Article
Multidisciplinary Sciences
Matteo Sesia, Stephen Bates, Emmanuel Candes, Jonathan Marchini, Chiara Sabatti
Summary: The study introduces a comprehensive statistical framework for analyzing data from genome-wide association studies of polygenic traits, demonstrating validity and effectiveness through simulations and applications to the UK Biobank data. The method outperforms state-of-the-art alternatives and is supported by comparisons with other studies, offering researchers fast software for analyzing Biobank-scale datasets.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Multidisciplinary Sciences
Ludivine Obry, Cyril Dalmasso
Summary: In this study, we evaluated recent weighted multiple testing procedures for genome wide association studies (GWAS) through a simulation study. We also introduced a new efficient procedure called wBHa, which prioritizes the detection of genetic variants with low minor allel frequencies while maximizing overall detection power. Our results demonstrated that wBHa outperformed other procedures in detecting rare variants while maintaining good overall power.
Article
Multidisciplinary Sciences
Zihuai He, Linxi Liu, Michael E. Belloy, Yann Le Guen, Aaron Sossin, Xiaoxia Liu, Xinran Qi, Shiyang Ma, Prashnna K. Gyawali, Tony Wyss-Coray, Hua Tang, Chiara Sabatti, Emmanuel Candes, Michael D. Greicius, Iuliana Ionita-Laza
Summary: The authors present GhostKnockoff, a method for genome-wide association studies which can be applied to enhance existing and future studies to identify functional variants with weaker statistical effects that might be missed by conventional association tests.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Jianhui Gao, Osvaldo Espin-Garcia, Andrew D. Paterson, Lei Sun
Summary: This study comprehensively evaluated the impact of functional annotations on genome-wide association studies (GWAS) in the UK Biobank. The results showed that the number of new genome-wide significant findings increased with the SNP-heritability estimate of traits, but there was a trade-off between new findings and loss of baseline GWAS findings. Therefore, more informative functional scores and new data-integration methods are needed to further improve the power of GWAS.
SCIENTIFIC REPORTS
(2022)
Article
Statistics & Probability
Xianyang Zhang, Jun Chen
Summary: This article introduces an FDR control procedure that can incorporate covariate information in large-scale inference problems. The proposed procedure is implemented using a fast algorithm and has been shown to have asymptotic validity even in cases of misspecified models and weakly dependent p-values. Extensive simulations demonstrate that the method improves upon existing approaches in terms of flexibility, robustness, power, and computational efficiency. The method is applied to omics datasets from genomics studies to identify features associated with clinical and biological phenotypes, and shows superiority, particularly in sparse signal scenarios.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2022)
Article
Biochemical Research Methods
Arya Ebadi, Jack Freestone, William S. Noble, Uri Keich
Summary: Controlling the false discovery rate (FDR) in proteomics experiments using target decoy competition (TDC) only controls the average proportion of false discoveries. However, the actual proportion of false discoveries (FDP) may exceed the specified FDR threshold. We demonstrate this using real data and present two methods, FDP Stepdown and TDC Uniform Band, which help bridge the gap between controlling the expected FDR and the empirical FDP.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Multidisciplinary Sciences
Sora Yoon, Bukyung Baik, Taesung Park, Dougu Nam
Summary: Meta-analyses increase statistical power by combining statistics from multiple studies. Traditional meta-analysis methods show decreasing power as unassociated statistics are included, while Fisher's method and wFisher demonstrate robustness in such cases.
SCIENTIFIC REPORTS
(2021)
Article
Statistics & Probability
Joshua Habiger, Ye Liang
Summary: Recent literature has shown that statistically significant results are often not replicated due to a high false positive rate (FPR) or false discovery rate (FDR). This article demonstrates the use of the local false discovery rate (lfdr) as a statistic to address the FPR and derive publication policies to control the community-wide FDR. It also highlights the limitations of relying solely on p-values for addressing the community-wide FDR.
AMERICAN STATISTICIAN
(2022)
Article
Medicine, General & Internal
Chun Yu Li, Tian Mi Yang, Ru Wei Ou, Qian Qian Wei, Hui Fang Shang
Summary: The study found a significant positive genetic correlation between ALS and celiac disease, multiple sclerosis, rheumatoid arthritis, and systemic lupus erythematosus, as well as a significant negative genetic correlation between ALS and inflammatory bowel disease, ulcerative colitis, and Crohn's disease. Three novel ALS risk genes were identified among shared risk loci.
Article
Multidisciplinary Sciences
Wentao Li, Han Chen, Xiaoqian Jiang, Arif Harmanci
Summary: The distributed Mixed Effects Genome-wide Association study (dMEGA) is a method that enables federated association testing without explicitly sharing genotype and phenotype data. It addresses challenges such as confounding factors and privacy concerns, and incorporates both fixed and random effects to improve accuracy and efficiency.
Article
Statistics & Probability
Dennis Leung, Wenguang Sun
Summary: Adaptive multiple testing with covariates is an important research direction that improves the power of false discovery rate (FDR) procedures. We have developed a z-value based covariate-adaptive (ZAP) methodology that guarantees FDR control and demonstrates state-of-the-art performance.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
(2022)
Article
Statistics & Probability
Xin Xing, Zhigen Zhao, Jun S. Liu
Summary: This article proposes a method called Gaussian Mirror (GM) that aims to find multiple influential variables by creating mirror variables and using test statistics effective for controlling the FDR. The GM method performs better than existing methods, especially in cases where the covariates are highly correlated and the influential variables are not too sparse.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2023)
Article
Urology & Nephrology
Ying-Chun Chen, Henry Sung-Ching Wong, Mei-Yi Wu, Wan-Hsuan Chou, Chih-Chin Kao, Ching-Hsuan Chao, Wei-Chiao Chang, Mai-Szu Wu
Summary: This study identified four susceptibility loci associated with kidney-related traits in a Taiwanese population, with 22q13.2 and 3q29 prioritized as critical candidates.
CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY
(2022)
Article
Medicine, Legal
David P. Baldwin, Stanley J. Bajic, Max D. Morris, Daniel S. Zamzow
Summary: This report presents a study that aimed to estimate error rates of examiner in false identifications and false eliminations when comparing an unknown cartridge case to a collection of three known ones. Volunteer active examiners from AFTE and ASCLD laboratories were provided with sets of known and questioned cartridge cases to assess. The overall false elimination rate was estimated as 0.367% while the false identification rate was estimated as 1.01%. These rates are comparable to or lower than the rate of production of poor-quality marks by the firearms used in the study.
FORENSIC SCIENCE INTERNATIONAL
(2023)
Review
Biochemical Research Methods
Mitra Ebrahimpoor, Jelle J. Goeman
Summary: Volcano plots are commonly used to select interesting discoveries, but they may lead to inflated false discovery rates. We demonstrate this issue with simulation experiments and data, and propose alternative approaches for multiple testing that do not inflate the false discovery rate.
BRIEFINGS IN BIOINFORMATICS
(2021)
