Whitney, David Yamanashi Leib, Allison
To understand visual consciousness, we must understand how the brain represents ensembles of objects at many levels of perceptual analysis. Ensemble perception refers to the visual system's ability to extract summary statistical information from groups of similar objects—often in a brief glance. It defines foundational limits on cognition, memory, ...
Vandenplas, Jeremie Calus, Mario Gorjanc, Gregor
This study presents a method for genomic prediction that uses individual-level data and summary statistics from multiple populations. Genome-wide markers are nowadays widely used to predict complex traits, and genomic prediction using multi-population data are an appealing approach to achieve higher prediction accuracies. However, sharing of indivi...
Zhang, Zhe Ma, Peipei Li, Qiumeng Xiao, Qian Sun, Hao Olasege, Babatunde Shittu Wang, Qishan Pan, Yuchun
Published in
Frontiers in genetics
The relationship between growth and immune phenotypes has been presented in the context of physiology and energy allocation theory, but has rarely been explained genetically in humans. As more summary statistics of genome-wide association studies (GWAS) become available, it is increasingly possible to explore the genetic relationship between traits...
Whitney, David Yamanashi Leib, Allison
To understand visual consciousness, we must understand how the brain represents ensembles of objects at many levels of perceptual analysis. Ensemble perception refers to the visual system's ability to extract summary statistical information from groups of similar objects-often in a brief glance. It defines foundational limits on cognition, memory, ...
Ray, Debashree Boehnke, Michael
Published in
Genetic epidemiology
Genome-wide association studies (GWAS) for complex diseases have focused primarily on single-trait analyses for disease status and disease-related quantitative traits. For example, GWAS on risk factors for coronary artery disease analyze genetic associations of plasma lipids such as total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycer...
Zhou, Xiang
Published in
The annals of applied statistics
Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs-the restricted maximum likelihood estimation method (REML)-suffers from several important drawbacks: REML requires individual-level genotypes and phenotypes from all samples in th...
Coeurjolly, Jean-François Møller, Jesper Waagepetersen, Rasmus
This tutorial provides an introduction to Palm distributions for spatial point processes. Initially, in the context of finite point processes, we give an explicit definition of Palm distributions in terms of their density functions. Then we review Palm distributions in the general case. Finally we discuss some examples of Palm distributions for spe...
Piazza, Elise A Iordan, Marius Cătălin Lew-Williams, Casey
Published in
Current biology : CB
The voice is the most direct link we have to others' minds, allowing us to communicate using a rich variety of speech cues [1, 2]. This link is particularly critical early in life as parents draw infants into the structure of their environment using infant-directed speech (IDS), a communicative code with unique pitch and rhythmic characteristics re...
Chetverikov, Andrey Campana, Gianluca Kristjánsson, Árni
Published in
Psychological science
Colors are rarely uniform, yet little is known about how people represent color distributions. We introduce a new method for studying color ensembles based on intertrial learning in visual search. Participants looked for an oddly colored diamond among diamonds with colors taken from either uniform or Gaussian color distributions. On test trials, th...
Daly, Aidan C Cooper, Jonathan Gavaghan, David J Holmes, Chris
Published in
Journal of the Royal Society, Interface
Bayesian methods are advantageous for biological modelling studies due to their ability to quantify and characterize posterior variability in model parameters. When Bayesian methods cannot be applied, due either to non-determinism in the model or limitations on system observability, approximate Bayesian computation (ABC) methods can be used to simi...