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Search Results: 1 - 10 of 219563 matches for " Pardis C. Sabeti "
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The case for selection at CCR5-Delta32.
Sabeti Pardis C,Walsh Emily,Schaffner Steve F,Varilly Patrick
PLOS Biology , 2005,
Abstract: The C-C chemokine receptor 5, 32 base-pair deletion (CCR5-Delta32) allele confers strong resistance to infection by the AIDS virus HIV. Previous studies have suggested that CCR5-Delta32 arose within the past 1,000 y and rose to its present high frequency (5%-14%) in Europe as a result of strong positive selection, perhaps by such selective agents as the bubonic plague or smallpox during the Middle Ages. This hypothesis was based on several lines of evidence, including the absence of the allele outside of Europe and long-range linkage disequilibrium at the locus. We reevaluated this evidence with the benefit of much denser genetic maps and extensive control data. We find that the pattern of genetic variation at CCR5-Delta32 does not stand out as exceptional relative to other loci across the genome. Moreover using newer genetic maps, we estimated that the CCR5-Delta32 allele is likely to have arisen more than 5,000 y ago. While such results can not rule out the possibility that some selection may have occurred at C-C chemokine receptor 5 (CCR5), they imply that the pattern of genetic variation seen atCCR5-Delta32 is consistent with neutral evolution. More broadly, the results have general implications for the design of future studies to detect the signs of positive selection in the human genome.
Positive Selection of a Pre-Expansion CAG Repeat of the Human SCA2 Gene.
Yu Fuli,Sabeti Pardis C,Hardenbol Paul,Fu Qing
PLOS Genetics , 2005,
Abstract: A region of approximately one megabase of human Chromosome 12 shows extensive linkage disequilibrium in Utah residents with ancestry from northern and western Europe. This strikingly large linkage disequilibrium block was analyzed with statistical and experimental methods to determine whether natural selection could be implicated in shaping the current genome structure. Extended Haplotype Homozygosity and Relative Extended Haplotype Homozygosity analyses on this region mapped a core region of the strongest conserved haplotype to the exon 1 of the Spinocerebellar ataxia type 2 gene (SCA2). Direct DNA sequencing of this region of the SCA2 gene revealed a significant association between a pre-expanded allele [(CAG)(8)CAA(CAG)(4)CAA(CAG)(8)] of CAG repeats within exon 1 and the selected haplotype of the SCA2 gene. A significantly negative Tajima's D value (-2.20, p < 0.01) on this site consistently suggested selection on the CAG repeat. This region was also investigated in the three other populations, none of which showed signs of selection. These results suggest that a recent positive selection of the pre-expansion SCA2 CAG repeat has occurred in Utah residents with European ancestry.
Measuring dependence powerfully and equitably
Yakir A. Reshef,David N. Reshef,Hilary K. Finucane,Pardis C. Sabeti,Michael M. Mitzenmacher
Computer Science , 2015,
Abstract: For high-dimensional datasets, it is common to evaluate a measure of dependence on every variable pair and retain the highest-scoring pairs for follow-up. If the statistic used systematically assigns higher scores to some relationship types over others, important relationships may be overlooked. This difficulty is avoided if the statistic is equitable [Reshef et al. 2015a], i.e., if, for some measure of noise, it assigns similar scores to equally noisy relationships regardless of relationship type. In this paper, we introduce and characterize a population measure of dependence called MIC*. We show three ways that MIC* can be viewed: as the population value of MIC, a highly equitable statistic from [Reshef et al. 2011], as a canonical "smoothing" of mutual information, and as the supremum of an infinite sequence defined in terms of optimal one-dimensional partitions of the marginals of the joint distribution. Based on this theory, we introduce an efficient algorithm for computing MIC* from the density of a pair of random variables, and we define a new consistent estimator MICe for MIC* that is efficiently computable. (In contrast, there is no known polynomial-time algorithm for computing MIC.) We show through simulations that MICe has better bias-variance properties than MIC, and that it has high equitability with respect to R^2 on a set of functional relationships. While MICe is designed for equitability rather than independence testing, we introduce a related statistic, TICe, that is a trivial side-product of the computation of MICe. We prove the consistency of independence testing based on TICe and show in simulations that this approach achieves excellent power. This paper is accompanied by a companion paper [Reshef et al. 2015b] focused on in-depth empirical evaluation of several leading measures of dependence that finds that the performance of MICe and TICe is state-of-the-art.
Equitability, interval estimation, and statistical power
Yakir A. Reshef,David N. Reshef,Pardis C. Sabeti,Michael M. Mitzenmacher
Computer Science , 2015,
Abstract: For analysis of a high-dimensional dataset, a common approach is to test a null hypothesis of statistical independence on all variable pairs using a non-parametric measure of dependence. However, because this approach attempts to identify any non-trivial relationship no matter how weak, it often identifies too many relationships to be useful. What is needed is a way of identifying a smaller set of relationships that merit detailed further analysis. Here we formally present and characterize equitability, a property of measures of dependence that aims to overcome this challenge. Notionally, an equitable statistic is a statistic that, given some measure of noise, assigns similar scores to equally noisy relationships of different types [Reshef et al. 2011]. We begin by formalizing this idea via a new object called the interpretable interval, which functions as an interval estimate of the amount of noise in a relationship of unknown type. We define an equitable statistic as one with small interpretable intervals. We then draw on the equivalence of interval estimation and hypothesis testing to show that under moderate assumptions an equitable statistic is one that yields well powered tests for distinguishing not only between trivial and non-trivial relationships of all kinds but also between non-trivial relationships of different strengths. This means that equitability allows us to specify a threshold relationship strength $x_0$ and to search for relationships of all kinds with strength greater than $x_0$. Thus, equitability can be thought of as a strengthening of power against independence that enables fruitful analysis of data sets with a small number of strong, interesting relationships and a large number of weaker ones. We conclude with a demonstration of how our two equivalent characterizations of equitability can be used to evaluate the equitability of a statistic in practice.
An Empirical Study of Leading Measures of Dependence
David N. Reshef,Yakir A. Reshef,Pardis C. Sabeti,Michael M. Mitzenmacher
Computer Science , 2015,
Abstract: In exploratory data analysis, we are often interested in identifying promising pairwise associations for further analysis while filtering out weaker, less interesting ones. This can be accomplished by computing a measure of dependence on all variable pairs and examining the highest-scoring pairs, provided the measure of dependence used assigns similar scores to equally noisy relationships of different types. This property, called equitability, is formalized in Reshef et al. [2015b]. In addition to equitability, measures of dependence can also be assessed by the power of their corresponding independence tests as well as their runtime. Here we present extensive empirical evaluation of the equitability, power against independence, and runtime of several leading measures of dependence. These include two statistics introduced in Reshef et al. [2015a]: MICe, which has equitability as its primary goal, and TICe, which has power against independence as its goal. Regarding equitability, our analysis finds that MICe is the most equitable method on functional relationships in most of the settings we considered, although mutual information estimation proves the most equitable at large sample sizes in some specific settings. Regarding power against independence, we find that TICe, along with Heller and Gorfine's S^DDP, is the state of the art on the relationships we tested. Our analyses also show a trade-off between power against independence and equitability consistent with the theory in Reshef et al. [2015b]. In terms of runtime, MICe and TICe are significantly faster than many other measures of dependence tested, and computing either one makes computing the other trivial. This suggests that a fast and useful strategy for achieving a combination of power against independence and equitability may be to filter relationships by TICe and then to examine the MICe of only the significant ones.
Theoretical Foundations of Equitability and the Maximal Information Coefficient
Yakir A. Reshef,David N. Reshef,Pardis C. Sabeti,Michael Mitzenmacher
Quantitative Biology , 2014,
Abstract: The maximal information coefficient (MIC) is a tool for finding the strongest pairwise relationships in a data set with many variables (Reshef et al., 2011). MIC is useful because it gives similar scores to equally noisy relationships of different types. This property, called {\em equitability}, is important for analyzing high-dimensional data sets. Here we formalize the theory behind both equitability and MIC in the language of estimation theory. This formalization has a number of advantages. First, it allows us to show that equitability is a generalization of power against statistical independence. Second, it allows us to compute and discuss the population value of MIC, which we call MIC_*. In doing so we generalize and strengthen the mathematical results proven in Reshef et al. (2011) and clarify the relationship between MIC and mutual information. Introducing MIC_* also enables us to reason about the properties of MIC more abstractly: for instance, we show that MIC_* is continuous and that there is a sense in which it is a canonical "smoothing" of mutual information. We also prove an alternate, equivalent characterization of MIC_* that we use to state new estimators of it as well as an algorithm for explicitly computing it when the joint probability density function of a pair of random variables is known. Our hope is that this paper provides a richer theoretical foundation for MIC and equitability going forward. This paper will be accompanied by a forthcoming companion paper that performs extensive empirical analysis and comparison to other methods and discusses the practical aspects of both equitability and the use of MIC and its related statistics.
Identification of Two Independent Risk Factors for Lupus within the MHC in United Kingdom Families
Michelle M. A Fernando,Christine R Stevens,Pardis C Sabeti,Emily C Walsh,Alasdair J. M McWhinnie,Anila Shah,Todd Green,John D Rioux ,Timothy J Vyse
PLOS Genetics , 2007, DOI: 10.1371/journal.pgen.0030192
Abstract: The association of the major histocompatibility complex (MHC) with SLE is well established yet the causal variants arising from this region remain to be identified, largely due to inadequate study design and the strong linkage disequilibrium demonstrated by genes across this locus. The majority of studies thus far have identified strong association with classical class II alleles, in particular HLA-DRB1*0301 and HLA-DRB1*1501. Additional associations have been reported with class III alleles; specifically, complement C4 null alleles and a tumor necrosis factor promoter SNP (TNF-308G/A). However, the relative effects of these class II and class III variants have not been determined. We have thus used a family-based approach to map association signals across the MHC class II and class III regions in a cohort of 314 complete United Kingdom Caucasian SLE trios by typing tagging SNPs together with classical typing of the HLA-DRB1 locus. Using TDT and conditional regression analyses, we have demonstrated the presence of two distinct and independent association signals in SLE: HLA-DRB1*0301 (nominal p = 4.9 × 10?8, permuted p < 0.0001, OR = 2.3) and the T allele of SNP rs419788 (nominal p = 4.3 × 10?8, permuted p < 0.0001, OR = 2.0) in intron 6 of the class III region gene SKIV2L. Assessment of genotypic risk demonstrates a likely dominant model of inheritance for HLA-DRB1*0301, while rs419788-T confers susceptibility in an additive manner. Furthermore, by comparing transmitted and untransmitted parental chromosomes, we have delimited our class II signal to a 180 kb region encompassing the alleles HLA-DRB1*0301-HLA-DQA1*0501-HLA-DQB1*020?1 alone. Our class III signal importantly excludes independent association at the TNF promoter polymorphism, TNF-308G/A, in our SLE cohort and provides a potentially novel locus for future genetic and functional studies.
Ancient and Recent Adaptive Evolution of Primate Non-Homologous End Joining Genes
Ann Demogines,Alysia M. East,Ji-Hoon Lee,Sharon R. Grossman,Pardis C. Sabeti,Tanya T. Paull,Sara L. Sawyer
PLOS Genetics , 2010, DOI: 10.1371/journal.pgen.1001169
Abstract: In human cells, DNA double-strand breaks are repaired primarily by the non-homologous end joining (NHEJ) pathway. Given their critical nature, we expected NHEJ proteins to be evolutionarily conserved, with relatively little sequence change over time. Here, we report that while critical domains of these proteins are conserved as expected, the sequence of NHEJ proteins has also been shaped by recurrent positive selection, leading to rapid sequence evolution in other protein domains. In order to characterize the molecular evolution of the human NHEJ pathway, we generated large simian primate sequence datasets for NHEJ genes. Codon-based models of gene evolution yielded statistical support for the recurrent positive selection of five NHEJ genes during primate evolution: XRCC4, NBS1, Artemis, POLλ, and CtIP. Analysis of human polymorphism data using the composite of multiple signals (CMS) test revealed that XRCC4 has also been subjected to positive selection in modern humans. Crystal structures are available for XRCC4, Nbs1, and Polλ; and residues under positive selection fall exclusively on the surfaces of these proteins. Despite the positive selection of such residues, biochemical experiments with variants of one positively selected site in Nbs1 confirm that functions necessary for DNA repair and checkpoint signaling have been conserved. However, many viruses interact with the proteins of the NHEJ pathway as part of their infectious lifecycle. We propose that an ongoing evolutionary arms race between viruses and NHEJ genes may be driving the surprisingly rapid evolution of these critical genes.
A global transcriptional analysis of Plasmodium falciparum malaria reveals a novel family of telomere-associated lncRNAs
Kate M Broadbent, Daniel Park, Ashley R Wolf, Daria Van Tyne, Jennifer S Sims, Ulf Ribacke, Sarah Volkman, Manoj Duraisingh, Dyann Wirth, Pardis C Sabeti, John L Rinn
Genome Biology , 2011, DOI: 10.1186/gb-2011-12-6-r56
Abstract: We used a high-resolution DNA tiling microarray to survey transcriptional activity across 22.6% of the P. falciparum strain 3D7 genome. We identified 872 protein-coding genes and 60 putative P. falciparum lncRNAs under developmental regulation during the parasite's pathogenic human blood stage. Further characterization of lncRNA candidates led to the discovery of an intriguing family of lncRNA telomere-associated repetitive element transcripts, termed lncRNA-TARE. We have quantified lncRNA-TARE expression at 15 distinct chromosome ends and mapped putative transcriptional start and termination sites of lncRNA-TARE loci. Remarkably, we observed coordinated and stage-specific expression of lncRNA-TARE on all chromosome ends tested, and two dominant transcripts of approximately 1.5 kb and 3.1 kb transcribed towards the telomere.We have characterized a family of 22 telomere-associated lncRNAs in P. falciparum. Homologous lncRNA-TARE loci are coordinately expressed after parasite DNA replication, and are poised to play an important role in P. falciparum telomere maintenance, virulence gene regulation, and potentially other processes of parasite chromosome end biology. Further study of lncRNA-TARE and other promising lncRNA candidates may provide mechanistic insight into P. falciparum transcriptional regulation.The causative agent of the most severe form of human malaria, Plasmodium falciparum, is a unicellular eukaryotic parasite transmitted through the bites of infected mosquitoes. The most vulnerable population to malarial disease is African children, but a staggering 3.3 billion people - half the world's population - are at risk for malarial infection. Despite recent research advances [1-6], the mechanisms P. falciparum utilizes to regulate mutually exclusive expression of multi-gene virulence families and stage-specific expression of approximately 80% of its genome during pathogenic blood stage development remain elusive.Most confounding is the scarcity of sequence-sp
A general SNP-based molecular barcode for Plasmodium falciparum identification and tracking
Rachel Daniels, Sarah K Volkman, Danny A Milner, Nira Mahesh, Daniel E Neafsey, Daniel J Park, David Rosen, Elaine Angelino, Pardis C Sabeti, Dyann F Wirth, Roger C Wiegand
Malaria Journal , 2008, DOI: 10.1186/1475-2875-7-223
Abstract: A panel of twenty-four SNP markers has been identified that exhibit a high minor allele frequency (average MAF > 35%), for which robust TaqMan genotyping assays were constructed. All SNPs were identified through whole genome sequencing and MAF was estimated through Affymetrix array-based genotyping of a worldwide collection of parasites. These assays create a "molecular barcode" to uniquely identify a parasite genome.Using 24 such markers no two parasites known to be of independent origin have yet been found to have the same allele signature. The TaqMan genotyping assays can be performed on a variety of samples including cultured parasites, frozen whole blood, or whole blood spotted onto filter paper with a success rate > 99%. Less than 5 ng of parasite DNA is needed to complete a panel of 24 markers. The ability of this SNP panel to detect and identify parasites was compared to the standard molecular methods, MSP-1 and MSP-2 typing.This work provides a facile field-deployable genotyping tool that can be used without special skills with standard lab equipment, and at reasonable cost that will unambiguously identify and track P. falciparum parasites both from patient samples and in the laboratory.Nearly all malaria-associated mortality in children is due to infection with Plasmodium falciparum, which causes over 300 million clinical infections and a million deaths per year in African children under five years of age [1]. Genome sequencing of multiple parasite isolates [2-5] indicates that the parasite population is highly diverse. Genetic diversity in P. falciparum is manifested in the form of single nucleotide polymorphim (SNPs), microsatellite repeats, insertions, deletions and a range of gene duplication events. Much of this diversity segregates independently. Analysis of the progeny from a genetic cross suggests that the parasite genome is approximately 50-fold more 'recombinogenic' than the human genome [2]. This genetic diversity underlies the ability of the pa
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