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The human brain has a complex, intricate functional architecture. While many studies primarily emphasize pairwise interactions, delving into high-order associations is crucial for a comprehensive understanding of how functional brain…

Neurons and Cognition · Quantitative Biology 2023-10-30 Qiang Li , Vince D. Calhoun , Adithya Ram Ballem , Shujian Yu , Jesus Malo , Armin Iraji

From longitudinal biomedical studies to social networks, graphs have emerged as a powerful framework for describing evolving interactions between agents in complex systems. In such studies, after pre-processing, the data can be represented…

Applications · Statistics 2018-03-12 Claire Donnat , Susan Holmes

We study an independence test based on distance correlation for random fields $(X,Y)$. We consider the situations when $(X,Y)$ is observed on a lattice with equidistant grid sizes and when $(X,Y)$ is observed at random locations. We provide…

Statistics Theory · Mathematics 2022-05-05 Muneya Matsui , Thomas Mikosch , Rasool Roozegar , Laleh Tafakori

Genetic interactions can strongly influence the fitness effects of individual mutations, yet the impact of these epistatic interactions on evolutionary dynamics remains poorly understood. Here we investigate the evolutionary role of…

Populations and Evolution · Quantitative Biology 2014-11-14 Benjamin H. Good , Michael M. Desai

Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), the signals identified by association analysis may not have specific pathological relevance to diseases so…

Genomics · Quantitative Biology 2019-07-19 Rong Jiao , Xiangning Chen , Eric Boerwinkle , Momiao Xiong

In many applications, hypothesis testing is based on an asymptotic distribution of statistics. The aim of this paper is to clarify and extend multiple correction procedures when the statistics are asymptotically Gaussian. We propose a…

Statistics Theory · Mathematics 2020-07-03 Sophie Achard , Pierre Borgnat , Irène Gannaz

Building upon the Chatterjee correlation (2021: J. Am. Stat. Assoc. 116, p2009) for two real-valued variables, this study introduces a generalized measure of directed association between two vector variables, real or complex-valued, and of…

Methodology · Statistics 2024-06-26 Roberto D. Pascual-Marqui , Kieko Kochi , Toshihiko Kinoshita

Many complex diseases are known to be affected by the interactions between genetic variants and environmental exposures beyond the main genetic and environmental effects. Study of gene-environment (G$\times$E) interactions is important for…

Methodology · Statistics 2019-10-01 Jie Ren , Fei Zhou , Xiaoxi Li , Qi Chen , Hongmei Zhang , Shuangge Ma , Yu Jiang , Cen Wu

We propose a method that uses genetic data to test for the occurrence of a recent range expansion and to infer the location of the origin of the expansion. We introduce a statistic for pairs of populations $\psi$ (the directionality index)…

Populations and Evolution · Quantitative Biology 2013-04-01 Benjamin M Peter , Montgomery Slatkin

Recently, the SPIKE-distance has been proposed as a parameter-free and time-scale independent measure of spike train synchrony. This measure is time-resolved since it relies on instantaneous estimates of spike train dissimilarity. However,…

Data Analysis, Statistics and Probability · Physics 2012-12-11 Thomas Kreuz , Daniel Chicharro , Conor Houghton , Ralph G Andrzejak , Florian Mormann

Test of independence plays a fundamental role in many statistical techniques. Among the nonparametric approaches, the distance-based methods (such as the distance correlation based hypotheses testing for independence) have numerous…

Methodology · Statistics 2017-01-24 Cheng Huang , Xiaoming Huo

Studying the effects of groups of Single Nucleotide Polymorphisms (SNPs), as in a gene, genetic pathway, or network, can provide novel insight into complex diseases, above that which can be gleaned from studying SNPs individually. Common…

Applications · Statistics 2017-10-12 Ryan Sun , Xihong Lin

Qualitative interactions occur when a treatment effect or measure of association varies in sign by sub-population. Of particular interest in many biomedical settings are absence/presence qualitative interactions, which occur when an effect…

Methodology · Statistics 2020-10-20 Aaron Hudson , Ali Shojaie

In this work we study reverse complementary genomic word pairs in the human DNA, by comparing both the distance distribution and the frequency of a word to those of its reverse complement. Several measures of dissimilarity between distance…

Distance multivariance is a multivariate dependence measure, which can detect dependencies between an arbitrary number of random vectors each of which can have a distinct dimension. Here we discuss several new aspects, present a concise…

Statistics Theory · Mathematics 2020-04-17 Björn Böttcher

In genetic association studies, rare variants with extremely small allele frequency play a crucial role in complex traits, and the set-based testing methods that jointly assess the effects of groups of single nucleotide polymorphisms (SNPs)…

Methodology · Statistics 2020-03-13 Shonosuke Sugasawa , Hisashi Noma

The standard paradigm for the analysis of genome-wide association studies involves carrying out association tests at both typed and imputed SNPs. These methods will not be optimal for detecting the signal of association at SNPs that are not…

Large case/control Genome-Wide Association Studies (GWAS) often include groups of related individuals with known relationships. When testing for associations at a given locus, current methods incorporate only the familial relationships…

Applications · Statistics 2014-08-01 Joshua N. Sampson , Bill Wheeler , Peng Li , Jianxin Shi

In his seminal work, Chatterjee (2021) introduced a novel correlation measure which is distribution-free, asymptotically normal, and consistent against all alternatives. In this paper, we study the probabilistic relationships between…

Methodology · Statistics 2023-02-21 Qingyang Zhang

Finding interdependency relations between (possibly multivariate) time series provides valuable knowledge about the processes that generate the signals. Information theory sets a natural framework for non-parametric measures of several…

Information Theory · Computer Science 2016-02-09 German Gomez-Herrero , Wei Wu , Kalle Rutanen , Miguel C. Soriano , Gordon Pipa , Raul Vicente