Phase Ambiguity (phase + ambiguity)

Distribution by Scientific Domains


Selected Abstracts


Simple estimates of haplotype relative risks in case-control data

GENETIC EPIDEMIOLOGY, Issue 6 2006
Benjamin French
Abstract Methods of varying complexity have been proposed to efficiently estimate haplotype relative risks in case-control data. Our goal was to compare methods that estimate associations between disease conditions and common haplotypes in large case-control studies such that haplotype imputation is done once as a simple data-processing step. We performed a simulation study based on haplotype frequencies for two renin-angiotensin system genes. The iterative and noniterative methods we compared involved fitting a weighted logistic regression, but differed in how the probability weights were specified. We also quantified the amount of ambiguity in the simulated genes. For one gene, there was essentially no uncertainty in the imputed diplotypes and every method performed well. For the other, ,60% of individuals had an unambiguous diplotype, and ,90% had a highest posterior probability greater than 0.75. For this gene, all methods performed well under no genetic effects, moderate effects, and strong effects tagged by a single nucleotide polymorphism (SNP). Noniterative methods produced biased estimates under strong effects not tagged by an SNP. For the most likely diplotype, median bias of the log-relative risks ranged between ,0.49 and 0.22 over all haplotypes. For all possible diplotypes, median bias ranged between ,0.73 and 0.08. Results were similar under interaction with a binary covariate. Noniterative weighted logistic regression provides valid tests for genetic associations and reliable estimates of modest effects of common haplotypes, and can be implemented in standard software. The potential for phase ambiguity does not necessarily imply uncertainty in imputed diplotypes, especially in large studies of common haplotypes. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source]


Angle differential-QAM scheme for resolving phase ambiguity in continuous transmission system

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 6 2008
Jeng-Kuang Hwang
Abstract An angle differential quadrature amplitude modulation (ADQAM) scheme is proposed to solve phase ambiguity problem in non-data-aided continuous transmission system with square QAM constellation. Starting from the 16-ADQAM case, we derive differential encoding and decoding schemes in terms of two differential angles and use a solar system analogy for explanation. The 16-ADQAM system incurs only about 0.5-dB performance degradation compared with the coherent 16-QAM system under AWGN channel. Generalization of flat fading channel and higher-level ADQAM is straightforward. Copyright © 2007 John Wiley & Sons, Ltd. [source]


The algebraic approach to the phase problem

ACTA CRYSTALLOGRAPHICA SECTION A, Issue 5 2005
A. Cervellino
A rather detailed report is presented on the present status of the algebraic approach to the phase problem in the case of an ideal crystal in order to make clear that some points must still be proven for it to apply to neutron scattering. To make this extension, the most important results that were previously obtained in the case of X-ray scattering are derived again by a different procedure. By so doing, the three-dimensional case is treated explicitly, the polynomial equations in a single variable whose roots determine the positions of the scattering centres are explicitly reported and the procedure is shown to generalize to neutron scattering, overcoming the difficulty related to the non-positivity of the scattering density. In this way, it is fully proven that the atomicity assumption removes the phase ambiguity in the sense that the full diffraction pattern of an ideal crystal can uniquely be reconstructed from a suitable finite portion of it in both X-ray and neutron scattering. The procedures able to isolate these portions that contain the pattern's full information are also given. [source]


Using Case-parent Triads to Estimate Relative Risks Associated with a Candidate Haplotype

ANNALS OF HUMAN GENETICS, Issue 3 2009
Min Shi
Summary Estimating haplotype relative risks in a family-based study is complicated by phase ambiguity and the many parameters needed to quantify relative risks for all possible diplotypes. This problem becomes manageable if a particular haplotype has been implicated previously as relevant to risk. We fit log-linear models to estimate the risks associated with a candidate haplotype relative to the aggregate of other haplotypes. Our approach uses existing haplotype-reconstruction algorithms but requires assumptions about the distribution of haplotypes among triads in the source population. We consider three levels of stringency for those assumptions: Hardy-Weinberg Equilibrium (HWE), random mating, and no assumptions at all. We assessed our method's performance through simulations encompassing a range of risk haplotype frequencies, missing data patterns, and relative risks for either offspring or maternal genetic effects. The unconstrained model provides robustness to bias from population structure but requires excessively large sample sizes unless there are few haplotypes. Assuming HWE accommodates many more haplotypes but sacrifices robustness. The model assuming random mating is intermediate, both in the number of haplotypes it can handle and in robustness. To illustrate, we reanalyze data from a study of orofacial clefts to investigate a 9-SNP candidate haplotype of the IRF6 gene. [source]


Direct-method SAD phasing of proteins enhanced by the use of intrinsic bimodal phase distributions in the subsequent phase-improvement process

ACTA CRYSTALLOGRAPHICA SECTION D, Issue 11 2009
Li-Jie Wu
A modified SAD (single-wavelength anomalous diffraction) phasing algorithm has been introduced in the latest version of the program OASIS. In addition to direct-method phases and figures of merit, Hendrickson,Lattman coefficients that correspond to the original unresolved bimodal phase distributions are also output and used in subsequent phase-improvement procedures in combination with the improved phases. This provides the possibility of rebreaking the SAD phase ambiguity using the ever-improving phases resulting from the phase-improvement process. Tests using experimental SAD data from six known proteins showed that in all cases the new treatment produced significant improved results. [source]


Map self-validation: a useful discriminator of phase correctness at low resolution

ACTA CRYSTALLOGRAPHICA SECTION D, Issue 4 2001
David A. Langs
A new map-validation procedure is based on the correlation-coefficient agreement between the observed structure-factor magnitudes and their extrapolated values from suitably modified electron-density maps from which they have been each in turn systematically excluded. The correlation coefficient tends to a maximum as the phase errors in a map are reduced. This principle was used to resolve the single-wavelength anomalous scattering (SAS) and single-derivative isomorphous replacement (SIR) phase ambiguity for a number of error-free trial structures. Applications employing real data sets tend to be more difficult owing to data incompleteness and errors affecting the construction of the Argand diagram. [source]


Conditional Likelihood Methods for Haplotype-Based Association Analysis Using Matched Case,Control Data

BIOMETRICS, Issue 4 2007
Jinbo Chen
Summary Genetic epidemiologists routinely assess disease susceptibility in relation to haplotypes, that is, combinations of alleles on a single chromosome. We study statistical methods for inferring haplotype-related disease risk using single nucleotide polymorphism (SNP) genotype data from matched case,control studies, where controls are individually matched to cases on some selected factors. Assuming a logistic regression model for haplotype-disease association, we propose two conditional likelihood approaches that address the issue that haplotypes cannot be inferred with certainty from SNP genotype data (phase ambiguity). One approach is based on the likelihood of disease status conditioned on the total number of cases, genotypes, and other covariates within each matching stratum, and the other is based on the joint likelihood of disease status and genotypes conditioned only on the total number of cases and other covariates. The joint-likelihood approach is generally more efficient, particularly for assessing haplotype-environment interactions. Simulation studies demonstrated that the first approach was more robust to model assumptions on the diplotype distribution conditioned on environmental risk variables and matching factors in the control population. We applied the two methods to analyze a matched case,control study of prostate cancer. [source]