutation method of estimating FDR is biased and proposed to delete the predicted differentially expressed (DE) genes in the estimation of FDR for one-sample comparison. However, we notice that the formula of the FDR used …

Statistical Issues In The Normalizationof Multi-Species Microarray Data, John R. Stevens, Balasubramanian Ganesan, Prerak Desai, Sweta Rajan, Bart C. Weimer

Conference on Applied Statistics in Agriculture

Several species of bacteria are involved in the production of cheese, including Lactobacillus brevis and Lactococcus lactis. A custom-designed Affymetrix microarray was recently developed to study gene expression in three organisms on a single chip. This array contains only perfect match features for the coding and non-coding regions in the genomes of all three sequences. The multi-species nature of this array version raises interesting questions regarding the preprocessing or normalization strategies for the analysis of gene expression data. We present and evaluate several possible strategies using both cDNA dilution data and experimental expression data from a repeated measures design. The …

The Expression Of Microrna Mir-107 Decreases Early In Alzheimer's Disease And May Accelerate Disease Progression Through Regulation Of Β-Site Amyloid Precursor Protein-Cleaving Enzyme 1, Wang-Xia Wang, Bernard W. Rajeev, Arnold J. Stromberg, Na Ren, Guiliang Tang, Qingwei Huang, Isidore Rigoutsos, Peter T. Nelson

Sanders-Brown Center on Aging Faculty Publications

MicroRNAs (miRNAs) are small regulatory RNAs that participate in posttranscriptional gene regulation in a sequence-specific manner. However, little is understood about the role(s) of miRNAs in Alzheimer's disease (AD). We used miRNA expression microarrays on RNA extracted from human brain tissue from the University of Kentucky Alzheimer's Disease Center Brain Bank with near-optimal clinicopathological correlation. Cases were separated into four groups: elderly nondemented with negligible AD-type pathology, nondemented with incipient AD pathology, mild cognitive impairment (MCI) with moderate AD pathology, and AD. Among the AD-related miRNA expression changes, miR-107 was exceptional because miR-107 levels decreased significantly even in patients with …

The T-Mixture Model Approach For Detecting Differentially Expressed Genes In Microarrays, Shuo Jiao, Shunpu Zhang

Shuo Jiao

The finite mixture model approach has attracted much attention in analyzing microarray data due to its robustness to the excessive variability which is common in the microarray data. Pan (2003) proposed to use the normal mixture model method (MMM) to estimate the distribution of a test statistic and its null distribution. However, considering the fact that the test statistic is often of t-type, our studies find that the rejection region from MMM is often significantly larger than the correct rejection region, resulting an inflated type I error. This motivates us to propose the t-mixture model (TMM) approach. In this paper, …

Molecular Targets Of 2,3,7,8-Tetrachlorodibenzo-P-Dioxin (Tcdd) Within The Zebrafish Ovary: Insights Into Tcdd-Induced Endocrine Disruption And Reproductive Toxicity, Tisha C. King Heiden, Craig Struble, Matthew L. Rise, Martin J. Hessner, Reinhold J. Hutz, Michael J. Carvan Iii

Mathematics, Statistics and Computer Science Faculty Research and Publications

TCDD is a reproductive toxicant and endocrine disruptor, yet the mechanisms by which it causes these reproductive alterations are not fully understood. In order to provide additional insight into the molecular mechanisms that underlie TCDD's reproductive toxicity, we assessed TCDD-induced transcriptional changes in the ovary as they relate to previously described impacts on serum estradiol concentrations and altered follicular development in zebrafish. In silico computational approaches were used to correlate candidate regulatory motifs with observed changes in gene expression. Our data suggest that TCDD inhibits follicle maturation via attenuated gonadotropin responsiveness and/or depressed estradiol biosynthesis, and that interference of estrogen-regulated …

Probe Level Analysis Of Affymetrix Microarray Data, Richard Ellis Kennedy

Theses and Dissertations

The analysis of Affymetrix GeneChip® data is a complex, multistep process. Most often, methodscondense the multiple probe level intensities into single probeset level measures (such as RobustMulti-chip Average (RMA), dChip and Microarray Suite version 5.0 (MAS5)), which are thenfollowed by application of statistical tests to determine which genes are differentially expressed. An alternative approach is a probe-level analysis, which tests for differential expression directly using the probe-level data. Probe-level models offer the potential advantage of more accurately capturing sources of variation in microarray experiments. However, this has not been thoroughly investigated, since current research efforts have largely focused on the …