Results 21 to 30 of about 345,542 (371)

Prioritizing susceptibility genes for the prognosis of male-pattern baldness with transcriptome-wide association study [PDF]

Human Genomics
Background Male-pattern baldness (MPB) is the most common cause of hair loss in men. It can be categorized into three types: type 2 (T2), type 3 (T3), and type 4 (T4), with type 1 (T1) being considered normal.
Eunyoung Choi, Jaeseung Song, Yubin Lee, Yeonbin Jeong, Wonhee Jang   +4 more
doaj   +2 more sources

On the interpretation of transcriptome-wide association studies [PDF]

PLOS Genetics, 2021
AbstractTranscriptome-wide association studies (TWAS) aim to detect relationships between gene expression and a phenotype, and are commonly used for secondary analysis of genome-wide association study (GWAS) results. Results from TWAS analyses are often interpreted as indicating a geneticrelationship between gene expression and a phenotype, but this ...
de Leeuw, Christiaan, Werme, Josefin, Savage, Jeanne E., Peyrot, Wouter J., Posthuma, Danielle   +4 more
openaire   +6 more sources

A Single-Nucleus Transcriptome-Wide Association Study Implicates Novel Genes in Depression Pathogenesis. [PDF]

Biol Psychiatry, 2023
Zeng L, Fujita M, Gao Z, White CC, Green GS, Habib N, Menon V, Bennett DA, Boyle P, Klein HU, De Jager PL.   +10 more
europepmc   +2 more sources

Multi-tissue transcriptome-wide association studies [PDF]

Genetic Epidemiology, 2020
AbstractMany genetic mutations affecting phenotypes are presumed to do so via altering gene expression in particular cells or tissues, but identifying the specific genes involved has been challenging. A transcriptome-wide association study (TWAS) attempts to identify disease associated genes by first learning a predictive model on an eQTL dataset and ...
Grinberg, Nastasiya F, Wallace, Chris
openaire   +2 more sources

Genome- and Transcriptome-Wide Association Studies Identify Susceptibility Genes and Pathways for Periodontitis

Cells, 2022
Several genes associated with periodontitis have been identified through genome-wide association studies (GWAS); however, known genes only explain a minority of the estimated heritability.
Guirong Zhu, Xing Cui, Liwen Fan, Yongchu Pan, Lin Wang   +4 more
doaj   +1 more source

webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study

Nucleic Acids Res., 2021
The development of transcriptome-wide association studies (TWAS) has enabled researchers to better identify and interpret causal genes in many diseases.
Chen Cao, Jianhua Wang, Devin Kwok, Feifei Cui, Zilong Zhang, Da Zhao, Mulin Jun Li, Q. Zou   +7 more
semanticscholar   +1 more source

Statistical power of transcriptome‐wide association studies

Genetic Epidemiology, 2022
AbstractTranscriptome‐Wide Association Studies (TWASs) have become increasingly popular in identifying genes (or other endophenotypes or exposures) associated with complex traits. In TWAS, one first builds a predictive model for gene expressions using an expression quantitative trait loci (eQTL) data set in stage 1, then tests the association between ...
Ruoyu He, Haoran Xue, Wei Pan
openaire   +2 more sources

Alternative polyadenylation transcriptome-wide association study identifies APA-linked susceptibility genes in brain disorders

Nature Communications, 2023
Alternative polyadenylation (APA) plays an essential role in brain development; however, current transcriptome-wide association studies (TWAS) largely overlook APA in nominating susceptibility genes.
Ya Cui, F. Arnold, Fanglue Peng, Dan Wang, J. Li, S. Michels, E. Wagner, A. L. La Spada, Wei Li   +8 more
semanticscholar   +1 more source

Network regression analysis in transcriptome-wide association studies

BMC Genomics, 2022
Abstract Background Transcriptome-wide association studies (TWASs) have shown great promise in interpreting the findings from genome-wide association studies (GWASs) and exploring the disease mechanisms, by integrating GWAS and eQTL mapping studies. Almost all TWAS methods only focus on one gene at a time, with exception
Jin, Xiuyuan, Zhang, Liye, Ji, Jiadong, Ju, Tao, Zhao, Jinghua, Yuan, Zhongshang   +5 more
openaire   +4 more sources

Some statistical consideration in transcriptome‐wide association studies [PDF]

Genetic Epidemiology, 2019
Abstract The methodology of transcriptome‐wide association studies (TWAS) has become popular in integrating a reference expression quantitative trait (eQTL) data set with an independent main GWAS data set to identify (putatively) causal genes, shedding mechanistic insights to biological pathways from genetic variants to a GWAS trait ...
Haoran Xue, Wei Pan
openaire   +3 more sources