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Search Results: 1 - 10 of 211712 matches for " Stephen P. Page "
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Evaluating Statistical Methods Using Plasmode Data Sets in the Age of Massive Public Databases: An Illustration Using False Discovery Rates
Gary L. Gadbury,Qinfang Xiang,Lin Yang,Stephen Barnes,Grier P. Page,David B. Allison
PLOS Genetics , 2008, DOI: 10.1371/journal.pgen.1000098
Abstract: Plasmode is a term coined several years ago to describe data sets that are derived from real data but for which some truth is known. Omic techniques, most especially microarray and genomewide association studies, have catalyzed a new zeitgeist of data sharing that is making data and data sets publicly available on an unprecedented scale. Coupling such data resources with a science of plasmode use would allow statistical methodologists to vet proposed techniques empirically (as opposed to only theoretically) and with data that are by definition realistic and representative. We illustrate the technique of empirical statistics by consideration of a common task when analyzing high dimensional data: the simultaneous testing of hundreds or thousands of hypotheses to determine which, if any, show statistical significance warranting follow-on research. The now-common practice of multiple testing in high dimensional experiment (HDE) settings has generated new methods for detecting statistically significant results. Although such methods have heretofore been subject to comparative performance analysis using simulated data, simulating data that realistically reflect data from an actual HDE remains a challenge. We describe a simulation procedure using actual data from an HDE where some truth regarding parameters of interest is known. We use the procedure to compare estimates for the proportion of true null hypotheses, the false discovery rate (FDR), and a local version of FDR obtained from 15 different statistical methods.
A proposed metric for assessing the measurement quality of individual microarrays
Kyoungmi Kim, Grier P Page, T Mark Beasley, Stephen Barnes, Katherine E Scheirer, David B Allison
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-35
Abstract: We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets.We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements.Gene expression microarrays are a powerful tool used in molecular biology and genetics for understanding gene expression change in biological processes under normal and pathological conditions [1]. Intensity measurements of gene expression are associated with significant variations as a result of the complex and multi-stage processing involved in microarray experiments. Beyond the variability that may be introduced during the fabrication of arrays as a result of print substrate quality and printing pin anomalies, several processing steps – mRNA sample extraction, amplification and labeling, hybridization, and scanning – may introduce substantial variation in measurements [2]. Although several studies have characterized the potential impact of these latter sources of variation on measurements of gene expression [2-4], methods for assessing the physical measurement quality of individual microarrays are not widely available. If technical replicates for a biological case are available, the degree of concordance between technical replicates ca
Correlation of microRNA levels during hypoxia with predicted target mRNAs through genome-wide microarray analysis
Jennifer S Guimbellot, Stephen W Erickson, Tapan Mehta, Hui Wen, Grier P Page, Eric J Sorscher, Jeong S Hong
BMC Medical Genomics , 2009, DOI: 10.1186/1755-8794-2-15
Abstract: To identify changes induced by hypoxia, we conducted mRNA- and miRNA-array-based experiments in HT29 cells, and performed comparative analysis of the resulting data sets based on multiple target prediction algorithms. To date, few studies have investigated an environmental perturbation for effects on genome-wide miRNA levels, or their consequent influence on mRNA output.Comparison of miRNAs with predicted mRNA targets indicated a lower level of concordance than expected. We did, however, find preliminary evidence of combinatorial regulation of mRNA expression by miRNA.Target prediction programs and expression profiling techniques do not yet adequately represent the complexity of miRNA-mediated gene repression, and new methods may be required to better elucidate these pathways. Our data suggest the physiologic impact of miRNAs on cellular transcription results from a multifaceted network of miRNA and mRNA relationships, working together in an interconnected system and in context of hundreds of RNA species. The methods described here for comparative analysis of cellular miRNA and mRNA will be useful for understanding genome wide regulatory responsiveness and refining miRNA predictive algorithms.MicroRNAs (miRNA) are approximately 22-nucleotide, non-coding RNA sequences important in the control of gene expression. They are involved in a variety of cellular processes, including development, cell differentiation, signaling, and tumorigenesis[1], and are believed to represent 1% of the predicted genes in mammalian and nematode genomes[2,3]. Mammals in general (and primates in particular) appear to have a large number of miRNAs not found in other animal orders[2], suggesting that many functional miRNAs may have emerged during recent evolutionary periods. According to current functional and predictive models, each miRNA regulates multiple genes during differentiation and/or development at the transcription, translation, and posttranslational levels[1,4,5]. However, few of t
A Novel Myosin Essential Light Chain Mutation Causes Hypertrophic Cardiomyopathy with Late Onset and Low Expressivity
Paal Skytt Andersen,Paula Louise Hedley,Stephen P. Page,Petros Syrris,Johanna Catharina Moolman-Smook,William John McKenna,Perry Michael Elliott,Michael Christiansen
Biochemistry Research International , 2012, DOI: 10.1155/2012/685108
Abstract: Hypertrophic cardiomyopathy (HCM) is caused by mutations in genes encoding sarcomere proteins. Mutations in MYL3, encoding the essential light chain of myosin, are rare and have been associated with sudden death. Both recessive and dominant patterns of inheritance have been suggested. We studied a large family with a 38-year-old asymptomatic HCM-affected male referred because of a murmur. The patient had HCM with left ventricular hypertrophy (max WT 21 mm), a resting left ventricular outflow gradient of 36 mm Hg, and left atrial dilation (54 mm). Genotyping revealed heterozygosity for a novel missense mutation, p.V79I, in MYL3. The mutation was not found in 300 controls, and the patient had no mutations in 10 sarcomere genes. Cascade screening revealed a further nine heterozygote mutation carriers, three of whom had ECG and/or echocardiographic abnormalities but did not fulfil diagnostic criteria for HCM. The penetrance, if we consider this borderline HCM the phenotype of the p.V79I mutation, was 40%, but the mean age of the nonpenetrant mutation carriers is 15, while the mean age of the penetrant mutation carriers is 47. The mutation affects a conserved valine replacing it with a larger isoleucine residue in the region of contact between the light chain and the myosin lever arm. In conclusion, MYL3 mutations can present with low expressivity and late onset.
Sources of variation in Affymetrix microarray experiments
Stanislav O Zakharkin, Kyoungmi Kim, Tapan Mehta, Lang Chen, Stephen Barnes, Katherine E Scheirer, Rudolph S Parrish, David B Allison, Grier P Page
BMC Bioinformatics , 2005, DOI: 10.1186/1471-2105-6-214
Abstract: We performed a microarray experiment using a total of 24 Affymetrix GeneChip? arrays. The study included 4th mammary gland samples from eight 21-day-old Sprague Dawley CD female rats exposed to genistein (soy isoflavone). RNA samples from each rat were split to assess variation arising at labeling and hybridization steps. A general linear model was used to estimate variance components. Pearson correlations were computed to evaluate agreement between technical and biological replicates.The greatest source of variation was biological variation, followed by residual error, and finally variation due to labeling when *.cel files were processed with dChip and RMA image processing algorithms. When MAS 5.0 or GCRMA-EB were used, the greatest source of variation was residual error, followed by biology and labeling. Correlations between technical replicates were consistently higher than between biological replicates.Microarray chips are a powerful technology capable of measuring expression levels of thousands of genes simultaneously. Expression profiling has led to dramatic advances in the understanding of cellular processes at the molecular level, which may lead to improvements in molecular diagnostics and personalized medicine [1]. The number of experiments involving microarrays grows nearly exponentially each year [2]. Several platforms are currently available, including the commonly used short oligonucleotide-based Affymetrix GeneChip? arrays, which utilize multiple probes for each gene and automated control of the experimental process from hybridization to quantification. Although microarrays have tremendous potential, great effort and care is required in planning and designing microarray experiments, analyzing gene expression data, and interpreting results [3-6].A typical microarray experiment has many different sources of variation which can be attributed to biological and technical causes [4]. Biological variation results from tissue heterogeneity, genetic polymorphis
A Novel Myosin Essential Light Chain Mutation Causes Hypertrophic Cardiomyopathy with Late Onset and Low Expressivity
Paal Skytt Andersen,Paula Louise Hedley,Stephen P. Page,Petros Syrris,Johanna Catharina Moolman-Smook,William John McKenna,Perry Michael Elliott,Michael Christiansen
Biochemistry Research International , 2012, DOI: 10.1155/2012/685108
Abstract: Hypertrophic cardiomyopathy (HCM) is caused by mutations in genes encoding sarcomere proteins. Mutations in MYL3, encoding the essential light chain of myosin, are rare and have been associated with sudden death. Both recessive and dominant patterns of inheritance have been suggested. We studied a large family with a 38-year-old asymptomatic HCM-affected male referred because of a murmur. The patient had HCM with left ventricular hypertrophy (max WT?21?mm), a resting left ventricular outflow gradient of 36?mm?Hg, and left atrial dilation (54?mm). Genotyping revealed heterozygosity for a novel missense mutation, p.V79I, in MYL3. The mutation was not found in 300 controls, and the patient had no mutations in 10 sarcomere genes. Cascade screening revealed a further nine heterozygote mutation carriers, three of whom had ECG and/or echocardiographic abnormalities but did not fulfil diagnostic criteria for HCM. The penetrance, if we consider this borderline HCM the phenotype of the p.V79I mutation, was 40%, but the mean age of the nonpenetrant mutation carriers is 15, while the mean age of the penetrant mutation carriers is 47. The mutation affects a conserved valine replacing it with a larger isoleucine residue in the region of contact between the light chain and the myosin lever arm. In conclusion, MYL3 mutations can present with low expressivity and late onset. 1. Introduction Hypertrophic cardiomyopathy (HCM) is an autosomal dominant genetic disease caused by mutations in genes which encode sarcomeric proteins [1–4]. The most frequently affected genes are MYH7 [5], MYBPC3 [6], and TNNT2 [7], coding for the heavy chain of myosin, the myosin-binding protein-C, and troponin T, respectively. More than 200 mutations have been described in these genes. Furthermore, mutations in a number of other genes, for example, mitochondrial genes [8] have been associated with HCM, albeit at a much lower frequency. Among the rare causes of HCM [9] are mutations in MYL3 which encodes the myosin essential light chain (ELC) of the sarcomere [4, 10–19]. The ELC is located at the lever arm of the myosin head and stabilises this region (Figure 1) through interaction with the IQ1 motif [20, 21] at aminoacid residues 781–810 [22] in beta myosin. The N-terminus of ELC interacts with actin [23]. Although the precise functional role of ELC has not been defined [24], the protein belongs to the EF-hand family of Ca2+-binding proteins [25] and appears to be involved in force development and fine tuning of muscle contraction [26, 27]. The phosphorylation of a C-terminal serine residue has
XMM-Newton Detection of a Comptonized Accretion Disc in the Quasar PKS0558-504
P. T. O'Brien,J. N. Reeves,M. J. L. Turner,K. A. Pounds,M. Page,M. Gliozzi,W. Brinkmann,J. B. Stephen,M. Dadina
Physics , 2000, DOI: 10.1051/0004-6361:20000215
Abstract: We present XMM-Newton observations of the bright quasar PKS0558-504. The 0.2-10 keV spectrum is dominated by a large, variable soft X-ray excess. The fastest flux variations imply accretion onto a Kerr black hole. The XMM-Newton data suggest the presence of a `big blue bump' in PKS0558-504 extending from the optical band to ~3 keV. The soft X-ray spectrum shows no evidence for significant absorption or emission-line features. The most likely explanation for the hot big blue bump is Comptonization by the multi-temperature corona of a thermal accretion disc running at a high accretion rate.
Erratum to “Stroke Survivors Scoring Zero on the NIH Stroke Scale Score Still Exhibit Significant Motor Impairment and Functional Limitation”
Brittany Hand,Stephen J. Page,Susan White
Stroke Research and Treatment , 2014, DOI: 10.1155/2014/542638
Abstract:
Stroke Survivors Scoring Zero on the NIH Stroke Scale Score Still Exhibit Significant Motor Impairment and Functional Limitation
Brittany Hand,Stephen J. Page,Susan White
Stroke Research and Treatment , 2014, DOI: 10.1155/2014/462681
Abstract: Objective. To determine the National Institutes of Health Stroke Scale’s (NIHSS’s) association with upper extremity (UE) impairment and functional outcomes. Design. Secondary, retrospective analysis of randomized controlled trial data. Setting. Not applicable. Participants. 146 subjects with stable, chronic stroke-induced hemiparesis. Intervention. The NIHSS, the UE Fugl-Meyer (FM), and the Arm Motor Ability Test (AMAT) were administered prior to their participation in a multicenter randomized controlled trial. Main Outcome Measures. The NIHSS, FM, and AMAT. Results. The association between the NIHSS and UE impairment was statistically significant but explained less than 4% of the variance among UE FM scores. The association between NIHSS total score and function as measured by the AMAT was not statistically significant . Subjects scoring a “zero” on the NIHSS exhibited discernible UE motor deficits and varied scores on the UE FM and AMAT. Conclusion. While being used in stroke trials, the NIHSS may have limited ability to discriminate between treatment responses, even when only a relatively narrow array of impairment levels exists among patients. Given these findings, NIHSS use should be restricted to acute stroke studies and clinical settings with the goal of reporting stroke severity. 1. Introduction Upper extremity (UE) hemiparesis remains one of the most frequent stroke-induced impairments [1] and considerably undermines performance of valued activities. Yet, despite weeks of rehabilitation, 50% of patients retain some degree of UE weakness [2] and up to seventy percent remain unable to functionally use their paretic UEs [3] in the months after stroke. Scores on the National Institute of Health Stroke Scale [4] (NIHSS) are associated with stroke outcomes [5–7], causing the NIHSS to be recommended for determining “appropriate treatment and predicting patient outcome” [8]. However, the “functional” measures with which the NIHSS has been associated in stroke trials [7, 9, 10] (e.g., Glasgow Coma Scale; Barthel Index) do not directly assess active UE movement or functional UE activity performance. For example, the Barthel Index ascertains the level of help that a patient requires to carry out various daily activities, but not the actual level of movement that the patient exhibits or how active movements conspire to facilitate participation in valued activities. These levels of help may be related to adaptive equipment use, available care partner support, or other factors, but do not tell the user how the client has actually responded to treatment
Faint NUV/FUV Standards from Swift/UVOT, GALEX and SDSS Photometry
Michael H. Siegel,Erik A. Hoversten,Peter W. A. Roming,Wayne B. Landsman,Carlos Allende Prieto,Alice A. Breeveld,Peter Brown,Stephen T. Holland,N. P. M. Kuin,Mathew J. Page,Daniel E. Vanden Berk
Physics , 2010, DOI: 10.1088/0004-637X/725/1/1215
Abstract: At present, the precision of deep ultraviolet photometry is somewhat limited by the dearth of faint ultraviolet standard stars. In an effort to improve this situation, we present a uniform catalog of eleven new faint (u sim17) ultraviolet standard stars. High-precision photometry of these stars has been taken from the Sloan Digital Sky Survey and Galaxy Evolution Explorer and combined with new data from the Swift Ultraviolet Optical Telescope to provide precise photometric measures extending from the Near Infrared to the Far Ultraviolet. These stars were chosen because they are known to be hot (20,000 < T_eff < 50,000 K) DA white dwarfs with published Sloan spectra that should be photometrically stable. This careful selection allows us to compare the combined photometry and Sloan spectroscopy to models of pure hydrogen atmospheres to both constrain the underlying properties of the white dwarfs and test the ability of white dwarf models to predict the photometric measures. We find that the photometry provides good constraint on white dwarf temperatures, which demonstrates the ability of Swift/UVOT to investigate the properties of hot luminous stars. We further find that the models reproduce the photometric measures in all eleven passbands to within their systematic uncertainties. Within the limits of our photometry, we find the standard stars to be photometrically stable. This success indicates that the models can be used to calibrate additional filters to our standard system, permitting easier comparison of photometry from heterogeneous sources. The largest source of uncertainty in the model fitting is the uncertainty in the foreground reddening curve, a problem that is especially acute in the UV.
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