Article
Biochemical Research Methods
Itziar Irigoien, Bru Cormand, Maria Soler-Artigas, Cristina Sanchez-Mora, Josep-Antoni Ramos-Quiroga, Concepcion Arenas
Summary: With the rise of GWAS, the analysis of large-scale SNP data has become crucial in biomedical research. This paper proposes a new method based on genetic distances between individuals to identify disease-related SNPs in case-control studies. By considering population substructure and avoiding multiple testing issues, the method provides ordered lists of SNPs and serves as a useful tool for researchers to focus their attention in the initial stage.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Review
Obstetrics & Gynecology
Che Xu, Xiangyan Ruan, Alfred O. Mueck
Summary: Menopause not only marks the end of reproductive life, but also has associations with diseases like hyperlipidemia, atherosclerotic cardiovascular disease, osteoporosis, and breast cancer. Traditional epidemiological studies have shown that heredity plays a significant role in determining the age of natural menopause (ANM). Advances in genomic technology have enabled researchers to conduct genome-wide association studies, revealing that defects in DNA damage repair pathways are the primary genetic mechanism. Further genetic and epidemiological studies, including research on polygenic scores and genetic mechanisms, are needed to investigate the pathogenesis and mechanisms related to menopause and its associated diseases.
REPRODUCTIVE BIOMEDICINE ONLINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Xinyue Wang, Xiaoqian Jiang, Jaideep Vaidya
Summary: The paper proposes two algorithms for generating synthetic SNPs that are indistinguishable from real SNPs. Through game theoretic analysis, it demonstrates the possibility of incentivizing honest behavior by the server. Extensive experiments show that the proposed method can ensure efficient and trustworthy outsourcing of logistic regression for GWAS.
JOURNAL OF BIOMEDICAL INFORMATICS
(2021)
Article
Multidisciplinary Sciences
Xiaoyu Liang, Xuewei Cao, Qiuying Sha, Shuanglin Zhang
Summary: The article introduces a novel multivariate method for phenome-wide association studies (PheWAS) and demonstrates its superiority through extensive simulation studies and real-life application. The proposed method involves hierarchical clustering, clustering linear combination, and false discovery rate control steps.
Review
Plant Sciences
Laura Tibbs Cortes, Zhiwu Zhang, Jianming Yu
Summary: Genome-wide association studies (GWAS) have become a powerful tool for investigating complex traits, with the development of the mixed model framework reducing false positives. Advances in technology have led to the development of methods to increase computational speed or improve statistical power in GWAS.
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.
Review
Biochemistry & Molecular Biology
Imane Lalami, Carole Abo, Bruno Borghese, Charles Chapron, Daniel Vaiman
Summary: This review discusses the genetics of endometriosis, a common feminine disease with a genetic heritability estimated at around 50%. Large GWAS studies have identified some genes and loci associated with the disease, but a significant portion of the heritability remains unexplained. Additional efforts such as exome sequencing may be needed to fully elucidate the genetic factors of endometriosis.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Editorial Material
Medicine, General & Internal
Lisa Bastarache, Joshua C. Denny, Dan M. Roden
Summary: This article discusses the concept and methodology of phenome-wide association studies, which aim to identify associations between genetic variations and phenotypic traits using a dataset.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
(2022)
Article
Multidisciplinary Sciences
Abbas Saad Alatrany, Wasiq Khan, Abir Hussain, Dhiya Al-Jumeily
Summary: The increasing incidence of Alzheimer's disease (AD) poses socioeconomic challenges. In this study, a hybrid feature selection approach and neural network models are used to predict AD. The approach outperformed existing methods with 99% accuracy and f1-score, providing impactful outcomes for other chronic diseases.
Article
Multidisciplinary Sciences
Jack W. O'Sullivan, John P. A. Ioannidis
Summary: This study compared SNVs from earlier and later GWAS and found a replication rate of 85.0% in subsequent studies, with a lower replication rate for binary phenotypes compared to quantitative phenotypes. The study also identified a decrease in SNV effect size for binary phenotypes, but an increase for quantitative phenotypes, and developed a model that could predict SNV replication effectively.
SCIENTIFIC REPORTS
(2021)
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
Plant Sciences
Guogen Zhang, Zhiyuan Bi, Jing Jiang, Jingbing Lu, Keyang Li, Di Bai, Xinchen Wang, Xueyu Zhao, Min Li, Xiuqin Zhao, Wensheng Wang, Jianlong Xu, Zhikang Li, Fan Zhang, Yingyao Shi
Summary: By utilizing genome-wide association and epistasis analysis (GWAES), the genetic basis of rice saline-alkali tolerance was studied. A total of 165 main-effect quantitative trait nucleotides (QTNs) and 124 additional epistatic QTNs were identified, explaining a significant portion of the phenotypic variation of saline-alkali tolerance. Most of these QTNs were located in genomic regions associated with saline-alkali tolerance or known genes. The finding of candidate genes and favorable haplotypes provides valuable information for genetic improvement of rice saline-alkali tolerance.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Genetics & Heredity
Adrian I. Campos, Shinichi Namba, Shu-Chin Lin, Kisung Nam, Julia Sidorenko, Huanwei Wang, Yoichiro Kamatani, Ling-Hua Wang, Seunggeun Lee, Yen-Feng Lin, Yen-Chen Anne Feng, Yukinori Okada, Peter M. Visscher, Loic Yengo
Summary: Simulations and applications to real data show that adjustment of genome-wide association analyses for polygenic scores increases the statistical power for discovery across all ancestries, suggesting an analytical strategy for future studies in underrepresented populations.
Review
Multidisciplinary Sciences
David O. Enoma, Janet Bishung, Theresa Abiodun, Olubanke Ogunlana, Victor Chukwudi Osamor
Summary: This article discusses the applications and future trends of machine learning algorithms in genome-wide association studies (GWAS) to better understand the effects of population genetic variants. The study found that algorithms such as classification, regression, ensemble, and neural networks have been applied to GWAS and their application areas are comprehensively discussed.
JOURNAL OF KING SAUD UNIVERSITY SCIENCE
(2022)
Article
Cell Biology
Yingjie Guo, Chenxi Wu, Zhian Yuan, Yansu Wang, Zhen Liang, Yang Wang, Yi Zhang, Lei Xu
Summary: This article introduces a gene-based method to detect gene-gene interactions by adding additive constraints to the model, and experimental results show that this method outperforms previous experiments in detecting gene-gene interactions.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
