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PubMed2000

Variance and covariance components for weaning weight for Herefords in three countries.

Records from the Hereford Associations of the United States (USA), Canada, and Uruguay were used to estimate genetic and phenotypic variances and covariances for weaning weight. Estimation was done using a complete animal model, relatively large data sets, and the same methodology for the three countries in order to determine whether genetic parameters for weaning weight were homogeneous across environments. Data were composed of 2,322,722, 487,661, and 102,986 edited weaning weight records for USA, Canada, and Uruguay, respectively. Ten samples were obtained from each country by eliminating data from small herds with fewer than 500 records, selecting herds at random from the entire data set after removing the small herds, and then retaining the direct-sire-connected contemporary groups within each sample. The final sample sizes ranged from 9,832 to 46,377 records. An accelerated EM-REML algorithm was used in estimating the (co)variance components in each sample. The estimates were pooled by calculating the arithmetic mean of the 10 samples from within each country. Direct and maternal (in parentheses) heritability estimates were .24 (.16), .20 (.16), and .23 (.18) for USA, Canada, and Uruguay, respectively. Maternal heritabilities reported here are nearly 50% smaller than the values currently used in national genetic evaluation for the breed, which were estimated using sire-maternal grandsire models. Covariance between direct and maternal was negative in all countries, accounting for 6, 8, and 10% of the total phenotypic variation, and the total dam effect was 32.5, 37.0, and 34.0% in USA, Canada, and Uruguay, respectively. Total heritabilities were similar among the countries, with values of .19, .19, and .17 for the three respective countries. The similarity of genetic and environmental parameters across the three countries suggests that joint genetic evaluation is feasible across environments provided that the genotype x environment interaction is negligible and can be ignored.

Animals↗

PubMed2000

Investigation of genotype x environment interactions for weaning weight for Herefords in three countries.

The objective of this study was to investigate the possibility of genotype x environment interactions for weaning weight (WWT) between different regions of the United States (US) and between Canada (CA), Uruguay (UY), and US for populations of Hereford cattle. Original data were composed of 487,661, 102,986, and 2,322,722 edited weaning weight records from CA, UY, and US, respectively. A total of 359 sires were identified as having progeny across all three countries; 240 of them had at least one progeny with a record in each environment. The data sets within each country were reduced by retaining records from herds with more than 500 WWT records, with an average contemporary group size of greater than nine animals, and that contained WWT records from progeny or maternal grand-progeny of the across-country sires. Data sets within each country were further reduced by randomly selecting among remaining herds. Four regions within US were defined: Upper Plains (UP), Cornbelt (CB), South (S), and Gulf Coast (GC). Similar sampling criteria and common international sires were used to form the within-US regional data sets. A pairwise analysis was done between countries and regions within US (UP-CB vs S-GC, UP vs CB, and S vs GC) for the estimation of (co)variance components and genetic correlation between environments. An accelerated EM-REML algorithm and a multiple-trait animal model that considered WWT as a different trait in each environment were used to estimate parameters in each pairwise analysis. Direct and maternal (in parentheses) estimated genetic correlations for CA vs UY, CA vs US, US vs UY, UP-CB vs S-GC, UP vs CB, and S vs GC were .88 (.84), .86 (.82), .90 (.85), .88 (.87), .88 (.84), and .87 (.85), respectively. The general absence of genotype x country interactions observed in this study, together with a prior study that showed the similarity of genetic and environmental parameters across the three countries, strongly indicates that a joint WWT genetic evaluation for Hereford cattle could be conducted using a model that treated the information from CA, UY, and US as a single population using single population-wide genetic parameters.

Animals↗

PubMed2002

Investigation of genotype x country interactions for growth traits in beef cattle.

The importance of genotype x country interactions for weaning and birth weight and postweaning gain between Argentina (AR), Canada (CA), Uruguay (UY), and the United States (US) for populations of Hereford cattle was investigated. Three sample data sets of computationally manageable sizes were formed for each trait and pairwise combination of countries to investigate possible interactions. Parameters were estimated for each sample data set via an accelerated EM-REML algorithm and multiple-trait animal models that considered either weaning or birth weight as a different trait in each country. Direct and maternal (in parentheses) weaning weight genetic correlation estimates for AR-CA, AR-UY, AR-US, CA-UY, CA-US, and UY-US were 0.82 (0.80), 0.81 (0.72), 0.81 (0.79), 0.83 (0.78), 0.85 (0.82), and 0.86 (0.81), respectively. Direct and maternal (in parentheses) birth weight genetic correlation estimates were 0.92 (0.62), 0.97, (0.85), and 0.99 (0.97) for AR-CA, AR-US, and CA-US, respectively. Birth weight was not analyzed for UY due to small amounts of data. Postweaning gain in CA and US was 160-d gain, and in AR and UY 345-d gain was used. Across-country direct genetic correlations for postweaning gain were estimated for each pairwise country data set using a model that considered weaning weight as the same trait across each country, whereas postweaning gain was treated as a different trait in each country. Direct genetic correlation estimates for postweaning gain for AR-CA, AR-UY, AR-US, CA-UY, CA-US, and US-UY were 0.64, 0.80, 0.51, 0.84, 0.92, and 0.83, respectively. The overall results indicate that weaning and birth weights of Hereford calves can be analyzed as the same trait in all countries with a common set of heritabilities and genetic correlations, after adjustment for heterogenous phenotypic variances across countries. Postweaning gain in CA and US can be considered as the same trait and analyzed using a single set of parameters. Postweaning gain in AR and UY should be considered as a separate trait from postweaning gain in CA and US, and postweaning gain in AR and UY can be considered as the same trait and analyzed using a common heritability, after adjustment for phenotypic variance differences between the two countries.

Animals↗

PubMed2005

Genrate: a generative model that finds and scores new genes and exons in genomic microarray data.

Recently, researchers have made some progress in using microarrays to validate predicted exons in genome sequence and find new gene structures. However, current methods rely on separately making threshold-based decisions on intensity of expression, similarity of expression profiles, and arrangements of exons in the genome. We have taken a Bayesian approach and developed GenRate, a generative model that accounts for both genome-wide expression data taken from multiple conditions (e.g. tissues) and co-location and density of probes in DNA sequence data. GenRate balances probabilistic evidence derived from different sources and outputs scores (log-likelihoods) for each gene model, enabling the estimation of false-positive and false-negative rates. The model has a number of local minima that is exponential in the length of the DNA sequence data, so direct application of the EM learning algorithm produces poor results. We describe a novel way of parameterizing the model using examples from the data set, so that good solutions are found using an efficient algorithm. We apply GenRate to a subset of mouse genome-wide expression data that we have created, and discuss the statistical significance of the genes found by GenRate. Three of the highest-ranking gene structures found by GenRate, each containing thousands of bases from the genome, are confirmed using RT-PCR experiments.

Animals↗

PubMed1995

An empirical Bayes approach to smoothing in backcalculation of HIV infection rates.

Backcalculation is a methodology to reconstruct the past human immunodeficiency virus (HIV) infection rates from the AIDS incidence data and incubation distribution by deconvolution. Smoothing has proved important in backcalculation, and a key question is how to choose the amount of smoothing. This paper proposes an empirical Bayes approach in which the smoothing parameter is estimated from the data. We introduce a family of priors that reflect the notion of closeness of neighboring infection rates. The variance parameter in the prior family plays the role of the smoothing parameter and is estimated by a method similar to the residual maximum likelihood in linear random effects model through an efficient EM (expectation/maximization) algorithm. A number of penalized likelihood functions that have been used in backcalculation have an empirical Bayes formulation. A bootstrap confidence interval for the infection rates is proposed. The methodology is illustrated with United States AIDS incidence data.

Acquired Immunodeficiency Syndrome↗

PubMed1996

[Evaluation of simultaneous acquisition of transmission and emission data on thallium-201 myocardial SPECT].

This study evaluates the usefulness of attenuation correction on regional myocardial tracer distributions defined by Thallium-201 myocardial SPECT images obtained from cardiac phantoms and patients with or without coronary heart disease. A three-detector SPECT system equipped with a Technetium-99m line source and a fan-beam collimator was used for simultaneous transmission and emission data acquisition. All three detectors were equipped with fan-beam collimators. Thallium-201 myocardial scintigraphy was performed on phantom study and 19 patients. Transmission images, uncorrected and corrected emission images were iteratively reconstructed with a EM-ML algorithm. Attenuation map computed from the transmission data was utilized for the attenuation correction. For the phantom study, circumferential profile analysis was applied to both datasets of horizontal long-axis slices through the center of the phantom. The maximum profile value in the circumferential profile set to 100% in the normalized uncorrected and corrected profiles. The uncorrected circumferential profiles from cardiac insert model 7070 and RH-2 cardiophantom showed decrease in activity in basal regions which appeared improvement in the attenuation corrected profiles. In clinical study, the inferior-to-anterior activity ratio, changed from 0.78 +/- 0.10 to 0.97 +/- 0.11 on stress images in patients with inferior ischemia and from 0.96 +/- 0.12 to 1.15 +/- 0.13 on 4 hour delayed or rest images in normal cases. The anteroapical wall of the attenuation corrected images, however, showed a decrease in activity relative to the inferior wall in normal cases. The increase in activity in inferior wall on attenuation corrected images was observed frequently in clinical study but not in phantom study. A presence of scatter from the liver or bowels may cause the increase in activity in the inferior wall in clinical study. In conclusion, transmission scan is one of the useful methods for the attenuation correction. Scatter correction, however, is also necessary to make an accurate attenuation corrected images.

Heart↗

PubMed1997

Latent variable modeling of diagnostic accuracy.

Latent class analysis has been applied in medical research to assessing the sensitivity and specificity of diagnostic tests/diagnosticians. In these applications, a dichotomous latent variable corresponding to the unobserved true disease status of the patients is assumed. Associations among multiple diagnostic tests are attributed to the unobserved heterogeneity induced by the latent variable, and inferences for the sensitivities and specificities of the diagnostic tests are made possible even though the true disease status is unknown. However, a shortcoming of this approach to analyses of diagnostic tests is that the standard assumption of conditional independence among the diagnostic tests given a latent class is contraindicated by the data in some applications. In the present paper, models incorporating dependence among the diagnostic tests given a latent class are proposed. The models are parameterized so that the sensitivities and specificities of the diagnostic tests are simple functions of model parameters, and the usual latent class model obtains as a special case. Marginal models are used to account for the dependencies within each latent class. An accelerated EM gradient algorithm is demonstrated to obtain maximum likelihood estimates of the parameters of interest, as well as estimates of the precision of the estimates.

Analysis of Variance↗

PubMed2001

Total variation norm for three-dimensional iterative reconstruction in limited view angle tomography.

An iterative Bayesian reconstruction algorithm for limited view angle tomography, or ectomography, based on the three-dimensional total variation (TV) norm has been developed. The TV norm has been described in the literature as a method for reducing noise in two-dimensional images while preserving edges, without introducing ringing or edge artefacts. It has also been proposed as a 2D regularization function in Bayesian reconstruction, implemented in an expectation maximization algorithm (TV-EM). The TV-EM was developed for 2D single photon emission computed tomography imaging, and the algorithm is capable of smoothing noise while maintaining edges without introducing artefacts. The TV norm was extended from 2D to 3D and incorporated into an ordered subsets expectation maximization algorithm for limited view angle geometry. The algorithm, called TV3D-EM, was evaluated using a modelled point spread function and digital phantoms. Reconstructed images were compared with those reconstructed with the 2D filtered backprojection algorithm currently used in ectomography. Results show a substantial reduction in artefacts related to the limited view angle geometry, and noise levels were also improved. Perhaps most important, depth resolution was improved by at least 45%. In conclusion, the proposed algorithm has been shown to improve the perceived image quality.

Algorithms↗

PubMed2006

Image reconstruction for positron emission tomography using fuzzy nonlinear anisotropic diffusion penalty.

Iterative algorithms such as maximum likelihood-expectation maximization (ML-EM) become the standard for the reconstruction in emission computed tomography. However, such algorithms are sensitive to noise artifacts so that the reconstruction begins to degrade when the number of iterations reaches a certain value. In this paper, we have investigated a new iterative algorithm for penalized-likelihood image reconstruction that uses the fuzzy nonlinear anisotropic diffusion (AD) as a penalty function. The proposed algorithm does not suffer from the same problem as that of ML-EM algorithm, and it converges to a low noisy solution even if the iteration number is high. The fuzzy reasoning instead of a nonnegative monotonically decreasing function was used to calculate the diffusion coefficients which control the whole diffusion. Thus, the diffusion strength is controlled by fuzzy rules expressed in a linguistic form. The proposed method makes use of the advantages of fuzzy set theory in dealing with uncertain problems and nonlinear AD techniques in removing the noise as well as preserving the edges. Quantitative analysis shows that the proposed reconstruction algorithm is suitable to produce better reconstructed images when compared with ML-EM, ordered subsets EM (OS-EM), Gaussian-MAP, MRP, TV-EM reconstructed images.

Algorithms↗

PubMedDate not supplied

Model-based particle picking for cryo-electron microscopy.

We describe an algorithm for finding particle images in cryo-EM micrographs. The algorithm starts from a crude 3D map of the target particle, computed from a relatively small number of manually picked images, and then projects the map in many different directions to give synthetic 2D templates. The templates are clustered and averaged and then cross-correlated with the micrographs. A probabilistic model of the imaging process then scores cross-correlation peaks to produce the final picks. We give quantitative results on two quite different target particles: keyhole limpet hemocyanin and p97 AAA ATPase. On these particles our automatic particle picker shows human performance level, as measured by the Fourier shell correlations of 3D reconstructions.

Adenosine Triphosphatases↗

PubMed2002

Multi-resolution contour-based fitting of macromolecular structures.

A novel contour-based matching criterion is presented for the quantitative docking of high-resolution structures of components into low-resolution maps of macromolecular complexes. The proposed Laplacian filter is combined with a six-dimensional search using fast Fourier transforms to rapidly scan the rigid-body degrees of freedom of a probe molecule relative to a fixed target density map. A comparison of the docking performance with the standard cross-correlation criterion demonstrates that contour matching with the Laplacian filter significantly extends the viable resolution range of correlation-based fitting to resolutions as low as 30 A. The gain in docking precision at medium to low resolution (15-30 A) is critical for image reconstructions from electron microscopy (EM). The new algorithm enables for the first time the reliable docking of smaller molecular components into EM densities of large biomolecular assemblies at such low resolutions. As an example of the practical effectiveness of contour-based fitting, a new pseudo-atomic model of a microtubule was constructed from a 20 A resolution EM map and from atomic structures of alpha and beta tubulin subunits.

Algorithms↗

PubMed1999

Fourier rebinning applied to multiplanar circular-orbit cone-beam SPECT.

We study the application of Fourier rebinning methods to dual-planar cone-beam SPECT. Dual-planar cone-beam SPECT involves the use of a pair of dissimilar cone-beam collimators on a dual-camera SPECT system. Each collimator has its focus in a different axial plane. While dual-planar data is best reconstructed with fully three-dimensional (3-D) iterative methods, these methods are slow and have prompted a search for faster reconstruction techniques. Fourier rebinning was developed to estimate equivalent parallel projections from 3-D PET data, but it simply expresses a relationship between oblique projections taken in planes not perpendicular to the axis of rotation and direct projections taken in those that are. We find that it is possible to put cone-beam data in this context as well. The rebinned data can then be reconstructed using either filtered backprojection (FBP) or parallel iterative algorithms such as OS-EM. We compare the Feldkamp algorithm and fully 3-D OSEM reconstruction with Fourier-rebinned reconstructions on realistically-simulated Tc-99m HMPAO brain SPECT data. We find that the Fourier-rebinned reconstructions exhibit much less image noise and lower variance in region-of-interest (ROI) estimates than Feldkamp. Also, Fourier-rebinning followed by OSEM with nonuniform attenuation correction exhibits less bias in ROI estimates than Feldkamp with Chang attenuation correction. The Fourier-rebinned ROI estimates exhibit bias and variance comparable to those from fully 3-D OSEM and require considerably less processing time. However, in areas off the axis of rotation, the axial-direction resolution of FORE-reconstructed images is poorer than that of images reconstructed with 3-D OSEM. We conclude that Fourier rebinning is a practical and potentially useful approach to reconstructing data from dual-planar circular-orbit cone-beam systems.

Brain↗

PubMed2006

The influence of noise in full Monte Carlo ML-EM and dual matrix reconstructions in positron emission tomography.

Monte Carlo (MC) simulations in positron emission tomography (PET) play an important role in detector modeling and algorithm testing. Whereas the simulations are widely used in a forward projection manner to accomplish this task, ideally they should be included into the reconstruction process itself. It is therefore desirable to investigate the convergence properties and the propagation of MC noise of these kinds of reconstruction algorithms. MC simulations were integrated into the maximum likelihood expectation maximization (ML-EM) algorithm in two different ways. In the full matrix approach the system matrix was calculated by running MC simulations, including scatter. This matrix was used in both the projector and the backprojector. In the dual matrix (DM) approach, MC simulations were used to incorporate scatter in the projector, whereas the backprojector only comprised attenuation. Repeated reconstructions with different MC seeds allowed a statistical analysis of the error at each iteration step and made it possible to investigate separately the propagation of the MC noise that was introduced by the sinogram, by the projector, and by the matrix. Both approaches resulted in similar images, but the DM approach with unmatched projector and backprojector yielded a faster initial convergence when compared to the ideal full matrix approach. The analysis of the noise sources for the modeled single ring scanner in full matrix reconstruction showed that the noise introduced by the matrix became comparable to the noise introduced by the sinogram when using a matrix that was simulated with 10,000 emissions/voxel.

Algorithms↗

PubMed2004

Emission image reconstruction for randoms-precorrected PET allowing negative sinogram values.

Most positron emission tomography (PET) emission scans are corrected for accidental coincidence (AC) events by real-time subtraction of delayed-window coincidences, leaving only the randoms-precorrected data available for image reconstruction. The real-time randoms precorrection compensates in mean for AC events but destroys the Poisson statistics. The exact log-likelihood for randoms-precorrected data is inconvenient, so practical approximations are needed for maximum likelihood or penalized-likelihood image reconstruction. Conventional approximations involve setting negative sinogram values to zero, which can induce positive systematic biases, particularly for scans with low counts per ray. We propose new likelihood approximations that allow negative sinogram values without requiring zero-thresholding. With negative sinogram values, the log-likelihood functions can be nonconcave, complicating maximization; nevertheless, we develop monotonic algorithms for the new models by modifying the separable paraboloidal surrogates and the maximum-likelihood expectation-maximization (ML-EM) methods. These algorithms ascend to local maximizers of the objective function. Analysis and simulation results show that the new shifted Poisson (SP) model is nearly free of systematic bias yet keeps low variance. Despite its simpler implementation, the new SP performs comparably to the saddle-point model which has shown the best performance (as to systematic bias and variance) in randoms-precorrected PET emission reconstruction.

Algorithms↗

PubMed2005

Automatic ultrastructure segmentation of reconstructed cryoEM maps of icosahedral viruses.

We present an automatic algorithm to segment all the local and global asymmetric units of a three-dimensional density map of icosahedral viruses. This approach is readily applicable to the structural analysis of a broad range of virus structures that are reconstructed using cryo-electron microscopy (cryo-EM) technique. Our algorithm includes three major steps operating on the three dimensional density map: the detection of critical points of the volumetric density function, the detection of global and local symmetry axes, and, finally, the boundary segmentation of all the asymmetric units. We demonstrate the efficacy of our algorithm and report our results on several experimental volumetric datasets, consisting of both reconstructed cryo-EM molecular density maps taken from the European Bioinformatics Institute archive, as well our own synthetically generated (blurred) maps calculated from X-ray resolution molecular structural data taken from the Protein Data Bank.

Algorithms↗

PubMed2005

The influence of filtered back-projection and iterative reconstruction on partial volume correction in PET.

AIM: We assess the influence of the reconstruction algorithms [OS-EM for the iterative one vs. a filtered back-projection in Fourier space (DiFT)] on partial volume correction in PET employing a fully 3D 3-compartment MR based PV-correction algorithm. The gray matter voxels in the PET image -- after removal of the white matter and cerebrospinal fluid contribution -- are corrected voxel-by-voxel using the image resolution. MATERIAL, METHODS: Phantom measurements and one healthy human brain FDG study were carried out. For the OSEM reconstruction, a combination of iteration steps and subset numbers (It/Sub) was used, whereby in case of no-convergence the image resolution had to be fitted. The RESULTS from the DiFT reconstruction were equivalent to those obtained from the OSEM reconstruction with 10/32 combination for objects with widespread activity concentration. For the sphere phantom, the mean recovery based on the actual values achieved 99.2% +/- 1.8 for all spheres and all reconstruction modes and It/sub combinations (except for 2/8). In case of the Hoffman 3D brain phantom the mean recovery of the cortical regions was 101% +/- 1.2 (the increase based on the uncorrected values: 35.5% +/- 1.5), while the subcortical regions reached a mean recovery of 80% with an increase of 43.9% +/- 2.5. For the human data, an increase of the metabolized values of several cortical regions ranged between 42% and 48% independent from the reconstruction mode. CONCLUSIONS: Our data show that the 3-compartment fully 3-D MR based PV-correction is sensitive to the choice of reconstruction algorithms and to the parameter choice. They indicate that despite improved spatial resolution, the use of the iterative reconstruction algorithm for PV-correction results in similar recovery factors when compared to a correction using DiFT reconstruction, insofar the image resolution values are fitted at the It/Sub combinations.

Algorithms↗

PubMed2006

Ribosome dynamics: insights from atomic structure modeling into cryo-electron microscopy maps.

Single-particle cryo-electron microscopy (cryo-EM) is the method of choice for studying the dynamics of macromolecular machines both at a phenomenological and, increasingly, at the molecular level, with the advent of high-resolution component X-ray structures and of progressively improving fitting algorithms. Cryo-EM has shed light on the structure of the ribosome during the four steps of translation: initiation, elongation, termination, and recycling. Interpretation of cryo-EM reconstructions of the ribosome in quasi-atomic detail reveals a picture in which the ribosome uses RNA not only to catalyze chemical reactions, but also as a means for signal transduction over large distances.

Computer Simulation↗

PubMedDate not supplied

2D fast rotational matching for image processing of biophysical data.

In 3D single particle reconstruction, which involves the translational and rotational matching of a large number of electron microscopy (EM) images, the algorithmic performance is largely dependent on the efficiency and accuracy of the underlying 2D image alignment kernel. We present a novel fast rotational matching kernel for 2D images (FRM2D) that significantly reduces the cost of this alignment. The alignment problem is formulated using one translational and two rotational degrees of freedom. This allows us to take advantage of fast Fourier transforms (FFTs) in rotational space to accelerate the search of the two angular parameters, while the remaining translational parameter is explored, within a limited range, by exhaustive search. Since there are no boundary effects in FFTs of cyclic angular variables, we avoid the expensive zero padding associated with Fourier transforms in linear space. To verify the robustness of our method, efficiency and accuracy tests were carried out over a range of noise levels in realistic simulations of EM images. Performance tests against two standard alignment methods, resampling to polar coordinates and self-correlation, demonstrate that FRM2D compares very favorably to the traditional methods. FRM2D exhibits a comparable or higher robustness against noise and a significant gain in efficiency that depends on the fineness of the angular sampling and linear search range.

Algorithms↗