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We analyze gene co-expression network under the random matrix theory framework. The nearest neighbor spacing distribution of the adjacency matrix of this network follows Gaussian orthogonal statistics of random matrix theory (RMT). Spectral…

Molecular Networks · Quantitative Biology 2015-05-18 Sarika Jalan , Norbert Solymosi , Gabör Vattay , Baowen Li

With the advance of high-throughput sequencing technologies, it has become feasible to investigate the influence of the entire spectrum of sequencing variations on complex human diseases. Although association studies utilizing the new…

Methodology · Statistics 2025-08-19 Ming Li , Zihuai He , Min Zhang , Xiaowei Zhan , Changshuai Wei , Robert C Elston , Qing Lu

Complete genome sequences contain valuable information about natural selection, but extracting this information for short, widely scattered noncoding elements remains a challenging problem. Here we introduce a new computational method for…

Genomics · Quantitative Biology 2015-03-19 Ilan Gronau , Leonardo Arbiza , Jaaved Mohammed , Adam Siepel

Reconstruction of population histories is a central problem in population genetics. Existing coalescent-based methods, like the seminal work of Li and Durbin (Nature, 2011), attempt to solve this problem using sequence data but have no…

Populations and Evolution · Quantitative Biology 2020-05-11 Younhun Kim , Frederic Koehler , Ankur Moitra , Elchanan Mossel , Govind Ramnarayan

What is a population? This review considers how a population may be defined in terms of understanding the structure of the underlying genetics of the individuals involved. The main approach is to consider statistically identifiable groups…

Populations and Evolution · Quantitative Biology 2013-06-05 Daniel John Lawson

Whole and targeted sequencing of human genomes is a promising, increasingly feasible tool for discovering genetic contributions to risk of complex diseases. A key step is calling an individual's genotype from the multiple aligned short read…

Applications · Statistics 2012-06-29 Baiyu Zhou , Alice S. Whittemore

In this paper, we consider a data matrix $X_N\in\mathbb{R}^{N\times p}$ where all the rows are i.i.d. samples in $\mathbb{R}^p$ of mean zero and covariance matrix $\Sigma\in\mathbb{R}^{p\times p}$. Here the population matrix $\Sigma$ is of…

Probability · Mathematics 2013-05-06 Dai Shi

Population stratification is a problem encountered in several areas of biology and public health. We tackle this problem by mapping a population and its elements attributes into a hypergraph, a natural extension of the concept of graph or…

Populations and Evolution · Quantitative Biology 2009-11-13 Alexei Vazquez

Network surveys of key populations at risk for HIV are an essential part of the effort to understand how the epidemic spreads and how it can be prevented. Estimation of population values from the sample data has been probematical, however,…

Applications · Statistics 2019-09-12 Steve Thompson

Population genetic studies have found evidence for dramatic population growth in recent human history. It is unclear how this recent population growth, combined with the effects of negative natural selection, has affected patterns of…

Populations and Evolution · Quantitative Biology 2014-02-11 Kirk E. Lohmueller

In this paper we propose a method and discuss its computational implementation as an integrated tool for the analysis of viral genetic diversity on data generated by high-throughput sequencing. Most methods for viral diversity estimation…

In genetic studies of complex diseases, the underlying mode of inheritance is often not known. Thus, the most powerful test or other optimal procedure for one model, e.g. recessive, may be quite inefficient if another model, e.g. dominant,…

Statistics Theory · Mathematics 2007-06-13 Gang Zheng , Boris Freidlin , Joseph L. Gastwirth

The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical…

Methodology · Statistics 2016-09-29 Marco Scutari , Ian Mackay , David Balding

It is of great interest to quantify the contributions of genetic variation to brain structure and function, which are usually measured by high-dimensional imaging data (e.g., magnetic resonance imaging). In addition to the variance, the…

Applications · Statistics 2020-05-05 Benjamin B. Risk , Hongtu Zhu

Studying physiology over a broad population for long periods of time is difficult primarily because collecting human physiologic data is intrusive, dangerous, and expensive. Electronic health record (EHR) data promise to support the…

Quantitative Methods · Quantitative Biology 2015-05-30 DJ Albers , George Hripcsak , Michael Schmidt

Eliciting preferences from human judgements is inherently imprecise, yet most decision analysis methods force a single priority vector from pairwise comparisons, discarding the information embedded in inconsistencies. We instead leverage…

General Economics · Economics 2026-02-27 Salvatore Greco , Sajid Siraj , Michele Lundy

We develop a general modelling framework for compartmental epidemiological systems structured by continuous variables which are linked to the levels of expression of compartment-specific traits. We start by formulating an individual-based…

Populations and Evolution · Quantitative Biology 2025-08-14 Emanuele Bernardi , Tommaso Lorenzi , Mattia Sensi , Andrea Tosin

Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for analysis of gene expression. By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer…

Methodology · Statistics 2011-06-17 Julia Salzman , Hui Jiang , Wing Hung Wong

We consider the hypothesis that Evolution promotes population-wide genome patterns that, under randomization, ensures the External Validity of adaptations across population members. An adaptation is Externally Valid (EV) if its effect holds…

Populations and Evolution · Quantitative Biology 2021-08-17 Andre F. Ribeiro

Genetic data are often used to infer demographic history and changes or detect genes under selection. Inferential methods are commonly based on models making various strong assumptions: demography and population structures are supposed…

Populations and Evolution · Quantitative Biology 2020-07-28 Clotilde Lepers , Sylvain Billiard , Matthieu Porte , Sylvie Méléard , Viet Chi Tran