Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data

Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even data sets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper we re-examine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (6 CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1357 individuals in 124 pedigrees) takes less than 2 minutes and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 minutes and 1.5 GB of memory

A narrow-band speckle-free light source via random Raman lasing

Currently, no light source exists which is both narrow-band and speckle-free with sufficient brightness for full-field imaging applications. Light emitting diodes (LEDs) are excellent spatially incoherent sources, but are tens of nanometers broad. Lasers on the other hand can produce very narrow-band light, but suffer from high spatial coherence which leads to speckle patterns which distort the image. Here we propose the use of random Raman laser emission as a new kind of light source capable of providing short-pulsed narrow-band speckle-free illumination for imaging applications

Non-Thermal X-ray Emission from the Northwestern Rim of the Galactic Supernova Remnant G266.2-1.2 (RX J0852.0-4622)

We present a detailed spatially-resolved spectroscopic analysis of two X-ray observations (with a total integration time of 73280 seconds) made of the luminous northwestern rim complex of the Galactic supernova remnant (SNR) G266.2-1.2 (RX J0852.0-4622) with the Chandra X-ray Observatory. G266.2-1.2 is a member of a class of Galactic SNRs which feature X-ray spectra dominated by non-thermal emission: in the cases of these SNRs, the emission is believed to have a synchrotron origin and studies of the X-ray spectra of these SNRs can lend insights into how SNRs accelerate cosmic-ray particles. The Chandra observations have clearly revealed fine structure in this rim complex and the spectra of these features are dominated by non-thermal emission. We have measured the length scales of the upstream structures at eight positions along the rim and derive lengths of 0.02-0.08 pc (assuming a distance of 750 pc to G266.2-1.2). We have also extracted spectra from seven regions in the rim complex and fit these spectra with such models as a simple power law as well as the synchrotron models SRCUT and SRESC. We have constrained our fits to the latter two models using estimates for the flux densities of these filaments at 1 GHz as determined from radio observations made with the Australia Telescope Compact Array (ATCA). Statistically-acceptable fits to all seven regions are derived using each model: differences in the fit parameters (such as photon index and cutoff frequency) are seen in the different regions, which may indicate variations in shock conditions and the maximum energies of the cosmic-ray electrons accelerated at each region. Finally, we estimate the maximum energy of cosmic-ray electrons accelerated along this rim complex to be approximately 40 TeV. We include a summary of estimated maximum energies for both Galactic SNRs as well as SNRs located in the Large Magellanic Cloud.Comment: 56 Pages, 11 Figures, Accepted for publication in the Astrophysical Journa

Data for Genetic Analysis Workshop (GAW) 15 Problem 2, Genetic Causes of Rheumatoid Arthritis and Associated Traits

For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North American Rheumatoid Arthritis Consortium (NARAC), collaboration among Canadian researchers, the European Consortium on Rheumatoid Arthritis Families (ECRAF), and investigators from Manchester, England. All groups used a common standard for defining rheumatoid arthritis, but NARAC also further selected for a more severe phenotype in the probands. Genotyping and family structures for microsatellite-based linkage analysis were provided from all centers. In addition, all centers but ECRAF have genotyped families for linkage analysis using SNPs and these data were additionally provided. NARAC also had additional data from a dense genotyping analysis of a region of chromosome 18 and results from candidate gene studies, which were provided. Finally, smoking influences risk for rheumatoid arthritis, and data were provided from the NARAC study on this behavior as well as some additional phenotypes measuring severity. Several questions could be evaluated using the data that were provided. These include comparing linkage analysis using single-nucleotide polymorphisms versus microsatellites and identifying credible regions of linkage outside the HLA region on chromosome 6p13, which has been extensively documented; evaluating the joint effects of smoking with genetic factors; and identifying more homogenous subsets of families for whom genetic susceptibility might be stronger, so that linkage and association studies may be more efficiently conducted

Clubbing masculinities: Gender shifts in gay men's dance floor choreographies

This is an Author's Accepted Manuscript of an article published in Journal of Homosexuality, 58(5), 608-625, 2011 [copyright Taylor & Francis], available online at: http://www.tandfonline.com/10.1080/00918369.2011.563660This article adopts an interdisciplinary approach to understanding the intersections of gender, sexuality, and dance. It examines the expressions of sexuality among gay males through culturally popular forms of club dancing. Drawing on political and musical history, I outline an account of how gay men's gendered choreographies changed throughout the 1970s, 80s, and 90s. Through a notion of “technologies of the body,” I situate these developments in relation to cultural levels of homophobia, exploring how masculine expressions are entangled with and regulated by musical structures. My driving hypothesis is that as perceptions of cultural homophobia decrease, popular choreographies of gay men's dance have become more feminine in expression. Exploring this idea in the context of the first decade of the new millennium, I present a case study of TigerHeat, one of the largest weekly gay dance club events in the United States

How managers can build trust in strategic alliances: a meta-analysis on the central trust-building mechanisms

Trust is an important driver of superior alliance performance. Alliance managers are influential in this regard because trust requires active involvement, commitment and the dedicated support of the key actors involved in the strategic alliance. Despite the importance of trust for explaining alliance performance, little effort has been made to systematically investigate the mechanisms that managers can use to purposefully create trust in strategic alliances. We use Parkhe’s (1998b) theoretical framework to derive nine hypotheses that distinguish between process-based, characteristic-based and institutional-based trust-building mechanisms. Our meta-analysis of 64 empirical studies shows that trust is strongly related to alliance performance. Process-based mechanisms are more important for building trust than characteristic- and institutional-based mechanisms. The effects of prior ties and asset specificity are not as strong as expected and the impact of safeguards on trust is not well understood. Overall, theoretical trust research has outpaced empirical research by far and promising opportunities for future empirical research exist

Smoothing of the bivariate LOD score for non-normal quantitative traits

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error