Ichg 2011, genomes project data tutorial, imputation in gwas studies, bryan howie created date. The catalog of human genetic variation has been rapidly growing over. Imputation of sequence variants for identification of genetic. Genotype imputation 1,2 is the process of predicting genotypes that are not directly assayed in a sample of individuals. Genotype imputation is a statistical technique that is often used to increase the power and resolution of genetic association studies. Jun 23, 2011 in genomewide association studies gwas, imputation can improve the coverage of genotyping arrays,, which only measure a small proportion of genetic variation in a study sample. Dec 12, 2008 missing genotype data in genetic association studies is a common problem often caused by poor dna quality and inadequate genotype calling algorithms, and imputation has been widely used to infer missing genotype data. Multiple genetic association studies most associated common variants have small effect sizes e. Illumina, the company that provides chips to companies that test autosomal dna for genetic genealogy has obsoleted their omniexpress chip previously in use, forcing. Genotype imputation for genomewide association studies jonathan marchini and bryan howie abstract in the past few years genomewide association gwa studies have uncovered a large number of convincingly replicated associations for many complex human diseases. For gwas, such metaanalyses are necessitated by the need for large sample sizes to discover modest genetic effects figure 2.
In the past decade, genomewide association studies gwas have identified numerous genetic variants that are associated with human traits. The aim of this talk is to introduce the idea of genotype imputation for genomewide association studies. I will start with a short overview of what genotype imputation is and then well give a quick summary of the basic idea behind how imputation works. Genotype imputation enables powerful combined analyses of. Imputation in genomewide association analysis hstalks. Each column shows a particular error rate ij, where ij represents the probability that. Until recently, the word imputation wasnt a part of the vocabulary of genetic genealogy, but earlier this year, it became a factor and will become even more important in coming months. This technique allows geneticists to accurately evaluate the evidence for association at genetic. Genotype imputation is particularly useful for combining results across studies that rely on different genotyping platforms but also increases the power of. Data quality control in genetic casecontrol association studies.
These studies are complex and must be planned carefully in order to maximize the probability of finding novel associations. Nearest neighbor imputation for categorical data by weighting. The imputation method, based on the li and stephens model and implemented in beagle v. Genotype imputation is now an essential tool in the analysis of genomewide association scans. Data quality control in genetic casecontrol association. Jun 16, 2009 although highthroughput genotyping arrays have made wholegenome association studies wgas feasible, only a small proportion of snps in the human genome are actually surveyed in such studies. This approach can confer a number of improvements on genome. Genetic association an overview sciencedirect topics. Genomewide imputation of untyped markers allows us to. Smith b, chen z, reimers l, van doorslaer k, schiffman m, et al. Genetic association analysis of candidate gene regions without any preceding linkage analysis has a long history of discovering single marker disease allele associations. Genotype imputation infers missing genotypes in silico using haplotype information from reference samples with genotypes from denser genotyping arrays or sequencing.
Imputation methods work by using haplotype patterns in a reference panel to predict unobserved genotypes in a study dataset, and a number of approaches have been proposed for choosing subsets of reference haplotypes that will. A new multipoint method for genomewide association. Snps, imputation and haplotypes nilanjan chatterjee, yihau chen, sheng luo and raymond j. A multiplephenotype imputation method for genetic studies. A tutorial on statistical methods for population association. Balding abstract although genetic association studies have been with us for many years, even for the simplest analyses there is little consensus on the most appropriate statistical procedures. The approach works by finding haplotype segments that are shared between study individuals, who are typically genotyped on a commercial. Such approaches typically analyze thousands of nominally unrelated individuals and search for correlations between genetic variants and a single trait of interest. Valdes, in genetics of bone biology and skeletal disease, 20. Genetic association analysis of candidate gene regions without any preceding linkage analysis has a long history of discovering singlemarker disease allele associations. Although prospective logistic regression is the standard method of analysis for casecontrol data, it. Beagle genetic analysis software university of washington. Although highthroughput genotyping arrays have made wholegenome association studies wgas feasible, only a small proportion of snps in the human genome are actually surveyed in such studies. Genotype imputation with thousands of genomes genetics.
Although prospective logistic regression is the standard method of analysis for casecontrol data, it has been recently noted that. Imputation in genetics refers to the statistical inference of unobserved genotypes. Genetic association studies have yielded a wealth of biological discoveries. The association between genetic variability at the lrrk2 locus and parkinsons disease is mechanistically interesting because data suggest that this association is a result of variability outside the common g2019s mutation, which raises the possibility that splicing or expression of wildtype lrrk2 might be pathologically important. Genotype imputation and genetic association studies of uk. Imputation provides a probability for each of the three possible genotype classes, and calls are based on the most likely genotype at. We present a genotype imputation method that scales to millions of reference samples. Current software for genotype imputation pdf paperity. The objectives of this study were to estimate and compare vitiligo heritability in europeanderived patients using both familybased and deep imputation genotypebased approaches. Genotype imputation is a key step in the analysis of gwas.
This approach is limited to that, and it relies upon a. A multiple phenotype imputation method for genetic studies. Strategies for imputing and analyzing rare variants in. Pdf sequence imputation of hpv16 genomes for genetic. Beagle is a state of the art software package for analysis of largescale genetic data sets with hundreds of thousands of markers genotyped on thousands of samples. Autoimmune vitiligo is a complex disease involving polygenic risk from at least 50 loci previously identified by genomewide association studies. Sep 05, 2017 concepts imputation posted on september 5, 2017 by roberta estes until recently, the word imputation wasnt a part of the vocabulary of genetic genealogy, but earlier this year, it became a factor and will become even more important in coming months. At the same time, harnessing genetic relatedness, even amongst nominally unrelated samples, to boost power in association studies is becoming increasingly prevalent. Despite the progresses of genomewide association studies gwass in revealing genetic mechanisms of human complex traits, the basis through which most identified risk variants function are highly unknown and need further investigations as well as discoveries. Advancements of transcriptome imputation and related. It is achieved by using known haplotypes in a population, for instance from the hapmap or the genomes project in humans, thereby allowing to test for association between a trait of interest e. May, 2019 this approach can confer a number of improvements on genome.
An efficient approach to characterizing the disease burden of rare variants may be to impute them into existing large datasets. Integration of genetic and clinical information to improve. Statistical power in genetic association studies in diverse populations lucy huang, chaolong wang, and noah a. Sequence imputation of hpv16 genomes for genetic association. Sometimes, also the information may not be recorded or included. Imputation of 3 million snps in the arabidopsis regional. It is well known that the ability to impute a rare variant is dependent both on the array choice and number of individuals in the reference. Genotype imputation is particularly useful for combining results across studies that rely on different genotyping platforms but also increases the power. Sequence imputation of hpv16 genomes for genetic association studies article pdf available in plos one 66. In addition, various snp arrays assay different sets of snps, which leads to challenges in comparing results and merging data for metaanalyses. Genotype imputation 1,2 is the process of predicting genotypes that are not directly. Arabidopsis thaliana, imputation accuracy, regional mapping, 1001 genomes project, genomewide association study.
These studies, however, mostly involve small sample sizes, and a majority of them have not been replicated in additional cohorts. Deep genotype imputation captures virtually all heritability. A central challenge in this area is the development of. Author summary genomewide association studies are a powerful and now widelyused method for finding genetic variants that increase the risk of developing particular diseases. Strategies for imputation that are specific to genetic data leverage knowledge of linkage disequilibrium ld between single. Rare genetic variants may be responsible for a significant amount of the uncharacterized genetic risk underlying many diseases. Imputation is based on ld, so it will not predict completely independent regions of the genome.
Fast and accurate genotype imputation in genomewide. Genotype imputation with millions of reference samples. The number of lines in this file corresponds to the number of datasets in the working directory. Nearest neighbor imputation for categorical data by. The relationship between imputation error and statistical. This technique allows geneticists to accurately evaluate the evidence for association at genetic markers that are not directly genotyped. Therefore, an imputed marker with a dramatically different association statistic than the surrounding directly genotyped markers. The main design choices to be made relate to sample sizes and choice of. Genomewide association studies gwas have successfully uncovered many associated loci. Typically, a subset of single nucleotide polymorphisms snps from individuals in a study population is assayed for association with a particular disease or. Many such errors can be avoided through careful collection of case and control groups and. Genotype imputation for genomewide association studies. Genotype imputation is an important tool for genomewide association studies as it increases power, aids in finemapping of associations and facilitates metaanalyses. I will then describe one of the first methods of genotype imputation post called impute v1.
Nov 01, 2011 genotype imputation is a statistical technique that is often used to increase the power and resolution of genetic association studies. Missing genotype data in genetic association studies is a common problem often caused by poor dna quality and inadequate genotype calling algorithms, and imputation has been widely used to infer missing genotype data. The genotype imputation strategy for casecontrol genetic association studies provides an economical way of assessing many more genetic markers for disease association than have actually been measured in any particular association study. Framed as an odds ratio, the odds of an outcome after an exposure. Biases in study design and errors in genotype calling have the potential to introduce systematic biases into genetic casecontrol association studies, leading to an increase in the number of falsepositive and falsenegative associations see box 1 for a glossary of terms. Genotype imputation is particularly useful for combining results across studies that rely on different genotyping platforms but also increases the power of individual scans. Jul 22, 2012 genotype imputation is a key step in the analysis of gwas. The genotypeimputation strategy for casecontrol genetic association studies provides an economical way of assessing many more genetic markers for disease association than have actually been measured in any particular association study. Genotype imputation can be carried out across the whole genome as part of a genomewide association gwa study or in a more focused region as part of a finemapping study. Concepts imputation dnaexplained genetic genealogy.
It is most likely that some respondentspatients do not provide the complete information on the queries, which is the most common reason for missing values. Strategies for imputation that are specific to genetic data leverage knowledge of linkage disequilibrium ld between single nucleotide. Imputation is an in silico method that can increase the power of association studies by inferring missing genotypes, harmonizing data sets for meta. It achieves fast, accurate, and memoryefficient genotype imputation by restricting the probability. A tutorial on statistical methods for population association studies david j. Mixed models, reemerging from the linkage and animal genetics literature 9 11, are now routinely used to search for associations in the presence of relatedness or population. Recent advancements of transcriptome predictions put the transcriptomewide association studies. Genetic association studies of bpd have attempted to identify specific candidate genes involved in the biologic pathways regulating the processes noted in figure 21. The main design choices to be made relate to sample sizes and choice of commercially available. Association studies determine if a particular genetic feature exposure cooccurs with a trait disease more often than would be expected by chance. Imputation methods work by using haplotype patterns in a reference panel to predict unobserved genotypes in a study dataset, and a number of approaches have been proposed for choosing subsets of reference haplotypes that will maximize accuracy in a given study. However, a complete characterization of the etiology of most traits remains elusive.
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