scholarly journals Identification of disease-associated pathways in pancreatic cancer by integrating genome-wide association study and gene expression data

2016 ◽  
Vol 12 (1) ◽  
pp. 537-543
Author(s):  
JIN LONG ◽  
ZHE LIU ◽  
XINGDA WU ◽  
YUANHONG XU ◽  
CHUNLIN GE
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Association Study ◽  
Gene Expression Data ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Expression Data ◽  
Genome Wide

scholarly journals The combination of a genome-wide association study of lymphocyte count and analysis of gene expression data reveals novel asthma candidate genes

2012 ◽  
Vol 21 (9) ◽  
pp. 2111-2123 ◽  
Author(s):  
Darren A. Cusanovich ◽  
Christine Billstrand ◽  
Xiang Zhou ◽  
Claudia Chavarria ◽  
Sherryl De Leon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Study ◽  
Candidate Genes ◽  
Gene Expression Data ◽  
Lymphocyte Count ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Expression Data ◽  
Genome Wide ◽  
A Genome

scholarly journals Novel Insight into the Aetiology of Autism Spectrum Disorder Gained by Integrating Expression Data with Genome-wide Association Statistics

2018 ◽  
Author(s):  
Oliver Pain ◽  
Andrew J. Pocklington ◽  
Peter A. Holmans ◽  
Nicholas J. Bray ◽  
Heath E. O’Brian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Fetal Brain ◽  
Autism Spectrum ◽  
Genome Wide Association ◽  
Summary Statistics ◽  
Expression Data ◽  
Genome Wide ◽  
Insight Into

AbstractBackgroundA recent genome-wide association study (GWAS) of autism spectrum disorders (ASD) (Ncases=18,381, Ncontrols=27,969) has provided novel opportunities for investigating the aetiology of ASD. Here, we integrate the ASD GWAS summary statistics with summary-level gene expression data to infer differential gene expression in ASD, an approach called transcriptome-wide association study (TWAS).MethodsUsing FUSION software, ASD GWAS summary statistics were integrated with predictors of gene expression from 16 human datasets, including adult and fetal brain. A novel adaptation of established statistical methods was then used to test for enrichment within candidate pathways, specific tissues, and at different stages of brain development. The proportion of ASD heritability explained by predicted expression of genes in the TWAS was estimated using stratified linkage disequilibrium-score regression.ResultsThis study identified 14 genes as significantly differentially expressed in ASD, 13 of which were outside of known genome-wide significant loci (±500kb). XRN2, a gene proximal to an ASD GWAS locus, was inferred to be significantly upregulated in ASD, providing insight into functional consequence of this associated locus. One novel transcriptome-wide significant association from this study is the downregulation of PDIA6, which showed minimal evidence of association in the GWAS, and in gene-based analysis using MAGMA. Predicted gene expression in this study accounted for 13.0% of the total ASD SNP-heritability.ConclusionThis study has implicated several genes as significantly up-/down-regulated in ASD providing novel and useful information for subsequent functional studies. This study also explores the utility of TWAS-based enrichment analysis and compares TWAS results with a functionally agnostic approach.

scholarly journals A Genome-Wide Integrative Association Study of DNA Methylation and Gene Expression Data and Later Life Cognitive Functioning in Monozygotic Twins

2020 ◽  
Vol 14 ◽  
Author(s):  
Mette Soerensen ◽  
Dominika Marzena Hozakowska-Roszkowska ◽  
Marianne Nygaard ◽  
Martin J. Larsen ◽  
Veit Schwämmle ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cognitive Functioning ◽  
Association Study ◽  
Gene Expression Data ◽  
Monozygotic Twins ◽  
Later Life ◽  
Expression Data ◽  
Genome Wide ◽  
A Genome

scholarly journals Genome-wide association study using diversity outcross mice identified candidate genes of pancreatic cancer

Genomics ◽  
2019 ◽  
Vol 111 (6) ◽  
pp. 1882-1888 ◽  
Author(s):  
Chuanjia Yang ◽  
Yan Wang ◽  
Weixue Xu ◽  
Zhen Liu ◽  
Siqi Zhou ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Association Study ◽  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide

scholarly journals A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data

2018 ◽  
Vol 14 (5) ◽  
pp. e1006105 ◽  
Author(s):  
Aaditya V. Rangan ◽  
Caroline C. McGrouther ◽  
John Kelsoe ◽  
Nicholas Schork ◽  
Eli Stahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Study Data ◽  
Genome Wide Association ◽  
Low Rank ◽  
Counting Method ◽  
Genome Wide

P1-229: Genome-Wide Association Study of Brain Gene Expression Levels (eGWAS)

2011 ◽  
Vol 7 ◽  
pp. S184-S184
Author(s):  
Nilufer Ertekin-Taner ◽  
Fanggeng Zou ◽  
High Chai ◽  
Curtis Younkin ◽  
Julia Crook ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Expression Levels ◽  
Brain Gene Expression ◽  
Genome Wide ◽  
Gene Expression Levels
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