Results 71 to 80 of about 41,900,780 (178)

Livestock Multi‐Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation

Advanced Science, Volume 13, Issue 50, 7 September 2026.
A three‐tier livestock multi‐omics framework resolves four typical analytical pitfalls. Moving from statistical association through machine learning preprocessing to triple‐modal causal inference, it converts omics results into genomic selection and gene editing strategies to achieve One Health, underpinned by multi‐omics data, multimodal sequencing ...
Jiying Wen, Zhongyu Wang, Jieping Huang, Fen Li, Ningbo Chen, Yun Ma   +5 more
wiley   +1 more source

XingyiGuo/transTF-TWAS: TransTF-TWAS

<p>Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data, while trans-located variants ...
Guo Lab at VUMC
core   +1 more source

Integrative Analysis of Transcriptome-Wide Association Study and mRNA Expression Profiles Identifies Candidate Genes Associated With Idiopathic Pulmonary Fibrosis

Frontiers in Genetics, 2020
Idiopathic pulmonary fibrosis (IPF) is a type of scarring lung disease characterized by a chronic, progressive, and irreversible decline in lung function. The genetic basis of IPF remains elusive.
Weiming Gong, Ping Guo, Lu Liu, Qingbo Guan, Qingbo Guan, Qingbo Guan, Zhongshang Yuan   +6 more
doaj   +1 more source

Cellular transcriptomic signatures underpinning the heterogeneity of depression in Alzheimer's disease

Alzheimer's &Dementia, Volume 22, Issue 9, September 2026.
Abstract INTRODUCTION Late‐onset Alzheimer's disease (LOAD) and major depressive disorder (MDD) share genetic etiologies. Here, we investigated brain transcriptomic landscapes to gain insights into shared and divergent molecular and biological etiologies across LOAD and MDD.
Michael W. Lutz, Zhaohui Man, Ornit Chiba‐Falek   +2 more
wiley   +1 more source

Testing and controlling for horizontal pleiotropy with probabilistic Mendelian randomization in transcriptome-wide association studies

, 2020
Integrating results from genome-wide association studies (GWASs) and gene expression studies through transcriptome-wide association study (TWAS) has the potential to shed light on the causal molecular mechanisms underlying disease etiology.
Yuan, Zhongshang, Sheng Yang, Liu, Jin, Zhou, Xiang, Sun, Shiquan, Xiang Zhou, Ping Zeng, Zhu, Huanhuan, Jin Liu, Yang, Sheng, Yang, Can, Huanhuan Zhu, Zeng, Ping, Can Yang, Zhongshang Yuan, Shiquan Sun   +15 more
core   +1 more source

Methyl-TWAS: A powerful method for in silico transcriptome-wide association studies (TWAS) using long-range DNA methylation [PDF]

, 2023
Soyeon Kim, Yidi Qin, Hyun Jung Park, Molin Yue, Zhongli Xu, Erick Forno, Wei Chen, Juan Carlos Celedon   +7 more
openalex   +1 more source

Beyond the Classics: The Synergy of AI and Genomics Reveals an Expanded Repertoire of Pigmentation Genes

Journal of Experimental Zoology Part B: Molecular and Developmental Evolution, Volume 346, Issue 6, Page 475-486, September 2026.
Classical approaches for coloration analysis are limited by human low‐resolution phenotyping and genetic analysis. Artificial intelligence allows us to find genes beyond the tip of the iceberg that explain color and pattern diversity in nature. ABSTRACT Pigmentation has long served as a powerful system for exploring gene–trait relationships, yet much ...
Ehsan Pashay Ahi, Nidal Karagic
wiley   +1 more source

Mapping Causal Biology: Mendelian Randomization in the Era of Big Data

Med Research, Volume 2, Issue 3, Page 522-548, September 2026.
Mendelian randomization (MR) leverages genetic variants to mitigate confounding biases in causal inference. This review systematically maps MR's methodological evolution, highlights its expanding applications in epidemiology and drug target validation, and outlines future directions for overcoming current biases through dynamic, multi‐omics, and cross ...
Xuanlu Shen, Chunrun Qu, Zeyu Wang, Jinglin Zhou, Hongwei Liu, Yingjie Li, Bowei Liu, Hao Zhang, Nan Zhang, Jingwei Zhang, Quan Cheng   +10 more
wiley   +1 more source

Transcriptome-wide association study of cardiovascular outcomes in chronic kidney disease: The chronic renal insufficiency cohort

HGG Advances
Summary: Transcriptome-wide association studies (TWASs) are powerful for identifying gene-trait associations by integrating gene expression and genome-wide association data, but findings may be impacted by the choice of gene expression reference.
Bridget M. Lin, Jia Wen, Andrea R.V.R. Horimoto, Lingbo Zhou, Shuai Huang, Mirela Dobre, Alan S. Go, Yun Li, Nora Franceschini, Amanda H. Anderson, Lawrence J. Appel, Jing Chen, Debbie L. Cohen, Laura M. Dember, Alan S. Go, James P. Lash, Mahboob Rahman, Panduranga S. Rao, Vallabh O. Shah, Mark L. Unruh   +19 more
doaj   +1 more source

TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies [PDF]

, 2022
Mingming Lu, Yadong Zhang, Fengchun Yang, Jialin Mai, Qianwen Gao, Xiaowei Xu, Hongyu Kang, Li Hou, Yunfei Shang, Qiheng Qain, Jie Liu, Meiye Jiang, Hao Zhang, Congfan Bu, Jinyue Wang, Zhewen Zhang, Zaichao Zhang, Jingyao Zeng, Jiao Li, Jingfa Xiao   +19 more
openalex   +1 more source