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The more the merrier? Multivariate approaches to genome-wide association analysis
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/gepi.20257openalex-snapshot
Pleiotropy and principal components of heritability combine to increase power for association analysis
inferredcites →https://doi.org/10.1002/gepi.20303openalex-snapshot
Estimation of the multiple testing burden for genomewide association studies of nearly all common variants
inferredcites →https://doi.org/10.1002/gepi.21759openalex-snapshot
A General Framework for Association Tests With Multivariate Traits in Large‐Scale Genomics Studies
inferredcites →https://doi.org/10.1007/bf02293746openalex-snapshot
Sufficient Statistics and Latent Trait Models
inferredcites →https://doi.org/10.1007/s10519-016-9787-1openalex-snapshot
Multivariate Gene-Based Association Test on Family Data in MGAS
inferredcites →https://doi.org/10.1007/s11336-014-9435-8openalex-snapshot
OpenMx 2.0: Extended Structural Equation and Statistical Modeling
inferredcites →https://doi.org/10.1016/j.ajhg.2010.11.011openalex-snapshot
GCTA: A Tool for Genome-wide Complex Trait Analysis
inferredcites →https://doi.org/10.1016/j.ajhg.2011.11.029openalex-snapshot
Five Years of GWAS Discovery
inferredcites →https://doi.org/10.1016/j.ajhg.2014.03.016openalex-snapshot
Maximizing the Power of Principal-Component Analysis of Correlated Phenotypes in Genome-wide Association Studies
inferredcites →https://doi.org/10.1016/j.ajhg.2014.11.011openalex-snapshot
Meta-analysis of Correlated Traits via Summary Statistics from GWASs with an Application in Hypertension
inferredcites →https://doi.org/10.1016/j.ajhg.2017.06.005openalex-snapshot
10 Years of GWAS Discovery: Biology, Function, and Translation
inferredcites →https://doi.org/10.1016/j.intell.2007.01.003openalex-snapshot
Sex differences on the WISC-R in Belgium and The Netherlands
inferredcites →https://doi.org/10.1016/s0019-9958(61)80061-2openalex-snapshot
Probabilistic Models for Some Intelligence and Attainment Tests
inferredcites →https://doi.org/10.1017/s0033291709992157openalex-snapshot
Deconstructing major depression: a validation study of the DSM-IV symptomatic criteria
inferredcites →https://doi.org/10.1037//0033-2909.115.3.465openalex-snapshot
How the power of MANOVA can both increase and decrease as a function of the intercorrelations among the dependent variables.
inferredcites →https://doi.org/10.1038/ejhg.2009.133openalex-snapshot
An integrated phenomic approach to multivariate allelic association
inferredcites →https://doi.org/10.1038/ejhg.2014.94openalex-snapshot
Sandwich corrected standard errors in family-based genome-wide association studies
inferredcites →https://doi.org/10.1038/mp.2008.126openalex-snapshot
A framework for interpreting genome-wide association studies of psychiatric disorders
inferredcites →https://doi.org/10.1038/mp.2011.85openalex-snapshot
Genome-wide association studies establish that human intelligence is highly heritable and polygenic
inferredcites →https://doi.org/10.1038/mp.2012.184openalex-snapshot
Childhood intelligence is heritable, highly polygenic and associated with FNBP1L
inferredcites →https://doi.org/10.1038/mp.2012.21openalex-snapshot
A mega-analysis of genome-wide association studies for major depressive disorder
inferredcites →https://doi.org/10.1038/mp.2012.65openalex-snapshot
Power in GWAS: lifting the curse of the clinical cut-off
inferredcites →https://doi.org/10.1038/mp.2014.121openalex-snapshot
MZ twin pairs or MZ singletons in population family-based GWAS? More power in pairs
inferredcites →https://doi.org/10.1038/ng.2876openalex-snapshot
Advantages and pitfalls in the application of mixed-model association methods
inferredcites →https://doi.org/10.1038/ng.3211openalex-snapshot
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
inferredcites →https://doi.org/10.1038/ng.3431openalex-snapshot
Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis
inferredcites →https://doi.org/10.1038/ng1847openalex-snapshot
Principal components analysis corrects for stratification in genome-wide association studies
inferredcites →https://doi.org/10.1038/ng2088openalex-snapshot
A new multipoint method for genome-wide association studies by imputation of genotypes
inferredcites →https://doi.org/10.1038/nmeth.2848openalex-snapshot
Efficient multivariate linear mixed model algorithms for genome-wide association studies
inferredcites →https://doi.org/10.1038/nn.3648openalex-snapshot
A solution to dependency: using multilevel analysis to accommodate nested data
inferredcites →https://doi.org/10.1038/nrg3461openalex-snapshot
Pleiotropy in complex traits: challenges and strategies
inferredcites →https://doi.org/10.1038/nrg3706openalex-snapshot
Statistical power and significance testing in large-scale genetic studies
inferredcites →https://doi.org/10.1038/s41467-018-03242-8openalex-snapshot
Item-level analyses reveal genetic heterogeneity in neuroticism
inferredcites →https://doi.org/10.1038/s41467-018-03819-3openalex-snapshot
Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways
inferredcites →https://doi.org/10.1038/s41588-017-0009-4openalex-snapshot
Multi-trait analysis of genome-wide association summary statistics using MTAG
inferredcites →https://doi.org/10.1038/s41588-018-0090-3openalex-snapshot
Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression
inferredcites →https://doi.org/10.1038/s41588-018-0152-6openalex-snapshot
Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence
inferredcites →https://doi.org/10.1038/s41588-018-0271-0openalex-snapshot
A linear mixed-model approach to study multivariate gene–environment interactions
inferredcites →https://doi.org/10.1038/s41588-019-0481-0openalex-snapshot
A global overview of pleiotropy and genetic architecture in complex traits
inferredcites →https://doi.org/10.1038/srep38837openalex-snapshot
Multivariate simulation framework reveals performance of multi-trait GWAS methods
inferredcites →https://doi.org/10.1080/00949650802412607openalex-snapshot
Distribution of Fisher's combination statistic when the tests are dependent
inferredcites →https://doi.org/10.1086/302193openalex-snapshot
Combined Linkage and Association Sib-Pair Analysis for Quantitative Traits
inferredcites →https://doi.org/10.1086/383251openalex-snapshot
A Simple Correction for Multiple Testing for Single-Nucleotide Polymorphisms in Linkage Disequilibrium with Each Other
inferredcites →https://doi.org/10.1086/519795openalex-snapshot
PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses
inferredcites →https://doi.org/10.1093/ajcp/15.11.552bopenalex-snapshot
Statistical Methods for Research Workers
inferredcites →https://doi.org/10.1093/bioinformatics/btn563openalex-snapshot
A multivariate test of association
inferredcites →https://doi.org/10.1093/biomet/73.3.751openalex-snapshot
An Improved Bonferroni Procedure for Multiple Tests of Significance
inferredcites →https://doi.org/10.1101/305029openalex-snapshot
Genomic SEM Provides Insights into the Multivariate Genetic Architecture of Complex Traits
inferredcites →https://doi.org/10.1111/ahg.12110openalex-snapshot
Statistical Methods for Association Tests of Multiple Continuous Traits in Genome‐Wide Association Studies
inferredcites →https://doi.org/10.1111/jcmm.13042openalex-snapshot
Susceptibility loci for metabolic syndrome and metabolic components identified in Han Chinese: a multi‐stage genome‐wide association study
inferredcites →https://doi.org/10.1155/2012/652569openalex-snapshot
Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies
inferredcites →https://doi.org/10.1161/circgenetics.111.961482openalex-snapshot
Genome-Wide Screen for Metabolic Syndrome Susceptibility Loci Reveals Strong Lipid Gene Contribution But No Evidence for Common Genetic Basis for Clustering of Metabolic Syndrome Traits
inferredcites →https://doi.org/10.1186/1471-2105-14-151openalex-snapshot
Analysis of multiple phenotypes in genome-wide genetic mapping studies
inferredcites →https://doi.org/10.1186/2047-217x-4-1openalex-snapshot
SmileFinder: a resampling-based approach to evaluate signatures of selection from genome-wide sets of matching allele frequency data in two or more diploid populations
inferredcites →https://doi.org/10.1186/s12859-015-0868-6openalex-snapshot
An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function
inferredcites →https://doi.org/10.1186/s13742-015-0047-8openalex-snapshot
Second-generation PLINK: rising to the challenge of larger and richer datasets
inferredcites →https://doi.org/10.1371/journal.pgen.1000792openalex-snapshot
Autoimmune Disease Classification by Inverse Association with SNP Alleles
inferredcites →https://doi.org/10.1371/journal.pgen.1003235openalex-snapshot
TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies
inferredcites →https://doi.org/10.1371/journal.pgen.1004445openalex-snapshot
Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data
inferredcites →https://doi.org/10.1371/journal.pone.0034861openalex-snapshot
MultiPhen: Joint Model of Multiple Phenotypes Can Increase Discovery in GWAS
inferredcites →https://doi.org/10.1371/journal.pone.0065245openalex-snapshot
A Unified Framework for Association Analysis with Multiple Related Phenotypes
inferredcites →https://doi.org/10.1371/journal.pone.0071494openalex-snapshot
Novel Genetic Analysis for Case-Control Genome-Wide Association Studies: Quantification of Power and Genomic Prediction Accuracy
inferredcites →https://doi.org/10.1371/journal.pone.0093766openalex-snapshot
Fast Principal Component Analysis of Large-Scale Genome-Wide Data
inferredcites →https://doi.org/10.1371/journal.pone.0095923openalex-snapshot
A Comparison of Multivariate Genome-Wide Association Methods
inferredcites →https://doi.org/10.1371/journal.pone.0140348openalex-snapshot
Association Tests of Multiple Phenotypes: ATeMP
inferredcites →https://doi.org/10.1375/twin.13.6.525openalex-snapshot
Genetic Association in Multivariate Phenotypic Data: Power in Five Models
inferredcites →https://doi.org/10.18637/jss.v045.i03openalex-snapshot
mice: Multivariate Imputation by Chained Equations inR
inferredcites →https://doi.org/10.2307/2284191openalex-snapshot
Factor Analysis as a Statistical Method.
inferredcites →https://doi.org/10.2307/2342720openalex-snapshot
Statistical Methods for Research Workers.
inferredcites →https://doi.org/10.2307/2529826openalex-snapshot
400: A Method for Combining Non-Independent, One-Sided Tests of Significance
inferredcites →https://doi.org/10.25336/p6cc87openalex-snapshot
An Introduction to the Use of Linear Models with Correlated Data
inferredcites →https://doi.org/10.4324/9780203843130openalex-snapshot
Applied Multivariate Statistics for the Social Sciences
inferredcites →https://doi.org/10.4324/9781315814919openalex-snapshot
Applied Multivariate Statistics for the Social Sciences
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1038/s41562-021-01182-wopenalex-snapshot
Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits
inferred← citeshttps://doi.org/10.1093/bib/bbad181openalex-snapshot
Integrating multiple traits for improving polygenic risk prediction in disease and pharmacogenomics GWAS
inferred← citeshttps://doi.org/10.1093/bib/bbad470openalex-snapshot
Applying polygenic risk score methods to pharmacogenomics GWAS: challenges and opportunities
inferred← citeshttps://doi.org/10.1101/623728openalex-snapshot
Multi-trait genome-wide association meta-analysis of dietary intake identifies new loci and genetic and functional links with metabolic traits
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