Author summary genomewide association studies are a powerful and now widelyused method for finding genetic variants that increase the risk. However, few studies have reported for the genetic foundation of photosynthetic response to low p stress in soybean. Class readings efficiency and power in genetic association studies selecting a from csci 295 at brown university. Abstract selecting the best design for genetic association studies. In genetic association studies, rare variants with extremely small allele frequency play a crucial role in complex traits, and the setbased testing methods that jointly assess the effects of groups of single nucleotide polymorphisms snps were developed to improve powers for the association tests. Not efficient at discriminating between small differences. Haploview is a commonly used bioinformatics software which is designed to analyze and visualize patterns of linkage disequilibrium ld in genetic data.
Pdf we investigated selection and analysis of tag snps for genomewide association studies by specifically examining the relationship between. Cancer and other complex diseases are influenced by a combination of genetic and environmental factors. The calculation of the power and sample size required for association studies is essential, particularly for followup of genomewide association studies, where much genotyping is required to replicate the original finding and identify the true disease susceptibility mutation. To identify genetic variants with modest effects on complex human diseases, a growing number of networks or consortia are created for sharing data from multiple genomewide association studies on the same disease or related disorders. For each set of parameters, we simulated 10,000 casecontrol studies varying the degree of matching, that is, the. Pga is a package of algorithms and graphical user interfaces developed in matlab for power and sample size calculation under various genetic models and statistical constraints. Metaanalysis of genomewide association studies with. Methodological issues in multistage genomewide association. To address this issue, 219 soybean accessions were genotyped by 292,035 highquality single nucleotide polymorphisms snps and phenotyped under normal and low p. There are similarities between genetic association studies and classic epidemiological studies of environmental risk factors but there are also issues that are specific to studies of genetic risk factors such as the use of particular familybased designs, the need to account for different. Haploview can also perform association studies, choosing tagsnps and estimating haplotype frequencies. A subsetbased approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits previous article genetic adaptation of fattyacid metabolism.
Power of genetic association studies in the presence of. Genetic association studies circulation aha journals. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Genomewide association studies gwas to scan 1 to 2. Thus, it is an indispensable procedure both for a priori and a posteriori analyses in genetic association studies. Sample size required for the tdt and the casecontrol designs was studied for markerbased genomewide scans for disease association. This article provides a broad outline of the design and analysis of such studies, focusing on casecontrol studies in candidate genes or regions. Gwas have evolved standards for study design, analysis, replication and interpretation.
Strengthening the reporting of genetic association studies. Pdf efficiency and power in genetic association studies. Genetic epidemiology research institute school of medicine university of california, irvine irvine, ca genetic epidemiology association studies and power considerations question approach is there evidence for genetic influences on a quantitative trait. Powerful and efficient strategies for genetic association testing of. Genome wide association studies a genomewide association study. Genetic association studies test for a correlation between disease status and genetic variation to identify candidate genes or genome regions that contribute to a specific disease. Similar to the genetic association study of human diseases, the casecontrol longevity study is also affected by factors such as population substructure or stratification, which is not considered in this simulation.
One approach to increasing the power of these studies is to enrich the case sample for individuals likely to be affected because of genetic factors. The power for genetic association analyses pga package was developed in matlab and consists a toolbox of command line functions and three unifying graphical user interfaces guis. Statistical power calculations are crucial in designing genetic association studies. A humanspecific haplotype increasing the biosynthesis of longchain omega3 and omega6 fatty acids. To choose the proper sample size and genotyping platform for such studies, power calculations that take into account genetic model, tag snp selection, and the population of interest are required. We assessed the power and efficiency of casecontrol studies under a variety of assumptions regarding the prevalence and the effects of the matching factor and the exposure of interest as well as their association in the population. The influence of various parameters on sample size required to attain a given level of power was analyzed in detail. We have developed the power for genetic association analyses. The cochranarmitage trend test has been used in casecontrol studies for testing genetic association. In this communication, wecompare the asymptotic behavior of two commonly used test statistics the score statistic z.
In the present study, we used an f2 chicken population in a genomewide association study gwas to detect potential genetic variants and candidate genes associated with daily feed. To scan several thousand snps on many individuals to find genetic variations associated with a particular disease. Genetic association studies are performed to determine whether a genetic variant is associated with a disease or trait. A subsetbased approach improves power and interpretation for. Dec 01, 2004 the power of a genetic mapping study depends on the heritability of the trait, the number of individuals included in the analysis, and the genetic dissimilarity among them. The software is designed to facilitate decision making for casecontrol association studies of candidate genes, finemapping studies, and wholegenome scans. As the variance of the test statistic is a function. Genomewide association studies are a promising new tool for deciphering the genetics of complex diseases. Pdf greater power and computational efficiency for. Efficiency and power as a function of sequence coverage, snp. Next we compared the power of gamut with univariate kmr and linear regression analyses in a series of simulation studies. Increasing feed costs prompt geneticists to include feed intake and efficiency as selection goals in breeding programs.
Frontiers genomewide association studies of photosynthetic. In the genetic association study of complex diseases in humans, small sample size is a frequent problem responsible for insufficient power to detect minoreffect genes. Because expected power in disease association studies is the most relevant measure of merit e. Fingerlin te, boehnke m and abecasis gr am j hum genet 2004 74. Increasing the power and efficiency of diseasemarker casecontrol association studies through use of allelesharing information. Dec 11, 2009 in the relatively brief but highly informative history of genomewide association studies gwas, 1 metaanalysis of individual participant data or summary results has proven to be a crucial step. Power for genetic association analyses pga tool national. This article provides a broad outline of the design and analysis of such studies, focusing on case control studies in candidate genes or regions. Genetic epidemiology association studies and power. Genetic association studies are used to find candidate genes or genome regions that contribute to a specific disease by testing for a correlation between disease status and genetic variation. In many instances, the results of individual studies were unremarkable, and statistically compelling findings only emerged after aggressive data. Gwas are particularly useful in finding genetic variations that.
Aug 28, 2018 photosynthesis is the basis of plant growth and development, and is seriously affected by low phosphorus p stress. Efficiency and power in genetic association studies. To facilitate widespread use of power analysis in the design and interpretation of genetic studies, it is important. Help develop better strategies to detect, treat and prevent the disease. On estimation of the variance in cochranarmitage trend.
May, 2008 alternatively, power analysis can be used to explore possible reasons for equivocal or negative results. Power and efficiency of the tdt and casecontrol design for. Small genotypic relative risks, low levels of linkage disequilibrium, and departure from equal frequencies for the disease allele and associated. Users with a matlab software can run the three guis or the command line functions in matlab environment. Power for genetic association study of human longevity. Moreover, the power estimates are for gene alleles in complete linkage disequilibrium with the causal gene. In experiments that involve microarrays or other complex physiological assays, phenotyping can be expensive and timeconsuming and may impose limits on the sample size. Genetic association studies should not be pursued unless the trait. However, other technologies can be more efficient in some settings by a reducing redundant coverage within samples and b exploiting patterns of genetic variation across samples. Joint analysis is more efficient than replicationbased. Power is robust to the completeness of the reference panel from which tags are selected. Power for genetic association study of human longevity using.
Degree of matching and gain in power and efficiency in. Increasing the power and efficiency of diseasemarker case. Casecontrol diseasemarker association studies are often used in the search for variants that predispose to complex diseases. Sep 01, 2014 read some statistical properties of efficiency robust tests with applications to genetic association studies, scandinavian journal of statistics on deepdyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips. Pdf design efficiency in genetic association studies. To characterize as many samples as possible, many genetic studies therefore employ lower coverage sequencing or snp array genotyping coupled to statistical imputation.
Efficiency robust statistics for genetic linkage and. Efficiency and power in genetic association studies article pdf available in nature genetics 3711. For a study of a single phenotype and multiple snps, the most efficient way to limit the number of tests is to perform a single test per snp. Statistical power is often a limiting factor for genetic association studies, and no comprehensive software has been a vail able for the full assessment of power and comparison of study designs. We set out to study the tradeoffs between efficiency and power for different tagging and testing approaches. Similarly, 1 major factor that explains the inconsistency in genelongevity associations is that a sizable proportion of the studies could have been underpowered by the small sample sizes used. The statistical efficiency power of allele scores can be increased by weighting each variant by the size of its association with the risk factor16 weaktrument ins biascancur oc in mendelian randomisation studies when using one or more genetic variants that only explain a small. These findings have implications for prioritizing tag snps and interpreting association studies. They help guide tradeoffs between large sample sizes and detailed assessments of genotype and phenotype, help determine which studies are viable, and help interpret research findings. Oct 23, 2005 because expected power in disease association studies is the most relevant measure of merit e. Genomewide association studies for feed intake and. Efficiency and power in genetic association studies nature.
Finally, we focus on power in the context of modern wholegenome association studies, in which issues of coverage, multiple testing, and staged designs are paramount. A higher frequency of a singlenucleotide polymorphism snp allele or genotype in a series of individuals affected with. Genetic architecture of quantitative traits in beef cattle. Efficient inference for genetic association studies with. Efficiency robust statistics for genetic linkage and association studies under genetic model uncertainty jungnam joo office of biostatistics research, national heart, lung and blood institute, bethesda, md, u. Greater power and computational efficiency for kernelbased association testing of sets of genetic variants. Zheng, some statistical properties of efficiency robust tests with applications to. Genetic epidemiology association studies and power considerations. Asymptotic relative efficiencies of the score and robust. Despite the many similarities between genetic association studies and classical observational epidemiologic studies that is, crosssectional, casecontrol, and cohort of lifestyle and environmental factors, genetic association studies present several specific challenges including an unprecedented volume of new data 5,6 and the. Power for genetic association study of human longevity using the casecontrol design article pdf available in american journal of epidemiology 1688.
794 1508 882 1384 1236 303 507 1386 284 769 923 40 789 906 489 951 937 969 423 615 845 323 861 315 1170 959 714 156 1155 1254 1206