Statistical power to detect genetic (co)variance of complex traits using SNP data in unrelated samples.
paper
Cited
Public
- Authors
- Visscher, Peter M; Hemani, Gibran; Vinkhuyzen, Anna A E; Chen, Guo-Bo; Lee, Sang Hong; Wray, Naomi R; Goddard, Michael E; Yang, Jian
- Year
- 2014
- Journal
- PLoS genetics
- PMID
- 24721987
- DOI
- 10.1371/journal.pgen.1004269
- PMCID
- PMC3983037
We have recently developed analysis methods (GREML) to estimate the genetic variance of a complex trait/disease and the genetic correlation between two complex traits/diseases using genome-wide single nucleotide polymorphism (SNP) data in unrelated individuals. Here we use analytical derivations and simulations to quantify the sampling variance of the estimate of the proportion of phenotypic variance captured by all SNPs for quantitative traits and case-control studies. We also derive the approximate sampling variance of the estimate of a genetic correlation in a bivariate analysis, when two complex traits are either measured on the same or different individuals. We show that the sampling variance is inversely proportional to the number of pairwise contrasts in the analysis and to the variance in SNP-derived genetic relationships. For bivariate analysis, the sampling variance of the genetic correlation additionally depends on the harmonic mean of the proportion of variance explained by the SNPs for the two traits and the genetic correlation between the traits, and depends on the phenotypic correlation when the traits are measured on the same individuals. We provide an online tool for calculating the power of detecting genetic (co)variation using genome-wide SNP data. The new theory and online tool will be helpful to plan experimental designs to estimate the missing heritability that has not yet been fully revealed through genome-wide association studies, and to estimate the genetic overlap between complex traits (diseases) in particular when the traits (diseases) are not measured on the same samples.
Standard error of the estimate of variance explained by all SNPs vs. sample size.The first three columns are the averaged standard error observed from 100 simulations under three heritability levels. The last column is the predicted standard error from our approximation theory. The plotted data can be found in Table S1.
Standard error (SE) of the estimate of variance explained by all SNPs on the underlying scale () from a univariate analysis of a case-control study vs. total number of cases and controls (sample size).The SE is predicted from the approximation theory given different levels of disease prevalence (K) and proportion of cases in the sample (v).
Statistical power of detecting genetic variance (correlation) under different study designs. a) Univarite analysis of a quantitative trait. b) Univariate analysis of a case-control study assuming equal number of cases and controls (v = 0.5) and heritability of liability () of 0.2. c) Bivariate analysis of two quantitative traits measured on the same set of individuals, assuming heritability of 0.2 for both traits. d) Bivariate analysis of two case-control studies on independent sets of samples, assuming equal numbers of cases and controls for each disease, and equal sample size (total number of cases and controls), equal heritability of liability ( = 0.2) and equal prevalence (K = 0.01) for both diseases.
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| Heritability estimates from genomewide relatedness matrices in wild populations: Application to a passerine, using a small sample size. | Perrier C et al. | β | 2018 | β |
| Identification of genes related to intramuscular fat content of pigs using genome-wide association study. | Won S et al. | β | 2018 | β |
| International Union of Basic and Clinical Pharmacology CIV: The Neurobiology of Treatment-resistant Depression: From Antidepressant Classifications to Novel Pharmacological Targets. | Caraci F et al. | β | 2018 | β |
| <i>PRDM16</i> Gene Polymorphism Is Associated with Obesity and Blood Lipids Profiles in Saudi Population. | AlAmrani A et al. | β | 2018 | β |
| Multi-level genomic analyses suggest new genetic variants involved in human memory. | Zhu Z et al. | β | 2018 | β |
| Nature vs. nurture in human sociality: multi-level genomic analyses of social conformity. | Chen B et al. | β | 2018 | β |
| Partitioning Phenotypic Variance Due to Parent-of-Origin Effects Using Genomic Relatedness Matrices. | Laurin C et al. | β | 2018 | β |
| Power and sample size calculations for high-throughput sequencing-based experiments. | Li CI et al. | β | 2018 | β |
| Real-life helping behaviours in North America: A genome-wide association approach. | Primes G et al. | β | 2018 | β |
| Recovery of novel association loci in Arabidopsis thaliana and Drosophila melanogaster through leveraging INDELs association and integrated burden test. | Song B et al. | β | 2018 | β |
| Required properties for markers used to calculate unbiased estimates of the genetic correlation between populations. | Wientjes YCJ et al. | β | 2018 | β |
| The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) consortium: A collaborative cognitive and neuroimaging genetics project. | Blokland GAM et al. | β | 2018 | β |
| The State of "<i>Omics</i>" Research for Farmed Penaeids: Advances in Research and Impediments to Industry Utilization. | Guppy JL et al. | β | 2018 | β |
| Using the Mus musculus hybrid zone to assess covariation and genetic architecture of limb bone lengths. | Ε krabar N et al. | β | 2018 | β |
| ATP binding cassette and cholecystokinin A receptor genetic variations in gallstone susceptibility. | Milanizadeh S et al. | β | 2017 | β |
| Concepts, estimation and interpretation of SNP-based heritability. | Yang J et al. | β | 2017 | β |
| Cross-ethnic meta-analysis identifies association of the GPX3-TNIP1 locus with amyotrophic lateral sclerosis. | Benyamin B et al. | β | 2017 | β |
| Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene-mapping approach. | Li Z et al. | β | 2017 | β |
| Do regional brain volumes and major depressive disorder share genetic architecture? A study of Generation Scotland (n=19β762), UK Biobank (n=24β048) and the English Longitudinal Study of Ageing (n=5766). | Wigmore EM et al. | β | 2017 | β |
| Genetic architecture of epigenetic and neuronal ageing rates in human brain regions. | Lu AT et al. | β | 2017 | β |
| Genetic correlations reveal the shared genetic architecture of transcription in human peripheral blood. | Lukowski SW et al. | β | 2017 | β |
| Genetic factors affecting EBV copy number in lymphoblastoid cell lines derived from the 1000 Genome Project samples. | Mandage R et al. | β | 2017 | β |
| Genetics of depressive symptoms in adolescence. | Sallis H et al. | β | 2017 | β |
| Genome-wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers. | Deming Y et al. | β | 2017 | β |
| Genome-wide association study of facial emotion recognition in children and association with polygenic risk for mental health disorders. | Coleman JRI et al. | β | 2017 | β |
| Genome-wide Regional Heritability Mapping Identifies a Locus Within the TOX2 Gene Associated With Major Depressive Disorder. | Zeng Y et al. | β | 2017 | β |
| Heritability of Atrial Fibrillation. | Weng LC et al. | β | 2017 | β |
| Hidden heritability due to heterogeneity across seven populations. | Tropf FC et al. | β | 2017 | β |
| Human Facial Shape and Size Heritability and Genetic Correlations. | Cole JB et al. | β | 2017 | β |
| Independent Maternal and Fetal Genetic Effects on Midgestational Circulating Levels of Environmental Pollutants. | Traglia M et al. | β | 2017 | β |
| Investigating the genetic relationship between Alzheimer's disease and cancer using GWAS summary statistics. | Feng YA et al. | β | 2017 | β |
| Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies. | de Vlaming R et al. | β | 2017 | β |
| Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations. | Wientjes YCJ et al. | β | 2017 | β |
| Phenome-wide heritability analysis of the UK Biobank. | Ge T et al. | β | 2017 | β |
| Phenotypic and Genetic Relationship Between BMI and Drinking in a Sample of UK Adults. | Wills AG et al. | β | 2017 | β |
| Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the <i>Caenorhabditis elegans</i> Multiparental Experimental Evolution (CeMEE) Panel. | Noble LM et al. | β | 2017 | β |
| Reevaluation of SNP heritability in complex human traits. | Speed D et al. | β | 2017 | β |
| Shared genetic influences between dimensional ASD and ADHD symptoms during child and adolescent development. | Stergiakouli E et al. | β | 2017 | β |
| SNP-Based Heritability Estimates of Common and Specific Variance in Self- and Informant-Reported Neuroticism Scales. | Realo A et al. | β | 2017 | β |
| The low single nucleotide polymorphism heritability of plasma and saliva cortisol levels. | Neumann A et al. | β | 2017 | β |
| Application of linear mixed models to study genetic stability of height and body mass index across countries and time. | Trzaskowski M et al. | β | 2016 | β |
| Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation. | Gusev A et al. | β | 2016 | β |
| Attentional biases to emotional stimuli: Key components of the RDoC constructs of sustained threat and loss. | Gibb BE et al. | β | 2016 | β |
| Cohort Effects in the Genetic Influence on Smoking. | Domingue BW et al. | β | 2016 | β |
| Defining a Contemporary Ischemic Heart Disease Genetic Risk Profile Using Historical Data. | Mosley JD et al. | β | 2016 | β |
| Detecting polygenic selection in marine populations by combining population genomics and quantitative genetics approaches. | Gagnaire PA et al. | β | 2016 | β |
| Detection and interpretation of shared genetic influences on 42 human traits. | Pickrell JK et al. | β | 2016 | β |
| Fast and Accurate Construction of Confidence Intervals for Heritability. | Schweiger R et al. | β | 2016 | β |
| GCTA-GREML accounts for linkage disequilibrium when estimating genetic variance from genome-wide SNPs. | Yang J et al. | β | 2016 | β |
| Genetic evidence for natural selection in humans in the contemporary United States. | Beauchamp JP | β | 2016 | β |
| Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum. | Lu AT et al. | β | 2016 | β |
| Genome-wide association study of response to cognitive-behavioural therapy in children with anxiety disorders. | Coleman JR et al. | β | 2016 | β |
| Genome-Wide Estimates of Heritability for Social Demographic Outcomes. | Domingue BW et al. | β | 2016 | β |
| Heritability of Hippocampal Formation Sub-region Volumes. | Greenspan KS et al. | β | 2016 | β |
| Identifying genetically driven clinical phenotypes using linear mixed models. | Mosley JD et al. | β | 2016 | β |
| Molecular Risk Factors for Schizophrenia. | Modai S et al. | β | 2016 | β |
| Multidimensional heritability analysis of neuroanatomical shape. | Ge T et al. | β | 2016 | β |
| Pharmacogenomics in diabetes mellitus: insights into drug action and drug discovery. | Zhou K et al. | β | 2016 | β |
| Pleiotropic Mechanisms Indicated for Sex Differences in Autism. | Mitra I et al. | β | 2016 | β |
| Polygenic Epidemiology. | Dudbridge F | β | 2016 | β |
| Single Nucleotide Polymorphism Heritability of a General Psychopathology Factor in Children. | Neumann A et al. | β | 2016 | β |
| SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE. | Docherty AR et al. | β | 2016 | β |
| Strategies for determining kinship in wild populations using genetic data. | StΓ€dele V et al. | β | 2016 | β |
| The Adapting Mind in the Genomic Era. | Fieder M et al. | β | 2016 | β |
| A Fast Method that Uses Polygenic Scores to Estimate the Variance Explained by Genome-wide Marker Panels and the Proportion of Variants Affecting a Trait. | Palla L et al. | β | 2015 | β |
| A gene-based information gain method for detecting gene-gene interactions in case-control studies. | Li J et al. | β | 2015 | β |
| A general unified framework to assess the sampling variance of heritability estimates using pedigree or marker-based relationships. | Visscher PM et al. | β | 2015 | β |
| Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types. | Sampson JN et al. | β | 2015 | β |
| Assessment of first and second degree relatives of individuals with bipolar disorder shows increased genetic risk scores in both affected relatives and young At-Risk Individuals. | Fullerton JM et al. | β | 2015 | β |
| Common genetic variation and schizophrenia polygenic risk influence neurocognitive performance in young adulthood. | Hatzimanolis A et al. | β | 2015 | β |
| Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis. | Loh PR et al. | β | 2015 | β |
| Does natural selection favour taller stature among the tallest people on earth? | Stulp G et al. | β | 2015 | β |
| Dominance genetic variation contributes little to the missing heritability for human complex traits. | Zhu Z et al. | β | 2015 | β |
| Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer's disease related cognitive functioning. | Levine ME et al. | β | 2015 | β |
| Estimation of Genetic Relationships Between Individuals Across Cohorts and Platforms: Application to Childhood Height. | Fedko IO et al. | β | 2015 | β |
| Familiality and SNP heritability of age at onset and episodicity in major depressive disorder. | Ferentinos P et al. | β | 2015 | β |
| Genetic analyses benefit from using less heterogeneous phenotypes: an illustration with the hospital anxiety and depression scale (HADS). | Laurin CA et al. | β | 2015 | β |
| Genetic Architecture of Lacunar Stroke. | Traylor M et al. | β | 2015 | β |
| Genetics and intelligence differences: five special findings. | Plomin R et al. | β | 2015 | β |
| Genomic architecture of human neuroanatomical diversity. | Toro R et al. | β | 2015 | β |
| Human fertility, molecular genetics, and natural selection in modern societies. | Tropf FC et al. | β | 2015 | β |
| Immunogenetics of systemic sclerosis: Defining heritability, functional variants and shared-autoimmunity pathways. | Bossini-Castillo L et al. | β | 2015 | β |
| Iron and hepcidin as risk factors in atherosclerosis: what do the genes say? | Galesloot TE et al. | β | 2015 | β |
| Large-scale genomics unveil polygenic architecture of human cortical surface area. | Chen CH et al. | β | 2015 | β |
| Massively expedited genome-wide heritability analysis (MEGHA). | Ge T et al. | β | 2015 | β |
| Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder. | Genetics of Personality Consortium et al. | β | 2015 | β |
| New data and an old puzzle: the negative association between schizophrenia and rheumatoid arthritis. | Lee SH et al. | β | 2015 | β |
| Novel directions for GΒ ΓΒ E analysis in psychiatry. | Vinkhuyzen AA et al. | β | 2015 | β |
| Pleiotropy across academic subjects at the end of compulsory education. | Rimfeld K et al. | β | 2015 | β |
| Relatedness in the post-genomic era: is it still useful? | Speed D et al. | β | 2015 | β |
| Single Nucleotide Polymorphism Heritability of Behavior Problems in Childhood: Genome-Wide Complex Trait Analysis. | Pappa I et al. | β | 2015 | β |
| Statistical power for identifying nucleotide markers associated with quantitative traits in genome-wide association analysis using a mixed model. | Shin J et al. | β | 2015 | β |
| The role of common genetic variation in educational attainment and income: evidence from the National Child Development Study. | Davies NM et al. | β | 2015 | β |
| Variation and covariation in strongyle infection in East African shorthorn zebu calves. | Callaby R et al. | β | 2015 | β |
| Do our "big data" in genetic analysis need to get bigger? | Baker LA | β | 2014 | β |
| Effect of polygenic risk scores on depression in childhood trauma. | Peyrot WJ et al. | β | 2014 | β |
| Genetic influence on family socioeconomic status and children's intelligence. | Trzaskowski M et al. | β | 2014 | β |
| Genome-wide interaction of genotype by erythrocyte n-3 fatty acids contributes to phenotypic variance of diabetes-related traits. | Zheng JS et al. | β | 2014 | β |
| Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. | Gusev A et al. | β | 2014 | β |
| Research review: Polygenic methods and their application to psychiatric traits. | Wray NR et al. | β | 2014 | β |