Performance of genomic selection in mice

Selection plans in plant and animal breeding are driven by genetic evaluation. Recent developments suggest using massive genetic marker information, known as "genomic selection." There is little evidence of its performance, though. We empirically compared three strategies for selection: (1) use of pedigree and phenotypic information, (2) use of genomewide markers and phenotypic information, and (3) the combination of both. We analyzed four traits from a heterogeneous mouse population (http://gscan.well.ox.ac.uk/), including 1884 individuals and 10,946 SNP markers. We used linear mixed models, using extensions of association analysis. Cross-validation techniques were used, providing assumption-free estimates of predictive ability. Sampling of validation and training data sets was carried out across and within families, which allows comparing across- and within-family information. Use of genomewide genetic markers increased predictive ability up to 0.22 across families and up to 0.03 within families. The latter is not statistically significant. These values are roughly comparable to increases of up to 0.57 (across family) and 0.14 (within family) in accuracy of prediction of genetic value. In this data set, within-family information was more accurate than across-family information, and populational linkage disequilibrium was not a completely accurate source of information for genetic evaluation. This fact questions some applications of genomic selection.     

Characterizing and correcting for the dynamic response of a bag-in-box system

A bag-in-box system (BBS) whose volume is monitored by a mechanical spirometer tends to have a slow response if the volume of the box is large, and this may significantly affect its measurement of gas flow. We describe a device for creating reproducible gas flows with which the impulse response of a BBS may be conveniently determined. Two computational techniques for correcting a BBS flow measurement for the effects of the impulse response were investigated: 1) an exponential model method that assumes a second-order model of the BBS dynamics and 2) a Fourier transform-based method of deconvolution known as Wiener filtering. Both correction methods produced a significant increase in the accuracy of BBS flow estimations, with the Wiener filter giving superior results.     

Secondary structures comparison of aquaporin-1 and bacteriorhodopsin: a Fourier transform infrared spectroscopy study of two-dimensional membrane crystals.

Aquaporins are integral membrane proteins found in diverse animal and plant tissues that mediate the permeability of plasma membranes to water molecules. Projection maps of two-dimensional crystals of aquaporin-1 (AQP1) reconstituted in lipid membranes suggested the presence of six to eight transmembrane helices in the protein. However, data from other sequence and spectroscopic analyses indicate that this protein may adopt a porin-like beta-barrel fold. In this paper, we use Fourier transform infrared spectroscopy to characterize the secondary structure of highly purified native and proteolyzed AQP1 reconstituted in membrane crystalline arrays and compare it to bacteriorhodopsin. For this analysis the fractional secondary structure contents have been determined by using several different algorithms. In addition, a neural network-based evaluation of the Fourier transform infrared spectra in terms of numbers of secondary structure segments and their interconnections [sij] has been performed. The following conclusions were reached: 1) AQP1 is a highly helical protein (42-48% alpha-helix) with little or no beta-sheet content. 2) The alpha-helices have a transmembrane orientation, but are more tilted (21 degrees or 27 degrees, depending on the considered refractive index) than the bacteriorhodopsin helices. 3) The helices in AQP1 undergo limited hydrogen/deuterium exchange and thus are not readily accessible to solvent. Our data support the AQP1 structural model derived from sequence prediction and epitope insertion experiments: AQP1 is a protein with at least six closely associated alpha-helices that span the lipid membrane.     

Aerodynamic study of different cyclist positions: CFD analysis and full-scale wind-tunnel tests

Three different cyclist positions were evaluated with Computational Fluid Dynamics (CFD) and wind-tunnel experiments were used to provide reliable data to evaluate the accuracy of the CFD simulations. Specific features of this study are: (1) both steady Reynolds-averaged Navier–Stokes (RANS) and unsteady flow modelling, with more advanced turbulence modelling techniques (Large-Eddy Simulation – LES), were evaluated; (2) the boundary layer on the cyclist’s surface was resolved entirely with low-Reynolds number modelling, instead of modelling it with wall functions; (3) apart from drag measurements, also surface pressure measurements on the cyclist’s body were performed in the wind-tunnel experiment, which provided the basis for a more detailed evaluation of the predicted flow field by CFD. The results show that the simulated and measured drag areas differed about 11% (RANS) and 7% (LES), which is considered to be a close agreement in CFD studies. A fair agreement with wind-tunnel data was obtained for the predicted surface pressures, especially with LES. Despite the higher accuracy of LES, its much higher computational cost could make RANS more attractive for practical use in some situations. CFD is found to be a valuable tool to evaluate the drag of different cyclist positions and to investigate the influence of small adjustments in the cyclist’s position. A strong advantage of CFD is that detailed flow field information is obtained, which cannot easily be obtained from wind-tunnel tests. This detailed information allows more insight in the causes of the drag force and provides better guidance for position improvements.     

Prediction of transmembrane regions of beta-barrel proteins using ANN- and SVM-based methods

This article describes a method developed for predicting transmembrane beta-barrel regions in membrane proteins using machine learning techniques: artificial neural network (ANN) and support vector machine (SVM). The ANN used in this study is a feed-forward neural network with a standard back-propagation training algorithm. The accuracy of the ANN-based method improved significantly, from 70.4% to 80.5%, when evolutionary information was added to a single sequence as a multiple sequence alignment obtained from PSI-BLAST. We have also developed an SVM-based method using a primary sequence as input and achieved an accuracy of 77.4%. The SVM model was modified by adding 36 physicochemical parameters to the amino acid sequence information. Finally, ANN- and SVM-based methods were combined to utilize the full potential of both techniques. The accuracy and Matthews correlation coefficient (MCC) value of SVM, ANN, and combined method are 78.5%, 80.5%, and 81.8%, and 0.55, 0.63, and 0.64, respectively. These methods were trained and tested on a nonredundant data set of 16 proteins, and performance was evaluated using "leave one out cross-validation" (LOOCV). Based on this study, we have developed a Web server, TBBPred, for predicting transmembrane beta-barrel regions in proteins (available at http://www.imtech.res.in/raghava/tbbpred).     

Accounting for genomic pre-selection in national BLUP evaluations in dairy cattle

Background

In future Best Linear Unbiased Prediction (BLUP) evaluations of dairy cattle, genomic selection of young sires will cause evaluation biases and loss of accuracy once the selected ones get progeny.

Methods

To avoid such bias in the estimation of breeding values, we propose to include information on all genotyped bulls, including the culled ones, in BLUP evaluations. Estimated breeding values based on genomic information were converted into genomic pseudo-performances and then analyzed simultaneously with actual performances. Using simulations based on actual data from the French Holstein population, bias and accuracy of BLUP evaluations were computed for young sires undergoing progeny testing or genomic pre-selection. For bulls pre-selected based on their genomic profile, three different types of information can be included in the BLUP evaluations: (1) data from pre-selected genotyped candidate bulls with actual performances on their daughters, (2) data from bulls with both actual and genomic pseudo-performances, or (3) data from all the genotyped candidates with genomic pseudo-performances. The effects of different levels of heritability, genomic pre-selection intensity and accuracy of genomic evaluation were considered.

Results

Including information from all the genotyped candidates, i.e. genomic pseudo-performances for both selected and culled candidates, removed bias from genetic evaluation and increased accuracy. This approach was effective regardless of the magnitude of the initial bias and as long as the accuracy of the genomic evaluations was sufficiently high.

Conclusions

The proposed method can be easily and quickly implemented in BLUP evaluations at the national level, although some improvement is necessary to more accurately propagate genomic information from genotyped to non-genotyped animals. In addition, it is a convenient method to combine direct genomic, phenotypic and pedigree-based information in a multiple-step procedure.     

A comparison of deconvolution techniques for stress relaxation

Stress relaxation (or equivalently creep) allows a large range of the relaxation (retardation) spectrum of materials to be examined, particularly at lower frequencies. However, higher frequency components of the relaxation curves (typically of the order of Hertz) are attenuated due to the finite time taken to strain the specimen. This higher frequency information can be recovered by deconvolution of the stress and strain during the loading period. This paper examines the use of three separate deconvolution techniques: numerical (Fourier) deconvolution, semi-analytical deconvolution using a theoretical form of the strain, and deconvolution by a linear approximation method. Both theoretical data (where the exact form of the relaxation function is known) and experimental data were used to assess the accuracy and applicability of the deconvolution methods. All of the deconvolution techniques produced a consistent improvement in the higher frequency data up to the frequencies of the order of Hertz, with the linear approximation method showing better resolution in high-frequency analysis of the theoretical data. When the different deconvolution techniques were applied to experimental data, similar results were found for all three deconvolution techniques. Deconvolution of the stress and strain during loading is a simple and practical method for the recovery of higher frequency data from stress-relaxation experiments.     

Rapid screening of the fermentation profiles of wine yeasts by Fourier transform infrared spectroscopy

A rapid screening method for the evaluation of the major fermentation products of Saccharomyces wine yeasts was developed using Fourier transform infrared spectroscopy and principal component factor analysis. Calibration equations for the quantification of volatile acidity, glycerol, ethanol, reducing sugar and glucose concentrations in fermented Chenin blanc and synthetic musts were derived from the Fourier transform infrared spectra of small-scale fermentations. The accuracy of quantification of volatile acidity in both Chenin blanc and synthetic must was excellent, and the standard error of prediction was 0.07 g l(-1) and 0.08 g l(-1), respectively. The respective standard error of prediction in Chenin blanc and synthetic musts for ethanol was 0.32% v/v and 0.31% v/v, for glycerol was 0.38 g l(-1) and 0.32 g l(-1), for reducing sugar in Chenin blanc must was 0.56 g l(-1) and for glucose in synthetic must was 0.39 g l(-1). These values were in agreement with the accuracy obtained by the respective reference methods used for the quantification of the components. The screening method was applied to quantify the fermentation products of glycerol-overproducing hybrid yeasts and commercial wine yeasts. Principal component factor analysis of the fermentation data facilitated an overall comparison of the fermentation profiles (in terms of the components tested) of the strains. The potential of Fourier transform infrared spectroscopy as a tool to rapidly screen the fermentative properties of wine yeasts and to speed up the evaluation processes in the initial stages of yeast strain development programs is shown.     

Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation

Accurate modeling of geographic distributions of species is crucial to various applications in ecology and conservation. The best performing techniques often require some parameter tuning, which may be prohibitively time‐consuming to do separately for each species, or unreliable for small or biased datasets. Additionally, even with the abundance of good quality data, users interested in the application of species models need not have the statistical knowledge required for detailed tuning. In such cases, it is desirable to use “default settings”, tuned and validated on diverse datasets. Maxent is a recently introduced modeling technique, achieving high predictive accuracy and enjoying several additional attractive properties. The performance of Maxent is influenced by a moderate number of parameters. The first contribution of this paper is the empirical tuning of these parameters. Since many datasets lack information about species absence, we present a tuning method that uses presence‐only data. We evaluate our method on independently collected high‐quality presence‐absence data. In addition to tuning, we introduce several concepts that improve the predictive accuracy and running time of Maxent. We introduce “hinge features” that model more complex relationships in the training data; we describe a new logistic output format that gives an estimate of probability of presence; finally we explore “background sampling” strategies that cope with sample selection bias and decrease model‐building time. Our evaluation, based on a diverse dataset of 226 species from 6 regions, shows: 1) default settings tuned on presence‐only data achieve performance which is almost as good as if they had been tuned on the evaluation data itself; 2) hinge features substantially improve model performance; 3) logistic output improves model calibration, so that large differences in output values correspond better to large differences in suitability; 4) “target‐group” background sampling can give much better predictive performance than random background sampling; 5) random background sampling results in a dramatic decrease in running time, with no decrease in model performance.     

Spatial and temporal variations in species occurrence rate affect the accuracy of occurrence models

Aim Predictive models of species occurrence have potential for prioritizing areas for competing land uses. Before widespread application, however, it is necessary to evaluate performance using independent data and effective accuracy measures. The objectives of this study were to (1) compare the effects of species occurrence rate on model accuracy, (2) assess the effects of spatial and temporal variation in occurrence rate on model accuracy, and (3) determine if the number of predictor variables affected model accuracy. Location We predicted the distributions of breeding birds in three adjacent mountain ranges in the Great Basin (Nevada, USA). Methods For each of 18 species, we developed separate models using five different data sets — one set for each of 2 years (to address the effects of temporal variation), and one set for each of three possible pairs of mountain ranges (to address the effects of spatial variation). We evaluated each model with an independent data set using four accuracy measures: discrimination ability [area under a receiver operating characteristic curve (AUC)], correct classification rate (CCR), proportion of presences correctly classified (sensitivity), and proportion of absences correctly classified (specificity). Results Discrimination ability was not affected by occurrence rate, whereas the other three accuracy measures were significantly affected. CCR, sensitivity and specificity were affected by species occurrence rate in the evaluation data sets to a greater extent than in the model‐building data sets. Discrimination ability was the only accuracy measure affected by the number of variables in a model. Main conclusions Temporal variation in species occurrence appeared to have a greater impact than did spatial variation. When temporal variation in species distributions is great, the relative costs of omission and commission errors should be assessed and long‐term census data should be examined before using predictive models of occurrence in a management setting.     

基于多源遥感数据的大豆叶面积指数估测精度对比

近年来遥感技术的革新促使遥感源越来越丰富.为分析多源遥感数据的叶面积指数(LAI)估测精度,本文以大豆为研究对象,利用比值植被指数(RVI)、归一化植被指数(NDVI)、土壤调整植被指数(SAVI)、差值植被指数(DVI)、三角植被指数(TVI)5种植被指数,结合地面实测LAI构建经验回归模型,比较3类遥感数据(地面高光谱数据、无人机多光谱影像以及高分一号WFV影像)对大豆LAI的估测能力,并从传感器几何位置和光谱响应特性以及像元空间分辨率三方面分析讨论了3类遥感数据的LAI反演差异.结果表明： 地面高光谱数据模型和无人机多光谱数据模型都可以准确预测大豆LAI(在α=0.01显著水平下,R²均>0.69,RMSE均<0.40);地面高光谱RVI对数模型的LAI预测能力优于无人机多光谱NDVI线性模型,但两者差异不大(E_A相差0.3%,R²相差0.04,RMSE相差0.006);高分一号WFV数据模型对研究区内大豆LAI的预测效果不理想(R²<0.30,RMSE>0.70).针对星、机、地三类遥感信息源,地面高光谱数据在反演LAI方面较传统多光谱数据有优势但不突出;16 m空间分辨率的高分一号WFV影像无法满足田块尺度作物长势监测的需求;在保证获得高精度大豆LAI预测值和高工作效率的前提条件下,基于无人机遥感的农情信息获取技术不失为一种最佳试验方案.在当今可用遥感信息源越来越多的情况下,农业无人机遥感信息可成为指导田块精细尺度作物管理的重要依据,为精准农业研究提供更科学准确的信息.     

Diagnostic and economic evaluation of new biomarkersfor Alzheimer¿s disease: the research protocol of a prospective cohort study

ABSTRACT: BACKGROUND: New research criteria for the diagnosis of Alzheimer's disease (AD) have recently been developed to enable an early diagnosis of AD pathophysiologyby relying on emerging biomarkers. To enable efficient allocation of health care resources, evidence is needed to support decision makers on the adoption of emerging biomarkers in clinical practice. The research goals are to 1) assess the diagnostic test accuracy of current clinical diagnostic work-up and emerging biomarkers in MRI, PET and CSF, 2) perform a cost-consequence analysis and 3) assess long-term cost-effectiveness by an economic model.Methods/designIn a cohort design 223 consecutive patients suspected of having a primary neurodegenerative disease are approached in four academic memory clinics and followed for two years. Clinical data and data on quality of life, costs and emerging biomarkers are gathered.Diagnostic test accuracy is determined by relating the clinical practice and new research criteria diagnoses to the reference diagnosis. The clinical practice diagnosis at baseline is reflected by a consensus procedure among experts using clinical information only (no biomarkers). The diagnosis based on the new research criteria is reflected by decision rules that combine clinical and biomarker information. The reference diagnosis is determined by a consensus procedure among experts based on clinical information on the course of symptoms over a two-year time period.A decision analytic model is built combining available evidence from different resources among which (accuracy) results from the study, literature and expert opinion to assess long-term cost-effectiveness of the emerging biomarkers. DISCUSSION: Several other multi-centre trials study the relative value of new biomarkers for early evaluation of AD and related disorders. The uniqueness of this study is the assessment of resource utilization and quality of life to enable an economic evaluation. The study results are generalizable to a population of patients who are referred to a memory clinic due to their memory problems.Trial registrationNCT01450891.     

Development of a record-keeping strategy for improvement of information retention in microbiological processing

The improvement of microbiological information processing in clinical laboratories depends on retention of information concerning who, what, when, how, and why each process was performed, the implementation of quality control procedures, and finally, its evaluation. The four objectives to be addressed are as follows: (1) to improve the collection of information concerned with microbiological processes, (2) to evaluate results of implemented strategies, (3) to offer a model data base to be used in research projects, and (4) to propose an evaluation model for comparative studies. To do this, microbiological cultures were collected from hospitalized patients from June 1997 to June 2003. Data for the analytical matrix were obtained from lab requests, medical history and the microbiological data. Statistical analyses were performed in Epi-Info 6. The laboratory records for 46,072 microbiological cultures were analyzed. Completion levels in data collection were compared between years 1997 and 2003. Samples from 1997 and 2003 showed 11% and 99% of the request forms specifically requesting microbiological culture, 11% and 99% were completed in 1997 and 2003, respectively. For the same years, 9% and 85% specifically stated the time of the request. Ten percent and 68%, respectively, provided complete information. Zero and 83% respectively stated who had collected the sample. Zero and 77%, respectively, specified the time of sample collection. Forms containing all relevent microbiological data were most complete with 78% and 96%, respectively. A database with 44 variables related to microbiological processes was created. In conclusion, improvement of microbiological data processing depends not only on the method of collection and completion of recorded information, but also on constant quality control and evaluation.     

Beyond average protein secondary structure content prediction using FTIR spectroscopy

This paper demonstrates that secondary structure information beyond purely protein secondary structure content can be predicted from FTIR (Fourier transform infrared spectroscopy) spectra of proteins with a high degree of accuracy. Both neural networks and adaptive neuro-fuzzy inference systems (ANFISs) were employed to predict helix/sheet segment information. The best results were achieved using ANFISs with fuzzy subtractive clustering based on normalised, compressed amide I data with an average SEP (standard error of prediction, root mean of squared errors) of 1.51. Predictions for average helix/sheet length based merely on the amide I band maximum position in combination with the full-width at half-height resulted in a comparable average SEP of 1.62. This suggests the importance of information on the position and width of the amide I band maximum for the prediction of helix/sheet segment information. Finally, the most promising pattern recognition approaches found in this study were applied to a protein with an as yet unknown x-ray structure: native a1-antichymotrypsin (a1-ACT).     

Curvilinear Three-Dimensional Modeling of Spinal Curves with Dual Kriging

In spinal deformation studies, three-dimensional reconstruction of the spine is frequently represented as a curve in space fitted to the vertebral centroids. Conventional interpolation techniques such as splines, Bezier and the least squares method are limited since they cannot describe precisely the great variety of spinal morphologies. This article presents a more general technique called dual kriging, which includes two mathematical constituents (drift and covariance) to adjust the interpolated functions to spinal deformity better. The cross-validation technique was used to compare the parametric representations of spinal curves with different combinations of drift and covariance functions. Model validation was performed from a series of analytic curves reflecting typical scoliotic spines. Calculation of geometric torsion, a sensitive parameter, was done to evaluate the accuracy of the kriging models. The best model showed an absolute mean difference of 1.2 x 10(-5) (+/- 7.1 x 10(-5) ) mm(-1) between the analytical and estimated geometric torsions compared to 5.25 x 10(-3) (+/- 3.7 x 10(-2) ) mm(-1) for the commonly used least-squares Fourier series method, a significant improvement in spinal torsion evaluation.     

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data

Background

Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA''s Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics.

Methodology/Principal Findings

We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005.

Conclusions/Significance

Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species'' distribution modelling.     

基于影像纹理特征的川西南山地常绿阔叶林有效叶面积指数的空间分析

遥感是获取叶面积指数（LAI）信息的最有吸引力的选择之一,但目前基于遥感数据的叶面积指数估测精度有限.本文以川西南山地常绿阔叶林为研究对象,基于地面调查的83个20 m×20 m样地和SPOT5数据,运用灰度共生矩阵法提取影像单波段、简单波段比图和主成分图的纹理信息,以不同图像处理方式的纹理参数作为辅助变量进行地统计分析估算有效LAI（LAIe）.结果表明： LAIe与不同方式处理图像的纹理参数存在不同程度的相关性,其中,与B₁波段、B₁/B₄和PC₁的均质性呈极显著相关关系.与以归一化植被指数（NDVI）为辅助变量相比,以纹理参数B₁波段、B₁/B₄和PC₁的均质性作为辅助变量估测LAIe的精度均有所提高,分别提高5.3%、11.0%、14.5%,还能在一定程度上降低统计误差.以NDVI、PC₁均质性作为辅助变量的LAIe空间地统计估测模型最优（R²＝0.840,RMSE=0.212）.本研究结果为合理地选择除植被指数外的其他辅助变量估测区域LAI的空间分布提供了一种新的思路和方法.     

VizStruct: exploratory visualization for gene expression profiling

MOTIVATION: DNA arrays provide a broad snapshot of the state of the cell by measuring the expression levels of thousands of genes simultaneously. Visualization techniques can enable the exploration and detection of patterns and relationships in a complex data set by presenting the data in a graphical format in which the key characteristics become more apparent. The dimensionality and size of array data sets however present significant challenges to visualization. The purpose of this study is to present an interactive approach for visualizing variations in gene expression profiles and to assess its usefulness for classifying samples. RESULTS: The first Fourier harmonic projection was used to map multi-dimensional gene expression data to two dimensions in an implementation called VizStruct. The visualization method was tested using the differentially expressed genes identified in eight separate gene expression data sets. The samples were classified using the oblique decision tree (OC1) algorithm to provide a procedure for visualization-driven classification. The classifiers were evaluated by the holdout and the cross-validation techniques. The proposed method was found to achieve high accuracy. AVAILABILITY: Detailed mathematical derivation of all mapping properties as well as figures in color can be found as supplementary on the web page http://www.cse.buffalo.edu/DBGROUP/bioinformatics/supplementary/vizstruct. All programs were written in Java and Matlab and software code is available by request from the first author.