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

The paradox of being a woman teacher

In this article I follow genealogical lines of analysis in an attempt to map the different discourses and practices that interweave women’s position in education today. I have theorised education as a nexus of created paradoxical spaces, where the female self has attempted to surpass closed boundaries and to question the dichotomy of the feminised private and/or the masculine public. I have also considered the importance of time restrictions upon women’s lives and have paid attention to the multifarious ways these lives are highly structured by specific space/time regulations. The genealogical cartography I have drawn, depicts various positions, where the female self has created parodic unities and temporary coalitions. Finally in tracing exit points that education has offered women, I have considered some of the implications of feminist theories for the subversion of the various dilemmas and dichotomies the female subject has lived through

Association of U.S. tornado occurrence with monthly environmental parameters

Monthly U.S. tornado numbers are here related to observation-based monthly averaged atmospheric parameters. Poisson regression is used to form an index which captures the climatological spatial distribution and seasonal variation of tornado occurrence, as well as year-to-year variability, and provides a framework for extended range forecasts of tornado activity. Computing the same index with predicted atmospheric parameters from a comprehensive forecast model gives some evidence of the predictability of monthly tornado activity

A Poisson Regression Index for Tropical Cyclone Genesis and the Role of Large-Scale Vorticity in Genesis

A Poisson regression between the observed climatology of tropical cyclogenesis (TCG) and large-scale climate variables is used to construct a TCG index. The regression methodology is objective and provides a framework for the selection of the climate variables in the index. Broadly following earlier work, four climate variables appear in the index: low-level absolute vorticity, relative humidity, relative sea surface temperature (SST), and vertical shear. Several variants in the choice of predictors are explored, including relative SST versus potential intensity and satellite-based column-integrated relative humidity versus reanalysis relative humidity at a single level; these choices lead to modest differences in the performance of the index. The feature of the new index that leads to the greatest improvement is a functional dependence on low-level absolute vorticity that causes the index response to absolute vorticity to saturate when absolute vorticity exceeds a threshold. This feature reduces some biases of the index and improves the fidelity of its spatial distribution. Physically, this result suggests that once low-level environmental vorticity reaches a sufficiently large value, other factors become rate limiting so that further increases in vorticity (at least on a monthly mean basis) do not increase the probability of genesis. Although the index is fit to climatological data, it reproduces some aspects of interannual variability when applied to interannually varying data. Overall, the new index compares positively to the genesis potential index (GPI), whose derivation, computation, and analysis is more complex in part because of its dependence on potential intensity

Seasonal Noise Versus Subseasonal Signal: Forecasts of California Precipitation During the Unusual Winters of 2015–2016 and 2016–2017

Subseasonal forecasts of California precipitation during the unusual winters of 2015–2016 and 2016–2017 are examined in this study. It is shown that two different ensemble forecast systems were able to predict monthly precipitation anomalies in California during these periods with some skill in forecasts initialized near or at the start of the month. The unexpected anomalies in February 2016, as well as in January and February 2017, were associated with shifts in the position of the jet stream over the northeast Pacific in a manner broadly consistent with associations found in larger ensembles of forecasts. These results support the broader notion that what is unpredictable atmospheric noise at the seasonal time scale can become predictable signal at the subseasonal time scale, despite that the lead times and verification averaging times associated with these forecasts are outside the predictability horizons of canonical midrange weather forecasting

Neutrino-induced deuteron disintegration experiment

Cross sections for the disintegration of the deuteron via neutral-current (NCD) and charged-current (CCD) interactions with reactor antineutrinos are measured to be 6.08 +/- 0.77 x 10^(-45) cm-sq and 9.83 +/- 2.04 x 10^(-45) cm-sq per neutrino, respectively, in excellent agreement with current calculations. Since the experimental NCD value depends upon the CCD value, if we use the theoretical value for the CCD reaction, we obtain the improved value of 5.98 +/- 0.54 x 10^(-45) for the NCD cross section. The neutral-current reaction allows a unique measurement of the isovector-axial vector coupling constant in the hadronic weak interaction (beta). In the standard model, this constant is predicted to be exactly 1, independent of the Weinberg angle. We measure a value of beta^2 = 1.01 +/- 0.16. Using the above improved value for the NCD cross section, beta^2 becomes 0.99 +/- 0.10.Comment: 22pages, 9 figure

An Empirical Relation between U.S. Tornado Activity and Monthly Environmental Parameters

In previous work the authors demonstrated an empirical relation, in the form of an index, between U.S. monthly tornado activity and monthly averaged environmental parameters. Here a detailed comparison is made between the index and reported tornado activity. The index is a function of two environmental parameters taken from the North American Regional Reanalysis: convective precipitation (cPrcp) and storm relative helicity (SRH). Additional environmental parameters are considered for inclusion in the index, among them convective available potential energy, but their inclusion does not significantly improve the overall climatological performance of the index. The aggregate climatological dependence of reported monthly U.S. tornado numbers on cPrcp and SRH is well described by the index, although it fails to capture nonsupercell and cool season tornadoes. The contributions of the two environmental parameters to the index annual cycle and spatial distribution are examined with the seasonality of cPrcp (maximum during summer) relative to SRH (maximum in winter) accounting for the index peak value in May. The spatial distribution of SRH establishes the central U.S. “tornado alley” of the index, while the spatial distribution of cPrcp enhances index values in the South and Southeast and suppresses them west of the Rockies and over elevation. At the scale of the NOAA climate regions, the largest deficiency of the index climatology occurs over the central region where the index peak in spring is too low and where the late summer drop-off in the reported number of tornadoes is poorly captured. This index deficiency is related to its sensitivity to SRH, and increasing the index sensitivity to SRH improves the representation of the annual cycle in this region. The ability of the index to represent the interannual variability of the monthly number of U.S. tornadoes can be ascribed during most times of the year to interannual variations of cPrcp rather than of SRH. However, both factors are important during the peak spring period. The index shows some skill in representing the interannual variability of monthly tornado numbers at the scale of NOAA climate regions

Rapid intensification and the bimodal distribution of tropical cyclone intensity

The severity of a tropical cyclone (TC) is often summarized by its lifetime maximum intensity (LMI), and the climatological LMI distribution is a fundamental feature of the climate system. The distinctive bimodality of the LMI distribution means that major storms (LMI >96 kt) are not very rare compared with less intense storms. Rapid intensification (RI) is the dramatic strengthening of a TC in a short time, and is notoriously difficult to forecast or simulate. Here we show that the bimodality of the LMI distribution reflects two types of storms: those that undergo RI during their lifetime (RI storms) and those that do not (non-RI storms). The vast majority (79%) of major storms are RI storms. Few non-RI storms (6%) become major storms. While the importance of RI has been recognized in weather forecasting, our results demonstrate that RI also plays a crucial role in the TC climatology