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 Journal of Genomes and Exomes , 2012, DOI: 10.4137/JGE.S11378 Abstract: Mutations in the NNT gene (nicotinamide nucleotide transhydrogenase), which is involved in NADPH generation in mitochondria, have recently been described in familial glucocorticoid deficiency. We report two patients, one with isolated glucocorticoid deficiency and the other with a combined glucocorticoid and mineralocorticoid deficiency. Through whole exome sequencing, both cases were found to carry two different NNT mutations, confirming previous results for these patients. Each patient also carries multiple heterozygous protein-altering mutations in other genes involved in steroid hormone biogenesis and regulation. The patient with a combined glucocorticoid and mineralocorticoid deficiency is a compound heterozygote for common missense variants in the ME3 gene (mitochondrial malic enzyme 3), the product of which also generates NADPH in mitochondria. Mutations in NNT are the likely proximal cause of the glucocorticoid deficiency in both patients, but genetic background effects may be important in modulating the specific phenotype of adrenal insufficiency.
 Hannah Stower Genome Biology , 2011, DOI: 10.1186/gb-2011-12-9-407 Abstract: The decision to launch a special issue of Genome Biology coincided with my first American Society of Human Genetics meeting in Washington, DC [1]; exciting work using exome capture sequencing had been presented on melanoma, somatic mutations in induced pluripotent stem cells and numerous single gene disorders. The technique strongly enriches a sequencing sample for exons by using DNA capture probes targeted only to the portion of the genome constituting the exome. In addition, at this time I met and discussed exome sequencing with one of the leaders in the field, Jay Shendure, and we are delighted that he agreed to be the Guest Editor for this issue. There was no doubt for me that exome sequencing was flourishing, and so it is in this September issue that we present articles with that special 'exome factor'.Choosing to publish a special issue on a field that is, relatively speaking, in its infancy necessitates many discussions about how best to make use of the technology and analyze the data, and these discussions have led us to present some guidelines and new approaches to exome capture sequencing. In a 'bake-off' between different exome capture techniques, Janna Saarela and colleagues [2] perform a systematic comparison of the two solution-based capture kits commercially available from Agilent and Roche-Nimblegen. The results show that researchers should be confident with the data garnered by either approach, and we hope that the clarity of this study will make it a useful reference, particularly to those just starting out. To provide further coverage and discussion of best methodological practice, we commissioned Shamil Sunyaev and colleagues [3] to review the computational and statistical approaches necessary for prioritization of variants from exome sequencing data. With typically 15,000 to 20,000 variants discovered per exome, whittling these variants down to those that are likely to be causing disease is a significant challenge. An abundance of tools has been
 Genome Biology , 2011, DOI: 10.1186/gb-2011-12-9-128 Abstract: Exomes are ideal to help us understand high-penetrance allelic variation and its relationship to phenotype. Because exomes focus on exons, which include coding regions of genes, and because most high-penetrance (Mendelian or nearly so) variation is mediated by non-synonymous, frameshifting and canonical splice variation, exomes are ideal for studying the relationship of such variation to health and disease.Sequencing using any approach is still in its early days, but it is clear that exome sequencing will often lead to the identification of the causative variant for Mendelian diseases. This should not be surprising given that we know that most mutations causing Mendelian disease are exonic. That said, there are clear limitations even for Mendelian disease. Structural variations (SVs), which are also important for Mendelian disease, are not easily detected using an exome approach. How well exome sequencing may do for complex traits is an entirely open question since we do not know what kinds of mutations are important there, but it is possible they are more often regulatory than for Mendelian disease.Cost is a huge factor - every day we ask ourselves the question, 'Would we rather have six samples analyzed by whole exome sequencing (WES) or one by whole genome sequencing (WGS)?' Our current, fully loaded price for a WGS is six times that of a WES assay - a ratio that has changed surprisingly little in the past 2 years. Which study one should use depends on the biomedical question that is being asked. If it is primarily a genotype-phenotype question, and the putative variant is high penetrance, then it is crucial to increase our statistical power by increasing our N, so exomes provide a big advantage here. If the question is different, it could be that a smaller number of WGS interrogations would be more effective. WES and WGS are tools - one has to select the optimal tool considering the biomedical question and the available resources.The lower cost of exome sequenci
 Computer Science , 1997, Abstract: The paper considers participles such as "unknown", "identified" and "unspecified", which in sentences such as "Solange is staying in an unknown hotel" have readings equivalent to an indirect question "Solange is staying in a hotel, and it is not known which hotel it is." We discuss phenomena including disambiguation of quantifier scope and a restriction on the set of determiners which allow the reading in question. Epistemic modifiers are analyzed in a DRT framework with file (information state) discourse referents. The proposed semantics uses a predication on files and discourse referents which is related to recent developments in dynamic modal predicate calculus. It is argued that a compositional DRT semantics must employ a semantic type of discourse referents, as opposed to just a type of individuals. A connection is developed between the scope effects of epistemic modifiers and the scope-disambiguating effect of "a certain".
 PLOS ONE , 2012, DOI: 10.1371/journal.pone.0038050 Abstract: Context Genetic testing for monogenic diabetes is important for patient care. Given the extensive genetic and clinical heterogeneity of diabetes, exome sequencing might provide additional diagnostic potential when standard Sanger sequencing-based diagnostics is inconclusive. Objective The aim of the study was to examine the performance of exome sequencing for a molecular diagnosis of MODY in patients who have undergone conventional diagnostic sequencing of candidate genes with negative results. Research Design and Methods We performed exome enrichment followed by high-throughput sequencing in nine patients with suspected MODY. They were Sanger sequencing-negative for mutations in the HNF1A, HNF4A, GCK, HNF1B and INS genes. We excluded common, non-coding and synonymous gene variants, and performed in-depth analysis on filtered sequence variants in a pre-defined set of 111 genes implicated in glucose metabolism. Results On average, we obtained 45 X median coverage of the entire targeted exome and found 199 rare coding variants per individual. We identified 0–4 rare non-synonymous and nonsense variants per individual in our a priori list of 111 candidate genes. Three of the variants were considered pathogenic (in ABCC8, HNF4A and PPARG, respectively), thus exome sequencing led to a genetic diagnosis in at least three of the nine patients. Approximately 91% of known heterozygous SNPs in the target exomes were detected, but we also found low coverage in some key diabetes genes using our current exome sequencing approach. Novel variants in the genes ARAP1, GLIS3, MADD, NOTCH2 and WFS1 need further investigation to reveal their possible role in diabetes. Conclusion Our results demonstrate that exome sequencing can improve molecular diagnostics of MODY when used as a complement to Sanger sequencing. However, improvements will be needed, especially concerning coverage, before the full potential of exome sequencing can be realized.
 Genome Biology , 2011, DOI: 10.1186/gb-2011-12-9-r97 Abstract: Each exome kit performed well at capturing the targets they were designed to capture, which mainly corresponds to the consensus coding sequences (CCDS) annotations of the human genome. In addition, based on their respective targets, each capture kit coupled with high coverage Illumina sequencing produced highly accurate nucleotide calls. However, other databases, such as the Reference Sequence collection (RefSeq), define the exome more broadly, and so not surprisingly, the exome kits did not capture these additional regions.Commercial exome capture kits provide a very efficient way to sequence select areas of the genome at very high accuracy. Here we provide the data to help guide critical analyses of sequencing data derived from these products.Targeted sequencing of large portions of the genome with next generation technology [1-4] has become a powerful approach for identifying human variation associated with disease [5-7]. The ultimate goal of targeted resequencing is to accurately and cost effectively identify these variants, which requires obtaining adequate and uniform sequencing depth across the target. The release of commercial capture reagents from both NimbleGen and Agilent that target human exons for resequencing (exome sequencing) has greatly accelerated the utilization of this strategy. The solution-based exome capture kits manufactured by both companies are of particular importance because they are more easily adaptable to a high-throughput workflow and, further, do not require an investment in array-processing equipment or careful training of personnel on array handling. As a result of the availability of these reagents and the success of the approach, a large number of such projects have been undertaken, some of them quite large in scope.As with many competitive commercial products, there have been updates and improvements to the original versions of the NimbleGen and Agilent solution exome capture kits that include a shift to the latest human genome
 Statistics , 2012, DOI: 10.1214/11-STS376 Abstract: The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection. This article reviews recent progress in the statistical modeling of spatial extremes, starting with sketches of the necessary elements of extreme value statistics and geostatistics. The main types of statistical models thus far proposed, based on latent variables, on copulas and on spatial max-stable processes, are described and then are compared by application to a data set on rainfall in Switzerland. Whereas latent variable modeling allows a better fit to marginal distributions, it fits the joint distributions of extremes poorly, so appropriately-chosen copula or max-stable models seem essential for successful spatial modeling of extremes.
 Mathematics , 2012, Abstract: This paper determines the range of feasible values of standard error exponents for binary-input memoryless symmetric channels of fixed capacity $C$ and shows that extremes are attained by the binary symmetric and the binary erasure channel. The proof technique also provides analogous extremes for other quantities related to Gallager's $E_0$ function, such as the cutoff rate, the Bhattacharyya parameter, and the channel dispersion.
 Statistics , 2014, Abstract: The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.
 Statistics , 2015, Abstract: The statistical modelling of spatial extremes has recently made major advances. Much of its focus so far has been on the modelling of the magnitudes of extreme events but little attention has been paid on the timing of extremes. To address this gap, this paper introduces the notion of extremal concurrence. Suppose that one measures precipitation at several synoptic stations over multiple days. We say that extremes are concurrent if the maximum precipitation over time at each station is achieved simultaneously, e.g., on a single day. Under general conditions, we show that the finite sample concurrence probability converges to an asymptotic quantity, deemed extremal concurrence probability. Using Palm calculus, we establish general expressions for the extremal concurrence probability through the max-stable process emerging in the limit of the componentwise maxima of the sample. Explicit forms of the extremal concurrence probabilities are obtained for various max-stable models and several estimators are introduced. In particular, we prove that the pairwise extremal concurrence probability for max-stable vectors is precisely equal to the Kendall's $\tau$. The estimators are evaluated by using simulations and applied to study the concurrence patterns of temperature extremes in the United States. The results demonstrate that concurrence probability can provide a powerful new perspective and tools for the analysis of the spatial structure and impact of extremes.
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