Abstract:
We developed the ProbABEL software package for the analysis of genome-wide imputed SNP data and quantitative, binary, and time-till-event outcomes under linear, logistic, and Cox proportional hazards models, respectively. For quantitative traits, the package also implements a fast two-step mixed model-based score test for association in samples with differential relationships, facilitating analysis in family-based studies, studies performed in human genetically isolated populations and outbred animal populations.ProbABEL package provides fast efficient way to analyze imputed data in genome-wide context and will facilitate future identification of complex trait loci.Genome-wide association (GWA) studies became the tool of choice for the identification of loci associated with complex traits. In GWA analyses, association between a trait of interest and genetic polymorphisms (usually single nucleotide polymorphisms, SNPs) is studied using thousands of people typed for hundreds of thousands of polymorphisms. Several hundred loci for dozens of complex human disease and quantitative traits have been discovered thus far using this method [1].For any given genetic polymorphism, association can be studied using standard statistical analysis methodology, such as fixed and mixed effects models. However, because of the large number of tests to be performed and the quantity of data to be stored in GWA studies, computational throughput and effective data handling are essential features of statistical analysis software to be used in this context. A number of specialized software packages, such as PLINK[2], GenABEL[3], SNPTEST[4] and snpMatrix[5] were developed for the statistical analysis of GWA data. Most of these packages were designed, and are fit for, the analysis of directly typed SNPs. When directly typed markers are studied, genotype calling is performed with a high degree of confidence for the vast majority of markers, resulting in four possible genotypes ("AA", "AB", "BB",

Abstract:
Through simulations, we investigated type I error for Bartlett's test, Bartlett's test with prior rank transformation of a trait to normality, and Levene's test for different genetic models. Additionally, we derived an analytical expression for power estimation. We showed that Bartlett's test has acceptable type I error in the case of trait following a normal distribution, whereas Levene's test kept nominal Type I error under all scenarios investigated. For the power of variance homogeneity test, we showed (as opposed to the power of direct test which uses information about known interacting factor) that, given the same interaction effect, the power can vary widely depending on the non-estimable direct effect of the unobserved interacting variable. Thus, for a given interaction effect, only very wide limits of power of the variance homogeneity test can be estimated. Also we applied Levene's approach to test genome-wide homogeneity of variances of the C-reactive protein in the Rotterdam Study population (n = 5959). In this analysis, we replicate previous results of Pare and colleagues (2010) for the SNP rs12753193 (n = 21, 799).Screening for differences in variances among genotypes of a SNP is a promising approach as a number of biologically interesting models may lead to the heterogeneity of variances. However, it should be kept in mind that the absence of variance heterogeneity for a SNP can not be interpreted as the absence of involvement of the SNP in the interaction network.Genome-wide association (GWA) study has become the tool of choice for the identification of loci associated with complex traits. In GWA analysis, the association between a trait of interest and genetic variation is studied by using thousands of subjects typed for hundreds of thousands of polymorphisms. Thus several hundred loci for dozens of complex human disease and quantitative traits have been discovered utilizing this method [1].However, it has become clear that for most complex traits, l

Abstract:
We and Pare with colleagues (2010) developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants.In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests.Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.Genome-wide association studies (GWAS) have been instrumental in identifying genetic variants involved in complex diseases. In GWAS, the relation between a trait of interest and genetic variation (usually a single nuclear polymorphism -- a SNP) is studied by assessing hundreds of thousands of polymorphisms in thousands of individuals. Several hundreds of loci for dozens of complex human diseases and quantitative traits have been discovered using GWAS [1].Though GWASs were successful in finding single loci associated with a trait, complex genetic models which include many interacting loci and environmental factors are of interest as they may help finding new loci and improve our understanding of the genetics of complex traits. A search for genetic interactions by direct analysis, in which all possible genetic models are examined, meets substantial computational and methodological difficulties. When millions of SNPs are considered, which nowadays has become routine in GWAS, testing for interaction for all possible pairwise combinations of SNPs becomes cumbersome requiring parallel computations using hundreds or thous

Abstract:
Multiple loss-of-function (LOF) alleles at the same gene may influence a phenotype not only in the homozygote state when alleles are considered individually, but also in the compound heterozygote (CH) state. Such LOF alleles typically have low frequencies and moderate to large effects. Detecting such variants is of interest to the genetics community, and relevant statistical methods for detecting and quantifying their effects are sorely needed. We present a collapsed double heterozygosity (CDH) test to detect the presence of multiple LOF alleles at a gene. When causal SNPs are available, which may be the case in next generation genome sequencing studies, this CDH test has overwhelmingly higher power than single SNP analysis. When causal SNPs are not directly available such as in current GWA settings, we show the CDH test has higher power than standard single SNP analysis if tagging SNPs are in linkage disequilibrium with the underlying causal SNPs to at least a moderate degree (r2>0.1). The test is implemented for genome-wide analysis in the publically available software package GenABEL which is based on a sliding window approach. We provide the proof of principle by conducting a genome-wide CDH analysis of red hair color, a trait known to be influenced by multiple loss-of-function alleles, in a total of 7,732 Dutch individuals with hair color ascertained. The association signals at the MC1R gene locus from CDH were uniformly more significant than traditional GWA analyses (the most significant P for CDH = 3.11×10？142 vs. P for rs258322 = 1.33×10？66). The CDH test will contribute towards finding rare LOF variants in GWAS and sequencing studies.

Abstract:
We review application of microstructured and photonic bandgap fibers for designing resonant optical sensors of changes in the value of analyte refractive index. This research subject has recently invoked much attention due to development of novel fiber types, as well as due to development of techniques for the activation of fiber microstructure with functional materials. Particularly, we consider two sensors types. The first sensor type employs hollow core photonic bandgap fibers where core guided mode is confined in the analyte filled core through resonant effect in the surrounding periodic reflector. The second sensor type employs metalized microstructured or photonic bandgap waveguides and fibers, where core guided mode is phase matched with a plasmon propagating at the fiber/analyte interface. In resonant sensors one typically employs fibers with strongly nonuniform spectral transmission characteristics that are sensitive to changes in the real part of the analyte refractive index. Moreover, if narrow absorption lines are present in the analyte transmission spectrum, due to Kramers-Kronig relation this will also result in strong variation in the real part of the refractive index in the vicinity of an absorption line. Therefore, resonant sensors allow detection of minute changes both in the real part of the analyte refractive index (10−6–10−4 RIU), as well as in the imaginary part of the analyte refractive index in the vicinity of absorption lines. In the following we detail various resonant sensor implementations, modes of operation, as well as analysis of sensitivities for some of the common transduction mechanisms for bio- and chemical sensing applications. Sensor designs considered in this review span spectral operation regions from the visible to terahertz.

Abstract:
Persistent
infection with a high-risk human papillomavirus (HRHPV) is generally accepted
as a necessary cause of cervical cancer. Modern lifestyle may represent the
most influential factor considering persistent genital human papillomavirus
(HPV) infection in women. Due to the contemporary clothing and use of toilet
bowl, the female micturition is usually performed in
sitting position with fully adducted thighs. The resistance to the urine flow
due to clenched Labia maiora and Labia minora and
capillary pressure among the folded walls of the vagina may cause an abnormal ascension of the urine
into the vagina. Urine is an excellent cultivating medium for many microorganisms,
including HPV. Education to adequate way of micturition in young girls might be
a simple way to significantly reduce the
likelihood for a persistent HRHPV infection, by eliminating conditions suitable for growth of virus.

Abstract:
We analyze the microstructure of He-II in the framework of the method of collective variables (CV), which was proposed by Bogolyubov and Zubarev and was developed later by Yukhnovskii and Vakarchuk. The logarithm of the ground-state wave function of He-II, ln(Psi_0), is calculated in the approximation of "two sums", i.e., as a Jastrow function and first (three-particle) correction. In the CV method equations for Psi_0 are deduced from the N-particle Schro'dinger equation. We also take into account the connection between the structure factor and Psi_0, which allows one to obtain Psi_0 from the structure factor of He-II, not from a model potential of interaction between He-II atoms. It should be emphasized that the model does not have any free parameters or functions. The amount of one-particle (N_1) and two-particle (N_2) condensates is calculated for the ground state of He-II: we find N_1=0.27N and N_2=0.53N in the Jastrow approximation for Psi_0, and, taking into account the three-particle correction to ln(Psi_0), we obtain N_1=0.06N (which agrees with the experiment) and $N_2=0.16N. In the approximation of "two sums", we also find that the higher s-particle condensates (s>2) are absent in He-II at T=0.

Abstract:
With the help of perturbation theory, we study the ground state of a Bose gas in a spherical trap, using the solution in the Thomas--Fermi approximation as the zero approximation. We have found within a certain approximation that, in some very narrow intervals of values of the magnetic field of a trap, the solution deviates strongly from that in the Thomas--Fermi approximation. If the magnetic field is equal to one of such critical values, the size (or even the shape) of the condensate cloud should significantly differ from the Thomas--Fermi one.

Abstract:
The nature of physical processes can depend substantially on the dimensionality of a system. One such example are buckling instabilities, which arise from the competition between axial compression and bending in elastic filaments. Thus, coiling of a jet of viscous fluid falling on a substrate (honey poured on a toast) \cite{maha1,griffiths} behaves quite differently from the coiling of viscous sheets (volcanous lava sliding on a crust) \cite{johnson,ramberg}. Here we consider a novel effect of coiling of a fluid jet confined to a two dimensional film.