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Search Results: 1 - 10 of 209444 matches for " Alkes L. Price "
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Application of Ancestry Informative Markers to Association Studies in European Americans
Michael F Seldin ,Alkes L Price
PLOS Genetics , 2008, DOI: 10.1371/journal.pgen.0040005
Population Structure and Eigenanalysis
Nick Patterson ,Alkes L Price,David Reich
PLOS Genetics , 2006, DOI: 10.1371/journal.pgen.0020190
Abstract: Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to develop formal significance tests. We also uncover a general “phase change” phenomenon about the ability to detect structure in genetic data, which emerges from the statistical theory we use, and has an important implication for the ability to discover structure in genetic data: for a fixed but large dataset size, divergence between two populations (as measured, for example, by a statistic like FST) below a threshold is essentially undetectable, but a little above threshold, detection will be easy. This means that we can predict the dataset size needed to detect structure.
Single-Tissue and Cross-Tissue Heritability of Gene Expression Via Identity-by-Descent in Related or Unrelated Individuals
Alkes L. Price ,Agnar Helgason ,Gudmar Thorleifsson,Steven A. McCarroll,Augustine Kong,Kari Stefansson
PLOS Genetics , 2011, DOI: 10.1371/journal.pgen.1001317
Abstract: Family studies of individual tissues have shown that gene expression traits are genetically heritable. Here, we investigate cis and trans components of heritability both within and across tissues by applying variance-components methods to 722 Icelanders from family cohorts, using identity-by-descent (IBD) estimates from long-range phased genome-wide SNP data and gene expression measurements for ~19,000 genes in blood and adipose tissue. We estimate the proportion of gene expression heritability attributable to cis regulation as 37% in blood and 24% in adipose tissue. Our results indicate that the correlation in gene expression measurements across these tissues is primarily due to heritability at cis loci, whereas there is little sharing of trans regulation across tissues. One implication of this finding is that heritability in tissues composed of heterogeneous cell types is expected to be more dominated by cis regulation than in tissues composed of more homogeneous cell types, consistent with our blood versus adipose results as well as results of previous studies in lymphoblastoid cell lines. Finally, we obtained similar estimates of the cis components of heritability using IBD between unrelated individuals, indicating that transgenerational epigenetic inheritance does not contribute substantially to the “missing heritability” of gene expression in these tissue types.
Identifying repeat domains in large genomes
Degui Zhi, Benjamin J Raphael, Alkes L Price, Haixu Tang, Pavel A Pevzner
Genome Biology , 2006, DOI: 10.1186/gb-2006-7-1-r7
Abstract: Repetitive elements form a major fraction of eukaryotic genomes. Though once dismissed as mere junk DNA, they are now recognized as "drivers of genome evolution" [1] whose evolutionary role can be "symbiotic (rather than parasitic)" [2]. Examples of potentially beneficial evolutionary events in which repetitive elements have been implicated include genome rearrangements [1], gene-rich segmental duplications [3], random drift to new biological function [4,5] and increased rate of evolution during times of stress [6,7]. For these and other reasons, the study of repeat elements and their evolution is now emerging as a key area in evolutionary biology.Individual repeat elements can be grouped into repeat families, each defined by the consensus sequence of its diverged copies. Repeat family libraries, such as Repbase Update libraries [8,9] and RepeatMasker libraries [10], contain consensus sequences of known repeat families. Repeat families often contain shared subsequences, which we call repeat domains. Repeat domains can occur more than once within the same repeat family; for example, the ubiquitous human Alu family is dimeric [11]. There are a number of cases of repeat families whose repeat domains are known to have different biological origins, for example, from repeat families with different modes of replication or from distinct retrovirus families. These repeat families and the domains they share are worthy of special attention, since they are assumed to result from interesting evolutionary events. We define a repeat family to be a composite repeat if it contains at least two repeat domains of different biological origin. Of course, discerning the biological origin of a repeat domain is a challenging endeavor. Nevertheless, human Repbase Update documents more than 10 repeat families as composite repeats, including the RICKSHA and Harlequin families. Many other composite repeats contain fragments from different retroviruses. Since composite repeats that contain only
Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits
Noah Zaitlen ,Peter Kraft,Nick Patterson,Bogdan Pasaniuc,Gaurav Bhatia,Samuela Pollack,Alkes L. Price
PLOS Genetics , 2013, DOI: 10.1371/journal.pgen.1003520
Abstract: Important knowledge about the determinants of complex human phenotypes can be obtained from the estimation of heritability, the fraction of phenotypic variation in a population that is determined by genetic factors. Here, we make use of extensive phenotype data in Iceland, long-range phased genotypes, and a population-wide genealogical database to examine the heritability of 11 quantitative and 12 dichotomous phenotypes in a sample of 38,167 individuals. Most previous estimates of heritability are derived from family-based approaches such as twin studies, which may be biased upwards by epistatic interactions or shared environment. Our estimates of heritability, based on both closely and distantly related pairs of individuals, are significantly lower than those from previous studies. We examine phenotypic correlations across a range of relationships, from siblings to first cousins, and find that the excess phenotypic correlation in these related individuals is predominantly due to shared environment as opposed to dominance or epistasis. We also develop a new method to jointly estimate narrow-sense heritability and the heritability explained by genotyped SNPs. Unlike existing methods, this approach permits the use of information from both closely and distantly related pairs of individuals, thereby reducing the variance of estimates of heritability explained by genotyped SNPs while preventing upward bias. Our results show that common SNPs explain a larger proportion of the heritability than previously thought, with SNPs present on Illumina 300K genotyping arrays explaining more than half of the heritability for the 23 phenotypes examined in this study. Much of the remaining heritability is likely to be due to rare alleles that are not captured by standard genotyping arrays.
Effects of cis and trans Genetic Ancestry on Gene Expression in African Americans
Alkes L. Price ,Nick Patterson,Dustin C. Hancks,Simon Myers,David Reich,Vivian G. Cheung,Richard S. Spielman
PLOS Genetics , 2008, DOI: 10.1371/journal.pgen.1000294
Abstract: Variation in gene expression is a fundamental aspect of human phenotypic variation. Several recent studies have analyzed gene expression levels in populations of different continental ancestry and reported population differences at a large number of genes. However, these differences could largely be due to non-genetic (e.g., environmental) effects. Here, we analyze gene expression levels in African American cell lines, which differ from previously analyzed cell lines in that individuals from this population inherit variable proportions of two continental ancestries. We first relate gene expression levels in individual African Americans to their genome-wide proportion of European ancestry. The results provide strong evidence of a genetic contribution to expression differences between European and African populations, validating previous findings. Second, we infer local ancestry (0, 1, or 2 European chromosomes) at each location in the genome and investigate the effects of ancestry proximal to the expressed gene (cis) versus ancestry elsewhere in the genome (trans). Both effects are highly significant, and we estimate that 12±3% of all heritable variation in human gene expression is due to cis variants.
Integrating Functional Data to Prioritize Causal Variants in Statistical Fine-Mapping Studies
Gleb Kichaev,Wen-Yun Yang,Sara Lindstrom,Farhad Hormozdiari,Eleazar Eskin,Alkes L. Price,Peter Kraft,Bogdan Pasaniuc
PLOS Genetics , 2014, DOI: doi/10.1371/journal.pgen.1004722
Abstract: Standard statistical approaches for prioritization of variants for functional testing in fine-mapping studies either use marginal association statistics or estimate posterior probabilities for variants to be causal under simplifying assumptions. Here, we present a probabilistic framework that integrates association strength with functional genomic annotation data to improve accuracy in selecting plausible causal variants for functional validation. A key feature of our approach is that it empirically estimates the contribution of each functional annotation to the trait of interest directly from summary association statistics while allowing for multiple causal variants at any risk locus. We devise efficient algorithms that estimate the parameters of our model across all risk loci to further increase performance. Using simulations starting from the 1000 Genomes data, we find that our framework consistently outperforms the current state-of-the-art fine-mapping methods, reducing the number of variants that need to be selected to capture 90% of the causal variants from an average of 13.3 to 10.4 SNPs per locus (as compared to the next-best performing strategy). Furthermore, we introduce a cost-to-benefit optimization framework for determining the number of variants to be followed up in functional assays and assess its performance using real and simulation data. We validate our findings using a large scale meta-analysis of four blood lipids traits and find that the relative probability for causality is increased for variants in exons and transcription start sites and decreased in repressed genomic regions at the risk loci of these traits. Using these highly predictive, trait-specific functional annotations, we estimate causality probabilities across all traits and variants, reducing the size of the 90% confidence set from an average of 17.5 to 13.5 variants per locus in this data.
The History of African Gene Flow into Southern Europeans, Levantines, and Jews
Priya Moorjani ,Nick Patterson,Joel N. Hirschhorn,Alon Keinan,Li Hao,Gil Atzmon,Edward Burns,Harry Ostrer,Alkes L. Price,David Reich
PLOS Genetics , 2011, DOI: 10.1371/journal.pgen.1001373
Abstract: Previous genetic studies have suggested a history of sub-Saharan African gene flow into some West Eurasian populations after the initial dispersal out of Africa that occurred at least 45,000 years ago. However, there has been no accurate characterization of the proportion of mixture, or of its date. We analyze genome-wide polymorphism data from about 40 West Eurasian groups to show that almost all Southern Europeans have inherited 1%–3% African ancestry with an average mixture date of around 55 generations ago, consistent with North African gene flow at the end of the Roman Empire and subsequent Arab migrations. Levantine groups harbor 4%–15% African ancestry with an average mixture date of about 32 generations ago, consistent with close political, economic, and cultural links with Egypt in the late middle ages. We also detect 3%–5% sub-Saharan African ancestry in all eight of the diverse Jewish populations that we analyzed. For the Jewish admixture, we obtain an average estimated date of about 72 generations. This may reflect descent of these groups from a common ancestral population that already had some African ancestry prior to the Jewish Diasporas.
The Impact of Divergence Time on the Nature of Population Structure: An Example from Iceland
Alkes L. Price ,Agnar Helgason ,Snaebjorn Palsson,Hreinn Stefansson,David St. Clair,Ole A. Andreassen,David Reich,Augustine Kong,Kari Stefansson
PLOS Genetics , 2009, DOI: 10.1371/journal.pgen.1000505
Abstract: The Icelandic population has been sampled in many disease association studies, providing a strong motivation to understand the structure of this population and its ramifications for disease gene mapping. Previous work using 40 microsatellites showed that the Icelandic population is relatively homogeneous, but exhibits subtle population structure that can bias disease association statistics. Here, we show that regional geographic ancestries of individuals from Iceland can be distinguished using 292,289 autosomal single-nucleotide polymorphisms (SNPs). We further show that subpopulation differences are due to genetic drift since the settlement of Iceland 1100 years ago, and not to varying contributions from different ancestral populations. A consequence of the recent origin of Icelandic population structure is that allele frequency differences follow a null distribution devoid of outliers, so that the risk of false positive associations due to stratification is minimal. Our results highlight an important distinction between population differences attributable to recent drift and those arising from more ancient divergence, which has implications both for association studies and for efforts to detect natural selection using population differentiation.
Sensitive Detection of Chromosomal Segments of Distinct Ancestry in Admixed Populations
Alkes L. Price,Arti Tandon,Nick Patterson,Kathleen C. Barnes,Nicholas Rafaels,Ingo Ruczinski,Terri H. Beaty,Rasika Mathias,David Reich ,Simon Myers
PLOS Genetics , 2009, DOI: 10.1371/journal.pgen.1000519
Abstract: Identifying the ancestry of chromosomal segments of distinct ancestry has a wide range of applications from disease mapping to learning about history. Most methods require the use of unlinked markers; but, using all markers from genome-wide scanning arrays, it should in principle be possible to infer the ancestry of even very small segments with exquisite accuracy. We describe a method, HAPMIX, which employs an explicit population genetic model to perform such local ancestry inference based on fine-scale variation data. We show that HAPMIX outperforms other methods, and we explore its utility for inferring ancestry, learning about ancestral populations, and inferring dates of admixture. We validate the method empirically by applying it to populations that have experienced recent and ancient admixture: 935 African Americans from the United States and 29 Mozabites from North Africa. HAPMIX will be of particular utility for mapping disease genes in recently admixed populations, as its accurate estimates of local ancestry permit admixture and case-control association signals to be combined, enabling more powerful tests of association than with either signal alone.
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