Results 21 to 30 of about 41,997,714 (232)

Multivariate adaptive shrinkage improves cross-population transcriptome prediction for transcriptome-wide association studies in underrepresented populations

, 2023
This Zenodo file collection contains transcriptome prediction models built for PrediXcan, as well as concatenated raw results from SPrediXcan. Files belong to the scientific research paper: "Multivariate adaptive shrinkage improves cross-population ...
Liu, Yongmei, Rich, Stephen S, Durda, Peter, Mikhaylova, Anna V, Gignoux, Chris, Papanicolaou, George, Nguyen, Chris, Im, Hae Kyung, Rotter, Jerome I, Manichaikul, Ani, Taylor, Kent D, Wheeler, Heather E, Hu, Xiaowei, Cho, Michael H, Araujo, Daniel S, NHLBI TOPMed Consortium, Ardlie, Kristin   +16 more
core   +1 more source

Transcriptome-wide association study identifies susceptibility genes for rheumatoid arthritis

Arthritis Research & Therapy, 2021
Objective To identify rheumatoid arthritis (RA)-associated susceptibility genes and pathways through integrating genome-wide association study (GWAS) and gene expression profile data. Methods A transcriptome-wide association study (TWAS) was conducted by
Cuiyan Wu, Sijian Tan, Li Liu, Shiqiang Cheng, Peilin Li, Wenyu Li, Huan Liu, Feng’e Zhang, Sen Wang, Yujie Ning, Yan Wen, Feng Zhang   +11 more
doaj   +1 more source

Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes

Human Genomics, 2019
Background While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and
Molly Went, Ben Kinnersley, Amit Sud, David C. Johnson, Niels Weinhold, Asta Försti, Mark van Duin, Giulia Orlando, Jonathan S. Mitchell, Rowan Kuiper, Brian A. Walker, Walter M. Gregory, Per Hoffmann, Graham H. Jackson, Markus M. Nöthen, Miguel Inacio da Silva Filho, Hauke Thomsen, Annemiek Broyl, Faith E. Davies, Unnur Thorsteinsdottir, Markus Hansson, Martin Kaiser, Pieter Sonneveld, Hartmut Goldschmidt, Kari Stefansson, Kari Hemminki, Björn Nilsson, Gareth J. Morgan, Richard S. Houlston   +28 more
doaj   +1 more source

Cross-population Transcriptome Prediction Models for Transcriptome-Wide Association Studies in Diverse Populations

, 2022
Genome-wide association studies (GWAS) have been utilized to find associations between single nucleotide polymorphisms (SNPs) and traits. However, most GWAS are conducted on populations of European ancestries. Further analysis involving the transcriptome
Nguyen, Christopher, Wheeler, Dr. Heather, Araujo, Daniel   +2 more
core   +1 more source

Integrative Analysis of Transcriptome-Wide Association Study and mRNA Expression Profiles Identified Candidate Genes and Pathways Associated With Acute Myocardial Infarction

Frontiers in Genetics, 2021
BackgroundAcute myocardial infarction (AMI), characterized by an event of myocardial necrosis, is a common cardiac emergency worldwide. However, the genetic mechanisms of AMI remain largely elusive.MethodsA genome-wide association study dataset of AMI ...
Guanzhong Chen, Guanzhong Chen, Liwei Liu, Liwei Liu, Huanqiang Li, Zhubin Lun, Zhubin Lun, Ziling Mai, Ziling Mai, Wenguang Lai, Wenguang Lai, Enzhao Chen, Chunyun Zhou, Sijia Yu, Sijia Yu, Junqing Yang, Shiqun Chen, Jiyan Chen, Jiyan Chen, Jiyan Chen, Yong Liu, Yong Liu, Yong Liu   +22 more
doaj   +1 more source

A transcriptome-wide association study of high-grade serous epithelial ovarian cancer identifies new susceptibility genes and splice variants. [PDF]

, 2019
We sought to identify susceptibility genes for high-grade serous ovarian cancer (HGSOC) by performing a transcriptome-wide association study of gene expression and splice junction usage in HGSOC-relevant tissue types (N = 2,169) and the largest genome ...
Liu, Gang, Pasaniuc, Bogdan, Felipe Segato, Paulo C. Lyra, Kar, Siddhartha, Vavra, Kevin C, Kevin C. Vavra, Gusev, Alexander, Bogdan Pasaniuc, Segato, Felipe, Freedman, Matthew L, Lyra, Paulo C, Lee, Janet M, Beth Y. Karlan, Kate Lawrenson, Marcos A. S. Fonseca, Janet M. Lee, Siddhartha Kar, Simon A. Gayther, Pharoah, Paul DP, Alvaro N. Monteiro, Lin, Xianzhi, Gang Liu, Matthew L. Freedman, Pejovic, Tanya, Tanya Pejovic, Noushmehr, Houtan, Fonseca, Marcos AS, Gayther, Simon A, Karlan, Beth Y, Monteiro, Alvaro N, Lawrenson, Kate, Houtan Noushmehr, Paul D. P. Pharoah, Alexander Gusev, Xianzhi Lin   +35 more
core   +5 more sources

Integrative analysis of transcriptome-wide association study and gene expression profiling identifies candidate genes associated with stroke [PDF]

PeerJ, 2019
Background Stroke is a major public health burden worldwide. Although genetic variation is known to play a role in the pathogenesis of stroke, the specific pathogenic mechanisms are still unclear.
Jian Yang, Bin Yan, Yajuan Fan, Lihong Yang, Binbin Zhao, Xiaoyan He, Qingyan Ma, Wei Wang, Ling Bai, Feng Zhang, Xiancang Ma   +10 more
doaj   +2 more sources

Probabilistic fine-mapping of transcriptome-wide association studies [PDF]

, 2019
Transcriptome-wide association studies using predicted expression have identified thousands of genes whose locally regulated expression is associated with complex traits and diseases.
Kichaev, Gleb, Pasaniuc, Bogdan, Gleb Kichaev, Huwenbo Shi, Malika K. Freund, Gusev, Alexander, Bogdan Pasaniuc, Ruth Johnson, Shi, Huwenbo, Freund, Malika K, Johnson, Ruth, Nicholas Mancuso, Alexander Gusev, Mancuso, Nicholas   +13 more
core   +1 more source

Transcriptome-Wide Association Studies and Integration Analysis of mRNA Expression Profiles Identify Candidate Genes and Pathways Associated With Ankylosing Spondylitis

Frontiers in Immunology, 2022
This study aimed to identify susceptibility genes and pathways associated with ankylosing spondylitis (AS) by integrating whole transcriptome-wide association study (TWAS) analysis and mRNA expression profiling data.
Ruoyang Feng, Mengnan Lu, Lin Liu, Ke Xu, Peng Xu   +4 more
doaj   +1 more source

MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies. [PDF]

, 2021
Traditional predictive models for transcriptome-wide association studies (TWAS) consider only single nucleotide polymorphisms (SNPs) local to genes of interest and perform parameter shrinkage with a regularization process.
Arjun Bhattacharya, Michael I Love, Li, Yun, Love, Michael I, Yun Li, Love, M.I., Bhattacharya, A., Li, Y., Bhattacharya, Arjun, Michael I. Love   +9 more
core   +1 more source