Gene set analysis of genome-wide association studies: methodological issues and perspectives.

paper Cited Public

Authors: Wang, Lily; Jia, Peilin; Wolfinger, Russell D; Chen, Xi; Zhao, Zhongming
Year: 2011
Journal: Genomics
PMID: 21565265
DOI: 10.1016/j.ygeno.2011.04.006
PMCID: PMC3852939

#	Section	Preview
20	Methodological issues — Assessing statistical significance	First, a typical GWAS measures a half million or more SNPs on hundreds or even thousands of samples.…
21	Methodological issues — Assessing statistical significance	However, this distribution ignores the empirical mean and standard deviation of the gene set…
22	Methodological issues — Assessing statistical significance	Second, it is not straight forward to model the hierarchical structure in gene sets: SNPs lie within…
23	Methodological issues — Assessing statistical significance	Third, to increase sample size, many GWAS were conducted at multiple study sites, often with…
24	Methodological issues — Assessing statistical significance	An alternative strategy is to employ more flexible parametric models. For GWAS with case-control…
25	Methodological issues — Assessing statistical significance	Additionally, Bayesian methods have recently been proposed for genetic association studies…
26	Several areas for improving gene set analysis of GWAS	Although the underlying principle that many functionally related genes collectively contribute to…
27	Several areas for improving gene set analysis of GWAS	1) Improve statistical power for detecting disease associated gene sets. Nearly all current methods…
28	Several areas for improving gene set analysis of GWAS	In addition, improving SNP coverage and, thus, the number of informative genes may also be…
29	Several areas for improving gene set analysis of GWAS	2) Develop strategies for the assessment and comparison of gene set analysis methods. When assessing…
30	Several areas for improving gene set analysis of GWAS	Similarly, to compare the power of different methods, one can randomly sample disease associated…
31	Several areas for improving gene set analysis of GWAS	Although most GWAS gene set analyses are discovery projects, careful attention still needs to be…
32	Several areas for improving gene set analysis of GWAS	3) Assess the stability of gene set testing results. In addition to power and type I error rate,…
33	Several areas for improving gene set analysis of GWAS	One possible cause for instability of the results in genetic association studies is genetic…
34	Several areas for improving gene set analysis of GWAS	4) Develop threshold-free procedures. To improve stability of results, one strategy is to develop…
35	Summary and perspectives	In summary, recent studies [11,73–84] have repeatedly demonstrated that gene set analysis is a…
36	Summary and perspectives	marginal effects that act jointly with exposure factors [85]. As many more GWAS datasets are…

Name	Type
Androgen local	drug
bipolar disorder	phenotype
breast cancer	phenotype
causal SNP	cohort
complex diseases	phenotype
C-reactive protein	phenotype
Crohn’s disease	phenotype
cystic fibrosis	phenotype
disease	phenotype
disease risk	phenotype
disease status	phenotype
disease susceptibility	phenotype
Endometrial cancer local	phenotype
estrogen	drug
GAIN schizophrenia dataset local	cohort
gene	gene
Gene Ontology	drug
gene set local	drug
GeneSet local	gene
gene set annotation database local	drug
genetic variants	cohort
genome-wide association studies	cohort
GWAS	cohort
GWAS datasets local	cohort
HapMap	cohort
HapMap3	cohort
HNF1A local	gene
KEGG	drug
most significant SNP local	variant
MSigDB local	drug
PANTHER Classification System local	drug
phenotype of interest	phenotype
REACTOME local	drug
schizophrenia	phenotype
single nucleotide polymorphisms	variant
SNP	cohort
trait level local	phenotype
type 2 diabetes	phenotype
UGT1A1 local	gene
UGT1A10 local	gene
UGT1A3 local	gene
UGT1A4 local	gene
UGT1A5 local	gene
UGT1A6 local	gene
UGT1A7 local	gene
UGT1A8 local	gene
UGT1A9 local	gene

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Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence.	Clark SL et al.	—	2017	→
Examination of the Involvement of Cholinergic-Associated Genes in Nicotine Behaviors in European and African Americans.	Melroy-Greif WE et al.	—	2017	→
Gene-wide Association Study Reveals RNF122 Ubiquitin Ligase as a Novel Susceptibility Gene for Attention Deficit Hyperactivity Disorder.	Garcia-Martínez I et al.	—	2017	→
Genomic Analysis of Genotype-by-Social Environment Interaction for <i>Drosophila melanogaster</i> Aggressive Behavior.	Rohde PD et al.	—	2017	→
Identification of additional loci associated with antibody response to Mycobacterium avium ssp. Paratuberculosis in cattle by GSEA-SNP analysis.	Del Corvo M et al.	—	2017	→
Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer.	Milne RL et al.	—	2017	→
Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions.	Kao PY et al.	—	2017	→
Pathway-based genome-wide association analysis of milk coagulation properties, curd firmness, cheese yield, and curd nutrient recovery in dairy cattle.	Dadousis C et al.	—	2017	→
Pooling-Based Genome-Wide Association Study Identifies Risk Loci in the Pathogenesis of Ovarian Endometrioma in Chinese Han Women.	Wang W et al.	—	2017	→
The genetics of human longevity: an intricacy of genes, environment, culture and microbiome.	Dato S et al.	—	2017	→
The null hypothesis of GSEA, and a novel statistical model for competitive gene set analysis.	Debrabant B	—	2017	→
A novel type 2 diabetes risk allele increases the promoter activity of the muscle-specific small ankyrin 1 gene.	Yan R et al.	—	2016	→
Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes.	Rohde PD et al.	—	2016	→
Cross-Study Comparison Reveals Common Genomic, Network, and Functional Signatures of Desiccation Resistance in Drosophila melanogaster.	Telonis-Scott M et al.	—	2016	→
FLAGS: A Flexible and Adaptive Association Test for Gene Sets Using Summary Statistics.	Huang J et al.	—	2016	→
Gene set analysis for interpreting genetic studies.	Pers TH	—	2016	→
Genetics of Coronary Artery Disease.	McPherson R et al.	—	2016	→
Genetics of structural connectivity and information processing in the brain.	Giddaluru S et al.	—	2016	→
Genetic variation in FAAH is associated with cannabis use disorders in a young adult sample of Mexican Americans.	Melroy-Greif WE et al.	—	2016	→
Genome-wide gene-based analysis suggests an association between Neuroligin 1 (NLGN1) and post-traumatic stress disorder.	Kilaru V et al.	—	2016	→
Investigation of a Possible Role for the Histidine Decarboxylase Gene in Tourette Syndrome in the Chinese Han Population: A Family-Based Study.	Dong H et al.	—	2016	→
Pathway Analysis Incorporating Protein-Protein Interaction Networks Identified Candidate Pathways for the Seven Common Diseases.	Lin PL et al.	—	2016	→
Protein Quantitative Trait Loci Analysis Identifies Genetic Variation in the Innate Immune Regulator TOLLIP in Post-Lung Transplant Primary Graft Dysfunction Risk.	Cantu E et al.	—	2016	→
Targeted genomic analysis reveals widespread autoimmune disease association with regulatory variants in the TNF superfamily cytokine signalling network.	Richard AC et al.	—	2016	→
Test for association of common variants in GRM7 with alcohol consumption.	Melroy-Greif WE et al.	—	2016	→
The statistical properties of gene-set analysis.	de Leeuw CA et al.	—	2016	→
ABC transporters and the proteasome complex are implicated in susceptibility to Stevens-Johnson syndrome and toxic epidermal necrolysis across multiple drugs.	Nicoletti P et al.	—	2015	→
Alcohol Dependence Genetics: Lessons Learned From Genome-Wide Association Studies (GWAS) and Post-GWAS Analyses.	Hart AB et al.	—	2015	→
A Powerful Pathway-Based Adaptive Test for Genetic Association with Common or Rare Variants.	Pan W et al.	—	2015	→
Endophenotypes for Alcohol Use Disorder: An Update on the Field.	Salvatore JE et al.	—	2015	→
Genetic Analysis of Association Between Calcium Signaling and Hippocampal Activation, Memory Performance in the Young and Old, and Risk for Sporadic Alzheimer Disease.	Heck A et al.	—	2015	→
Genetic factors and epigenetic mechanisms of longevity: current perspectives.	Lazarus J et al.	—	2015	→
Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy Phenotypes.	Hirbo J et al.	—	2015	→
Interaction of Wnt pathway related variants with type 2 diabetes in a Chinese Han population.	Zhou JB et al.	—	2015	→
Involvement of astrocyte metabolic coupling in Tourette syndrome pathogenesis.	de Leeuw C et al.	—	2015	→
Lessons learned in the analysis of high-dimensional data in vaccinomics.	Oberg AL et al.	—	2015	→
Linking genes to neurological clinical practice: the genomic basis for neurorehabilitation.	Goldberg A et al.	—	2015	→
MAGMA: generalized gene-set analysis of GWAS data.	de Leeuw CA et al.	—	2015	→
META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies.	Rosenberger A et al.	—	2015	→
Pathway-Based Genome-Wide Association Studies for Plasma Triglycerides in Obese Females and Normal-Weight Controls.	Jiao H et al.	—	2015	→
Polygenic risk for externalizing disorders: Gene-by-development and gene-by-environment effects in adolescents and young adults.	Salvatore JE et al.	—	2015	→
Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders.	Parikshak NN et al.	—	2015	→
Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease.	Ghosh S et al.	—	2015	→
Converging genetic and functional brain imaging evidence links neuronal excitability to working memory, psychiatric disease, and brain activity.	Heck A et al.	—	2014	→
Explaining additional genetic variation in complex traits.	Robinson MR et al.	—	2014	→
Human longevity and variation in DNA damage response and repair: study of the contribution of sub-processes using competitive gene-set analysis.	Debrabant B et al.	—	2014	→
Integrative identification of deregulated miRNA/TF-mediated gene regulatory loops and networks in prostate cancer.	Afshar AS et al.	—	2014	→
Network.assisted analysis to prioritize GWAS results: principles, methods and perspectives.	Jia P et al.	—	2014	→
Pathway-based analysis tools for complex diseases: a review.	Jin L et al.	—	2014	→
Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment.	Salvatore JE et al.	—	2014	→
Semantic particularity measure for functional characterization of gene sets using gene ontology.	Bettembourg C et al.	—	2014	→
The synapse in schizophrenia.	Pocklington AJ et al.	—	2014	→
Whole-genome pathway analysis on 132,497 individuals identifies novel gene-sets associated with body mass index.	Simonson MA et al.	—	2014	→
A century after Fisher: time for a new paradigm in quantitative genetics.	Nelson RM et al.	—	2013	→
Association signals unveiled by a comprehensive gene set enrichment analysis of dental caries genome-wide association studies.	Wang Q et al.	—	2013	→
Finding type 2 diabetes causal single nucleotide polymorphism combinations and functional modules from genome-wide association data.	Kang C et al.	—	2013	→
Gene-based testing of interactions in association studies of quantitative traits.	Ma L et al.	—	2013	→
Genome-wide modeling of complex phenotypes in Caenorhabditis elegans and Drosophila melanogaster.	De S et al.	—	2013	→
Integrated enrichment analysis of variants and pathways in genome-wide association studies indicates central role for IL-2 signaling genes in type 1 diabetes, and cytokine signaling genes in Crohn's disease.	Carbonetto P et al.	—	2013	→
Network-based multiple sclerosis pathway analysis with GWAS data from 15,000 cases and 30,000 controls.	International Multiple Sclerosis Genetics Consortium	—	2013	→
Pathway analysis using information from allele-specific gene methylation in genome-wide association studies for bipolar disorder.	Chuang LC et al.	—	2013	→
Pathway-based analysis using genome-wide association data from a Korean non-small cell lung cancer study.	Lee D et al.	—	2013	→
Pathway-based approaches for sequencing-based genome-wide association studies.	Wu G et al.	—	2013	→
Pharmacogenetics of topical and systemic treatment of psoriasis.	Prieto-Pérez R et al.	—	2013	→
Topics in transcriptional control of lipid metabolism: from transcription factors to gene-promoter polymorphisms.	Bergen WG et al.	—	2013	→
Translating genome wide association study results to associations among common diseases: in silico study with an electronic medical record.	Anand V et al.	—	2013	→
A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia.	Jia P et al.	—	2012	→
Cell adhesion molecules contribute to Alzheimer's disease: multiple pathway analyses of two genome-wide association studies.	Liu G et al.	—	2012	→
Comparison of pathway analysis approaches using lung cancer GWAS data sets.	Fehringer G et al.	—	2012	→
Enriched pathways for major depressive disorder identified from a genome-wide association study.	Kao CF et al.	—	2012	→
Genomics in 2012: challenges and opportunities in the next generation sequencing era.	Zhao Z et al.	—	2012	→
Integrated genome-wide pathway association analysis with INTERSNP.	Herold C et al.	—	2012	→
Integrative pathway analysis of genome-wide association studies and gene expression data in prostate cancer.	Jia P et al.	—	2012	→
Network-assisted investigation of combined causal signals from genome-wide association studies in schizophrenia.	Jia P et al.	—	2012	→
Pathway analysis of genomic data: concepts, methods, and prospects for future development.	Ramanan VK et al.	—	2012	→
Physiology and Endocrinology Symposium: How single nucleotide polymorphism chips will advance our knowledge of factors controlling puberty and aid in selecting replacement beef females.	Snelling WM et al.	—	2012	→
Pooled sample-based GWAS: a cost-effective alternative for identifying colorectal and prostate cancer risk variants in the Polish population.	Gaj P et al.	—	2012	→
Searching joint association signals in CATIE schizophrenia genome-wide association studies through a refined integrative network approach.	Jia P et al.	—	2012	→
Uncovering networks from genome-wide association studies via circular genomic permutation.	Cabrera CP et al.	—	2012	→
A comprehensive network and pathway analysis of candidate genes in major depressive disorder.	Jia P et al.	—	2011	→
An improved kinetic model for the acetone-butanol-ethanol pathway of Clostridium acetobutylicum and model-based perturbation analysis.	Li RD et al.	—	2011	→
Network-assisted Causal Gene Detection in Genome-wide Association Studies: An Improved Module Search Algorithm.	Jia P et al.	—	2011	→