Classes of Multiple Decision Functions Strongly Controlling FWER and FDR

This paper provides two general classes of multiple decision functions where each member of the first class strongly controls the family-wise error rate (FWER), while each member of the second class strongly controls the false discovery rate (FDR). These classes offer the possibility that an optimal multiple decision function with respect to a pre-specified criterion, such as the missed discovery rate (MDR), could be found within these classes. Such multiple decision functions can be utilized in multiple testing, specifically, but not limited to, the analysis of high-dimensional microarray data sets.Comment: 19 page

Data-driven prediction of vortex-induced vibration response of marine risers subjected to three-dimensional current

Slender marine structures such as deep-water marine risers are subjected to currents and will normally experience Vortex Induced Vibrations (VIV), which can cause fast accumulation of fatigue damage. The ocean current is often three-dimensional (3D), i.e., the direction and magnitude of the current vary throughout the water column. Today, semi-empirical tools are used by the industry to predict VIV induced fatigue on risers. The load model and hydrodynamic parameters in present VIV prediction tools are developed based on two-dimensional (2D) flow conditions, as it is challenging to consider the effect of 3D flow along the risers. Accordingly, the current profiles must be purposely made 2D during the design process, which leads to significant uncertainty in the prediction results. Further, due to the limitations in the laboratory, VIV model tests are mostly carried out under 2D flow conditions and thus little experimental data exist to document VIV response of riser subjected to varying directions of the current. However, a few experiments have been conducted with 3D current. We have used results from one of these experiments to investigate how well 1) traditional and 2) an alternative method based on a data driven prediction can describe VIV in 3D currents. Data driven modelling is particularly suited for complicated problems with many parameters and non-linear relationships. We have applied a data clustering algorithm to the experimental 3D flow data in order to identify measurable parameters that can influence responses. The riser responses are grouped based on their statistical characteristics, which relate to the direction of the flow. Furthermore we fit a random forest regression model to the measured VIV response and compare its performance with the predictions of existing VIV prediction tools (VIVANA-FD).Comment: 12 pages, presented at Norwegian AI Society Symposium 2019, accepted for publication in Springer Conference Proceeding

Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes

<p>Abstract</p> <p>Background</p> <p>In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases.</p> <p>Results</p> <p>This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevance-shifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error rate. Whereas the shift of the null hypothesis alone would give straight-forward solutions, the problems that are the reason for the empirical considerations discussed here arise by the fact that the shift is considered in both directions and the whole parameter space in between these two limits has to be accepted as null hypothesis.</p> <p>Conclusion</p> <p>The first algorithm to be discussed uses a permutation algorithm, and is appropriate for designs with a moderately large number of observations. However, many experiments have limited sample sizes. Then the second procedure might be more appropriate, where multiplicity is corrected according to a concept of data-driven order of hypotheses.</p

Sample size calculation for microarray experiments with blocked one-way design

<p>Abstract</p> <p>Background</p> <p>One of the main objectives of microarray analysis is to identify differentially expressed genes for different types of cells or treatments. Many statistical methods have been proposed to assess the treatment effects in microarray experiments.</p> <p>Results</p> <p>In this paper, we consider discovery of the genes that are differentially expressed among <it>K </it>(> 2) treatments when each set of <it>K </it>arrays consists of a block. In this case, the array data among <it>K </it>treatments tend to be correlated because of block effect. We propose to use the blocked one-way ANOVA <it>F</it>-statistic to test if each gene is differentially expressed among <it>K </it>treatments. The marginal p-values are calculated using a permutation method accounting for the block effect, adjusting for the multiplicity of the testing procedure by controlling the false discovery rate (FDR). We propose a sample size calculation method for microarray experiments with a blocked one-way design. With FDR level and effect sizes of genes specified, our formula provides a sample size for a given number of true discoveries.</p> <p>Conclusion</p> <p>The calculated sample size is shown via simulations to provide an accurate number of true discoveries while controlling the FDR at the desired level.</p

Prenatal Polycyclic Aromatic Hydrocarbon (PAH) Exposure and Child Behavior at Age 6–7 Years

Background: Airborne polycyclic aromatic hydrocarbons (PAH) are widespread urban air pollutants from fossil fuel burning and other combustion sources. We previously reported that a broad spectrum of combustion-related DNA adducts in cord blood was associated with attention problems at 6–7 years of age in the Columbia Center for Children’s Environmental Health (CCCEH) longitudinal cohort study

Robust test method for time-course microarray experiments

<p>Abstract</p> <p>Background</p> <p>In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectories of the gene-expression profiles. For many of these experiments, the scientific aim is the identification of genes for which the trajectories depend on an experimental or phenotypic factor. There is an extensive recent body of literature on statistical methodology for addressing this analytical problem. Most of the existing methods are based on estimating the time-course trajectories using parametric or non-parametric mean regression methods. The sensitivity of these regression methods to outliers, an issue that is well documented in the statistical literature, should be of concern when analyzing microarray data.</p> <p>Results</p> <p>In this paper, we propose a robust testing method for identifying genes whose expression time profiles depend on a factor. Furthermore, we propose a multiple testing procedure to adjust for multiplicity.</p> <p>Conclusions</p> <p>Through an extensive simulation study, we will illustrate the performance of our method. Finally, we will report the results from applying our method to a case study and discussing potential extensions.</p

Rpgrip1 is required for rod outer segment development and ciliary protein trafficking in zebrafish

The authors would like to thank the Royal Society of London, the National Eye Research Centre, the Visual Research Trust, Fight for Sight, the W.H. Ross Foundation, the Rosetrees Trust, and the Glasgow Children’s Hospital Charity for supporting this work. This work was also supported by the Deanship of Scientific Research at King Saud University for funding this research (Research Project) grant number ‘RGP – VPP – 219’.Mutations in the RPGR-interacting protein 1 (RPGRIP1) gene cause recessive Leber congenital amaurosis (LCA), juvenile retinitis pigmentosa (RP) and cone-rod dystrophy. RPGRIP1 interacts with other retinal disease-causing proteins and has been proposed to have a role in ciliary protein transport; however, its function remains elusive. Here, we describe a new zebrafish model carrying a nonsense mutation in the rpgrip1 gene. Rpgrip1homozygous mutants do not form rod outer segments and display mislocalization of rhodopsin, suggesting a role for RPGRIP1 in rhodopsin-bearing vesicle trafficking. Furthermore, Rab8, the key regulator of rhodopsin ciliary trafficking, was mislocalized in photoreceptor cells of rpgrip1 mutants. The degeneration of rod cells is early onset, followed by the death of cone cells. These phenotypes are similar to that observed in LCA and juvenile RP patients. Our data indicate RPGRIP1 is necessary for rod outer segment development through regulating ciliary protein trafficking. The rpgrip1 mutant zebrafish may provide a platform for developing therapeutic treatments for RP patients.Publisher PDFPeer reviewe

Study of intermediate velocity products in the Ar+Ni collisions between 52 and 95 A.MeV

Intermediate velocity products in Ar+Ni collisions from 52 to 95 A.MeV are studied in an experiment performed at the GANIL facility with the 4$\pi$ multidetector INDRA. It is shown that these emissions cannot be explained by statistical decays of the quasi-projectile and the quasi-target in complete equilibrium. Three methods are used to isolate and characterize intermediate velocity products. The total mass of these products increases with the violence of the collision and reaches a large fraction of the system mass in mid-central collisions. This mass is found independent of the incident energy, but strongly dependent on the geometry of the collision. Finally it is shown that the kinematical characteristics of intermediate velocity products are weakly dependent on the experimental impact parameter, but strongly dependent on the incident energy. The observed trends are consistent with a participant-spectator like scenario or with neck emissions and/or break-up.Comment: 37 pages, 13 figure

Measurements of sideward flow around the balance energy

Sideward flow values have been determined with the INDRA multidetector for Ar+Ni, Ni+Ni and Xe+Sn systems studied at GANIL in the 30 to 100 A.MeV incident energy range. The balance energies found for Ar+Ni and Ni+Ni systems are in agreement with previous experimental results and theoretical calculations. Negative sideward flow values have been measured. The possible origins of such negative values are discussed. They could result from a more important contribution of evaporated particles with respect to the contribution of promptly emitted particles at mid-rapidity. But effects induced by the methods used to reconstruct the reaction plane cannot be totally excluded. Complete tests of these methods are presented and the origins of the ``auto-correlation'' effect have been traced back. For heavy fragments, the observed negative flow values seem to be mainly due to the reaction plane reconstruction methods. For light charged particles, these negative values could result from the dynamics of the collisions and from the reaction plane reconstruction methods as well. These effects have to be taken into account when comparisons with theoretical calculations are done.Comment: 27 pages, 15 figure