Results 151 to 160 of about 39,970,022 (174)

Integrative Multi-omics Analysis for Prioritization of Candidate Genes in Polycystic Ovary Syndrome. [PDF]

FASEB J
Guo R, Liao D, Huang J, Dong B.
europepmc   +1 more source

Data-driven RNA phenotyping captures genetically regulated dimensions of the transcriptome. [PDF]

Am J Hum Genet
Munro D, Gusev A, Palmer AA, Mohammadi P.   +3 more
europepmc   +1 more source

Identifying expression and DNA methylation biomarkers for lung adenocarcinoma risk in East Asia. [PDF]

J Natl Cancer Inst
Chen TY, Chien LH, Jiang SS, Choi J, Hung HH, Hsiao CF, Shi J, Blechter B, Breeze CE, Chang GC, Chen KY, Tsai YH, Su WC, Huang MS, Chen YM, Wen YF, Chen CY, Wang CL, Tsai FY, Chen HL, Hsieh WS, Lin HC, Wang LH, Chen CJ, Yang PC, Chen CY, Rothman N, Chanock SJ, Lan Q, Chang IS, Hsiung CA.   +30 more
europepmc   +1 more source

Convergence in Pruning and Circadian Regulation in Obsessive-Compulsive Disorder and Allergic Diseases: Evidence From a Secondary Genome-Wide Analysis. [PDF]

Cureus
Cheung N.
europepmc   +1 more source

Diffusion kurtosis imaging (gen)omics unravels mechanisms of cerebral small vessel disease

Le Grand Q, Koch A, Imtiaz M, Maier G, Talevi V, Liu D, Aziz NA, Breteler MM.   +7 more
europepmc   +1 more source

Database for ancestry-specific cross-tissue gene expression models: AGEMdb

Pagnuco I, Herrerías-Azcué F, Eyre S, Rattray M, Morris AP.   +4 more
europepmc   +1 more source

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Multitrait transcriptome‐wide association study (TWAS) tests

Genetic Epidemiology, 2021
AbstractMultitrait tests can improve power to detect associations between individual single‐nucleotide polymorphisms (SNPs) and several related traits. Here, we develop methods for multi‐SNP transcriptome‐wide association (TWAS) tests to test the association between predicted gene expression levels and multiple phenotypes.
Joel Krier, Bogdan Pasaniuc, Hélian Feng   +2 more
exaly   +3 more sources

Transcriptome‐Wide Association Studies (TWAS): Methodologies, Applications, and Challenges

Current Protocols
Abstract Transcriptome‐wide association study (TWAS) methodologies aim to identify genetic effects on phenotypes through the mediation of gene transcription. In TWAS, in silico models of gene expression are trained as functions of genetic variants and then applied to genome‐wide association study (GWAS) data.
Eric R Gamazon
exaly   +3 more sources

Abstract 1591: Large-scale transcriptome-wide association study (TWAS) identifies novel candidate susceptibility genes for pancreatic cancer

Cancer Research, 2019
Abstract Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in United States with a 5-year survival rate of only 8%. Inherited predisposition plays an important role in PDAC risk. Rare, moderately to highly penetrant mutations in hereditary cancer and pancreatitis genes, identified in families ...
Jun Zhong, Ashley Jermusyk, Lang Wu, Jason W. Hoskins, Irene Collins, Mingfeng Zhang, Song Lei, Charles C. Chung, Tongwu Zhang, Wenming Xiao, Rachael Stolzenberg-Solomon, Alison P. Klein, Brian M. Wolpin, Xiao-Ou Shu, Stephen J. Chanock, Sara Olson, Nilanjan Chatterjee, Jill Smith, Jianxin Shi, Peter Kraft, Gloria M. Petersen, Wei Zheng, Laufey T. Amundadottir   +22 more
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A-TWAS: An aggregated transcriptome-wide association study model incorporating multiple Bayesian priors

Abstract Motivation Transcriptome-wide association study (TWAS) is a significant methodology utilized for identifying associations between genes and diseases by integrating transcriptome and genome-wide association studies (GWAS) data.
Yilan Liang, Han Wang, Yan Dora Zhang
openaire   +1 more source