Detecting differential usage of exons from RNA-Seq data

RNA-Seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires comparisons between treatments, tissues or conditions. For the analysis of such experiments, we present _DEXSeq_, a statistical method to test for differential exon usage in RNA-Seq data. _DEXSeq_ employs generalized linear models and offers good detection power and reliable control of false discoveries by taking biological variation into account. An implementation is available as an R/Bioconductor package

Statistical theory of relaxation of high energy electrons in quantum Hall edge states

We investigate theoretically the energy exchange between electrons of two co-propagating, out-of-equilibrium edge states with opposite spin polarization in the integer quantum Hall regime. A quantum dot tunnel-coupled to one of the edge states locally injects electrons at high energy. Thereby a narrow peak in the energy distribution is created at high energy above the Fermi level. A second downstream quantum dot performs an energy resolved measurement of the electronic distribution function. By varying the distance between the two dots, we are able to follow every step of the energy exchange and relaxation between the edge states - even analytically under certain conditions. In the absence of translational invariance along the edge, e.g. due to the presence of disorder, energy can be exchanged by non-momentum conserving two-particle collisions. For weakly broken translational invariance, we show that the relaxation is described by coupled Fokker-Planck equations. From these we find that relaxation of the injected electrons can be understood statistically as a generalized drift-diffusion process in energy space for which we determine the drift-velocity and the dynamical diffusion parameter. Finally, we provide a physically appealing picture in terms of individual edge state heating as a result of the relaxation of the injected electrons.Comment: 13 pages plus 6 appendices, 8 figures. Supplemental Material can be found on http://quantumtheory.physik.unibas.ch/people/nigg/supp_mat.htm

Escaping the Under-Reform Trap

Most former Soviet republics have fallen into an economic and political under-reform trap. An intrusive state imposes high tax rates and drives entrepreneurs into the unofficial economy, which further aggravates the pressure on official businessmen. Tax revenues and public goods dwindle, further reducing incentives to register business activity. This economic under-reform trap has a political counterpart. Remarkably, Communist parties remain popular and opposed to establishing the rule of law precisely in those places where they were able to delay and derail reform. No electoral backlash prompts the reforms necessary to leave the under-reform trap. The best way out of the trap in countries such as Russia and Ukraine is increased economic and political competition among the elite. Copyright 2002, International Monetary Fund

Interaction induced edge channel equilibration

The electronic distribution functions of two Coulomb coupled chiral edge states forming a quasi-1D system with broken translation invariance are found using the equation of motion approach. We find that relaxation and thereby energy exchange between the two edge states is determined by the shot noise of the edge states generated at a quantum point contact (QPC). In close vicinity to the QPC, we derive analytic expressions for the distribution functions. We further give an iterative procedure with which we can compute numerically the distribution functions arbitrarily far away from the QPC. Our results are compared with recent experiments of Le Sueur et al..Comment: 10 pages, 7 figures, includes 5 pages of supplementary informatio

Effects of abandonment on plant diversity in seminatural grasslands along soil and climate gradients

Questions: What are the effects of abandonment on plant diversity in semi-natural grasslands? Do the effects of abandonment on taxonomic and functional diversity vary along environmental gradients of climate and soil? Location: West and mid-Norway. Methods: Plant composition was surveyed in 110 subplots of 4 m2 in 14 sites across grazed and abandoned semi-natural grasslands. Climate data were extracted and soil composition analysed. To reduce the number of explanatory variables and deal with collinearity, we performed PCA. Data on the plant species vegetative height (H), leaf dry matter content (LDMC), specific leaf area (SLA), seed mass (SM) and number of seeds per plant (SNP) for 175 species were extracted from the LEDA database. Measures of plant diversity (species richness, CWM of functional traits and functional diversity (evenness and range)) were calculated for each subplot. To estimate the effects of abandonment on plant diversity and examine how these effects are moderated by gradients in soil and climate, we fitted mixed models to the data including site as a random effect. Results: Species richness in the subplots was lower in abandoned semi-natural grasslands, especially on more calcareous soils. CWM H, LDMC and SM were higher in abandoned semi-natural grasslands. CWM LDMC was only higher in the driest subplots. The ranges in H, SLA and SM, as well as evenness in LDMC were also higher in abandoned semi-natural grasslands, but the range in LDMC was lower. Conclusions: It is important to assess both taxonomic and functional diversity to understand ecosystem processes. The species pool in ecosystems influenced by a long history of intermediate grazing includes a high proportion of low stature, grazing-tolerant plant species. Abandonment of extensive land-use practices will cause a decline in taxonomic diversity (plant species richness) in such systems due to increased abundance of plants with high stature that outcompete the lower, grazing-tolerant plants. This process is predominant especially if moisture, soil fertility and pH are at intermediate levels. Changes in species communities due to abandonment will also influence ecosystem functioning, such as nutrient turnover and fodder production resilience. (Résumé d'auteur

Unfolding times for proteins in a force clamp

The escape process from the native valley for proteins subjected to a constant stretching force is examined using a model for a Beta-barrel. For a wide range of forces, the unfolding dynamics can be treated as one-dimensional diffusion, parametrized in terms of the end-to-end distance. In particular, the escape times can be evaluated as first passage times for a Brownian particle moving on the protein free-energy landscape, using the Smoluchowski equation. At strong forces, the unfolding process can be viewed as a diffusive drift away from the native state, while at weak forces thermal activation is the relevant mechanism. An escape-time analysis within this approach reveals a crossover from an exponential to an inverse Gaussian escape-time distribution upon passing from weak to strong forces. Moreover, a single expression valid at weak and strong forces can be devised both for the average unfolding time as well as for the corresponding variance. The analysis offers a possible explanation of recent experimental findings for ddFLN4 and ubiquitin.Comment: 6 pages, 4 figures, submitted for pubblication to Physical Review Letter

A Novel Model-Free Data Analysis Technique Based on Clustering in a Mutual Information Space: Application to Resting-State fMRI

Non-parametric data-driven analysis techniques can be used to study datasets with few assumptions about the data and underlying experiment. Variations of independent component analysis (ICA) have been the methods mostly used on fMRI data, e.g., in finding resting-state networks thought to reflect the connectivity of the brain. Here we present a novel data analysis technique and demonstrate it on resting-state fMRI data. It is a generic method with few underlying assumptions about the data. The results are built from the statistical relations between all input voxels, resulting in a whole-brain analysis on a voxel level. It has good scalability properties and the parallel implementation is capable of handling large datasets and databases. From the mutual information between the activities of the voxels over time, a distance matrix is created for all voxels in the input space. Multidimensional scaling is used to put the voxels in a lower-dimensional space reflecting the dependency relations based on the distance matrix. By performing clustering in this space we can find the strong statistical regularities in the data, which for the resting-state data turns out to be the resting-state networks. The decomposition is performed in the last step of the algorithm and is computationally simple. This opens up for rapid analysis and visualization of the data on different spatial levels, as well as automatically finding a suitable number of decomposition components

Grid-enabling FIRST: Speeding up simulation applications using WinGrid

The vision of grid computing is to make computational power, storage capacity, data and applications available to users as readily as electricity and other utilities. Grid infrastructures and applications have traditionally been geared towards dedicated, centralized, high performance clusters running on UNIX flavour operating systems (commonly referred to as cluster-based grid computing). This can be contrasted with desktop-based grid computing which refers to the aggregation of non-dedicated, de-centralized, commodity PCs connected through a network and running (mostly) the Microsoft Windowstrade operating system. Large scale adoption of such Windowstrade-based grid infrastructure may be facilitated via grid-enabling existing Windows applications. This paper presents the WinGridtrade approach to grid enabling existing Windowstrade based commercial-off-the-shelf (COTS) simulation packages (CSPs). Through the use of a case study developed in conjunction with Ford Motor Company, the paper demonstrates how experimentation with the CSP Witnesstrade and FIRST can achieve a linear speedup when WinGridtrade is used to harness idle PC computing resources. This, combined with the lessons learned from the case study, has encouraged us to develop the Web service extensions to WinGridtrade. It is hoped that this would facilitate wider acceptance of WinGridtrade among enterprises having stringent security policies in place

Cardiovascular magnetic resonance evaluation of effusive and constrictive physiologies

This thesis presents an exploration of cardiovascular magnetic resonance (CMR) in the evaluation of effusive and constrictive heart conditions. Central to the thesis is advanced CMR as a diagnostic tool in pericardial effusion and constrictive pericarditis. Studies I and II concern the application of T1 mapping for the characterization of pleural and pericardial effusions and attempts to enhance the understanding of the dynamics of extracellular gadolinium-based contrast agents (GBCA) in effusion fluid. Study II establishes normal T1 values at 1.5 T in the pericardial fluid of healthy individuals, providing a benchmark for future studies. Studies III and IV concern ventricular interdependence, a crucial aspect in evaluating constrictive physiology. Ventricular interdependence is measured by quantifying the respiratory variation in peak early transvalvular blood flow velocities. In Study III, an open-source software tool to perform semi-automated image analysis of real-time phase contrast (RT-PC) images is developed, and normal values are established. In Study IV, the repeatability and reproducibility of the method are tested. This thesis concludes that CMR can become a valuable tool in evaluating pericardial effusion and constrictive pericarditis. Both molecular imaging evaluation of effusive fluids and hemodynamic assessment of ventricular interdependence are feasible using CMR