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Objective: SNP heritability estimates vary substantially across estimation strategies, yet the downstream consequences for polygenic risk score (PRS) construction remain poorly characterised. We systematically benchmarked heritability…

Genomics · Quantitative Biology 2026-04-06 Muhammad Muneeb , David B. Ascher

Drug development is a very costly and lengthy process, while repositioned or repurposed drugs could be brought into clinical practice within a shorter time-frame and at a much reduced cost. The past decade has observed a massive growth in…

Genomics · Quantitative Biology 2019-11-14 Alexandria Lau , Hon-Cheong So

Pulsar searching with next-generation radio telescopes requires efficiently sifting through millions of candidates generated by search pipelines to identify the most promising ones. This challenge has motivated the utilization of Artificial…

Instrumentation and Methods for Astrophysics · Physics 2025-11-11 Qiuyang Fu , Mengyao Xue , Weiwei Zhu , N. D. R. Bhat , Kaichao Wu , Zihan Zhang , B. W. Meyers , Chia Min Tan , Youling Yue , Jiarui Niu , Lingqi Meng , Ziwei Wu , Ziyao Fang , Yukai Zhou , Jiawei Jin

The development and generation of synthetic data are becoming increasingly vital in the field of statistical disclosure control. The PSInference package provides tools to perform exact inferential analysis on singly imputed synthetic data…

Methodology · Statistics 2025-03-20 Ricardo Moura , Mina Norouzirad , Vitor Augusto , Miguel Fonseca

We describe a new algorithm and R package for peak detection in genomic data sets using constrained changepoint algorithms. These detect changes from background to peak regions by imposing the constraint that the mean should alternately…

Computation · Statistics 2018-10-02 Toby Dylan Hocking , Guillem Rigaill , Paul Fearnhead , Guillaume Bourque

We show that the signal-processing paradigm known as compressed sensing (CS) is applicable to genome-wide association studies (GWAS) and genomic selection (GS). The aim of GWAS is to isolate trait-associated loci, whereas GS attempts to…

Genomics · Quantitative Biology 2014-05-13 Shashaank Vattikuti , James J. Lee , Christopher C. Chang , Stephen D. H. Hsu , Carson C. Chow

Gaussian Process Regression (GPR) is widely used in statistics and machine learning for prediction tasks requiring uncertainty measures. Its efficacy depends on the appropriate specification of the mean function, covariance kernel function,…

Machine Learning · Computer Science 2024-09-20 Shifan Zhao , Jiaying Lu , Ji Yang , Edmond Chow , Yuanzhe Xi

Survival analysis based on Whole Slide Images (WSIs) is crucial for evaluating cancer prognosis, as they offer detailed microscopic information essential for predicting patient outcomes. However, traditional WSI-based survival analysis…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Zheng Wang , Hong Liu , Zheng Wang , Danyi Li , Min Cen , Baptiste Magnier , Li Liang , Liansheng Wang

Estimating the causal treatment effects by subgroups is important in observational studies when the treatment effect heterogeneity may be present. Existing propensity score methods rely on a correctly specified propensity score model. Model…

Methodology · Statistics 2024-04-19 Yan Li , Yong-Fang Kuo , Liang Li

Background/aims: While randomized controlled trials are the gold standard for measuring causal effects, robust conclusions about causal relationships can be obtained using data from observational studies if proper statistical techniques are…

Existing benchmarks for systematic reviewing remain limited either in scale or in disciplinary coverage, with some collections comprising only a modest number of topics and others focusing primarily on biomedical research. We present…

Information Retrieval · Computer Science 2026-04-28 Pierre Achkar , Tim Gollub , Arno Simons , Harrisen Scells , Martin Potthast

Statistical methods for genomewide association studies (GWAS) continue to improve. However, the increasing volume and variety of genetic and genomic data make computational speed and ease of data manipulation mandatory in future software.…

Gaussian Processes (GPs) are widely used tools in statistics, machine learning, robotics, computer vision, and scientific computation. However, despite their popularity, they can be difficult to apply; all but the simplest classification or…

Machine Learning · Computer Science 2016-01-06 Ulrich Schaechtle , Ben Zinberg , Alexey Radul , Kostas Stathis , Vikash K. Mansinghka

Ex-post harmonisation is one of many data preprocessing processes used to combine the increasingly vast and diverse sources of data available for research and analysis. Documenting provenance and ensuring the quality of multi-source…

Databases · Computer Science 2024-06-21 Cynthia A. Huang

Assessing developer proficiency in open-source software (OSS) projects is essential for understanding project dynamics, especially for expertise. This paper presents PyGress, a web-based tool designed to automatically evaluate and visualize…

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

Projection-based testing for mean trajectory differences in two groups of irregularly and sparsely observed functional data has garnered significant attention in the literature because it accommodates a wide spectrum of group differences…

Methodology · Statistics 2023-10-11 Salil Koner , Sheng Luo

The widespread usage of Microsoft Windows has unfortunately led to a surge in malware, posing a serious threat to the security and privacy of millions of users. In response, the research community has mobilized, with numerous efforts…

Cryptography and Security · Computer Science 2025-01-13 Fangtian Zhong , Qin Hu , Yili Jiang , Jiaqi Huang , Xiuzhen Cheng

Conducting genome-wide association studies (GWAS) in copy number variation (CNV) level is a field where few people involves and little statistical progresses have been achieved, traditional methods suffer from many problems such as batch…

Methodology · Statistics 2020-11-17 Han Wang , Changhu Wang , Linjie Wu , Ruibin Xi

Because biological processes can make different loci have different evolutionary histories, species tree estimation requires multiple loci from across the genome. While many processes can result in discord between gene trees and species…

Quantitative Methods · Quantitative Biology 2018-03-13 Md. Shamsuzzoha Bayzid , Siavash Mirarab , Bastien Boussau , Tandy Warnow