Abstract This article focuses on conducting global testing for association between a binary trait and set of rare variants (RVs), although its application can be much broader to other types traits, common (CVs), gene or pathway analysis. We show that many the existing tests have deteriorating performance in presence nonassociated RVs: their power dramatically drop as proportion RVs group tested increases. propose class so-called sum powered score (SPU) tests, each which is based vector from...

We study the problem of testing for single marker-multiple phenotype associations based on genome-wide association (GWAS) summary statistics without access to individual-level genotype and data. For most published GWASs, because obtaining data is substantially easier than accessing data, while often multiple correlated traits have been collected, studied here has become increasingly important. propose a powerful adaptive test compare its performance with some existing tests. illustrate...

There is increasing interest in investigating how the compositions of microbial communities are associated with human health and disease. Although existing methods have identified many associations, a proper choice phylogenetic distance critical for power these methods. To assess an overall association between composition community outcome interest, we present novel multivariate testing method called aMiSPU, that joint highly adaptive over all observed taxa thus high powered across various...

Abstract Background The estimation of microbial networks can provide important insight into the ecological relationships among organisms that comprise microbiome. However, there are a number critical statistical challenges in inference such from high-throughput data. Since abundances each sample constrained to have fixed sum and is incomplete overlap populations across subjects, data both compositional zero-inflated. Results We propose COmpositional Zero-Inflated Network Estimation (COZINE)...

Testing for genetic association with multiple traits has become increasingly important, not only because of its potential to boost statistical power, but also direct relevance applications. For example, there is accumulating evidence showing that some complex neurodegenerative and psychiatric diseases like Alzheimer's disease are due disrupted brain networks, which it would be natural identify variants associated a network, represented as set traits, one each regions interest. In spite...

Resting-state functional magnetic resonance imaging allows one to study brain connectivity, partly motivated by evidence that patients with complex disorders, such as Alzheimer's disease, may have altered connectivity patterns compared healthy subjects. A network describes statistical associations of the neural activities among distinct and distant regions. Recently, there is a major interest in group-level analysis; however, relative lack studies on inference, significance testing for group...

Hypoglycemia-associated autonomic failure (HAAF) limits the ability of patients with diabetes to achieve target glycemia. Animal models have provided insights into pathogenesis HAAF, but a robust human model HAAF in which recurrent hypoglycemia impacts counterregulatory responses days later is lacking. The aim this study was determine impact two or three episodes moderate on subsequent induced 5 later. Six healthy subjects participated each protocols. In both protocol 1 and 2, underwent...

Resting-state functional magnetic resonance imaging (rs-fMRI) and other technologies have been offering evidence insights showing that altered brain networks are associated with neurological illnesses such as Alzheimer's disease. Exploring of clinical populations compared to those controls would be a key inquiry reveal underlying processes related illnesses. For purpose, group-level inference is necessary first step in order establish whether there any genuinely disrupted subnetworks. Such...

A neuromorphic core utilizing logic-compatible embedded flash technology for storing multi-level synaptic weights is demonstrated in a 65nm standard CMOS process. carefully-designed program-verify sequence along with bitline voltage regulation scheme allows the individual cell currents to be programmed precisely. This makes it possible enable large number of rows parallel without impacting current summation accuracy. Furthermore, eflash based synapses are non-volatile and hence consumes zero...

The metamaterial structure composed of cubic high dielectric resonators periodically arrayed in a low substrate is analysed and flat lens used to improve the gain rectangular patch antenna. A slab also discussed compared with lens. Experimental results show that proposed can antenna remarkably at both first third resonant mode.

The effects of streamwise convex curvature, recovery, and free-stream turbulence intensity on the turbulent transport heat momentum in a mature boundary layer are investigated. A special three-wire hot-wire probe developed for this purpose is described. Two cases with levels 0.68 2.0 percent, taken same facility moderate strength δ/R = 0.03, compared. Profiles u′v′, t′, u′t′, v′t′ dramatically reduced within curve, asymptotic profiles being achieved quickly low TI case. Recovery occurs...

There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging studies. Most of existing methods treat a single trait or traits response while treating an SNP predictor coded under additive inheritance mode. In this paper, we follow earlier approach ordinal predictors proportional odds model (POM). way, it is not only easier handle mixed types e.g., some quantitative binary, but...

Abstract Single genome‐wide studies may be underpowered to detect trait‐associated rare variants with moderate or weak effect sizes. As a viable alternative, meta‐analysis is widely used increase power by combining different studies. The of critically depends on the underlying association patterns and heterogeneity levels, which are unknown vary from locus locus. However, existing methods mainly focus one only few combinations pattern level, thus lose in many situations. To address this...

Summary Hub nodes within biological networks play a pivotal role in determining phenotypes and disease outcomes. In the multiple network setting, we are interested understanding similarities differences across different experimental conditions or subtypes of disease. The majority proposed approaches for joint modeling focus on sharing edges graphs. Rather than assuming driven by individual edges, instead presence common hub nodes, which more likely to be preserved settings. Specifically,...

Pharmaceutical researchers are continually searching for techniques to improve both drug development processes and patient outcomes. An area of recent interest is the potential machine learning (ML) applications within pharmacology. One such application not yet given close study unsupervised clustering plasma concentration-time curves, hereafter, pharmacokinetic (PK) curves. In this paper, we present our findings on how cluster PK curves by their similarity. Specifically, find be effective...

With the advent of high-throughput sequencing, an efficient computing strategy is required to deal with large genomic data sets. The challenge estimating a precision matrix has garnered substantial research attention for its direct application discriminant analyses and graphical models. Most existing methods either use lasso-type penalty that may lead biased estimators or are computationally intensive, which prevents their applications very graphs. We propose using L0 estimate ultra-large...

Free-stream turbulence intensity effects on a convex-curved turbulent boundary layer are investigated. An attached fully is grown flat plate and then introduced to downstream section where the test wall convexly curved, having constant radius of curvature. Two cases, with free-stream intensities 1.85 0.65 percent, discussed. They were taken in same facility strength curvature, δ/R = 0.03−0.045. The two cases have similar flow conditions upon entry curve, thus separating under study from...

Pharmaceutical researchers are continually searching for techniques to improve both drug development processes and patient outcomes. An area of recent interest is the potential machine learning (ML) applications within pharmacology. One such application not yet given close study unsupervised clustering plasma concentration-time curves, hereafter, pharmacokinetic (PK) curves. In this paper, we present our findings on how cluster PK curves by their similarity. Specifically, find be effective...