scholarly journals MTG2: An efficient algorithm for multivariate linear mixed model analysis based on genomic information

2015 ◽  
Author(s):  
Sang Hong Lee ◽  
Julius van der Werf
Keyword(s):  
Complex Traits ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Covariance Structure ◽  
Random Regression ◽  
Current Standard ◽  
Model Framework ◽  
Genetic Covariance ◽  
Mixed Model Analysis ◽  
Mixed Model Equation

We have developed an algorithm for genetic analysis of complex traits using genome-wide SNPs in a linear mixed model framework. Compared to current standard REML software based on the mixed model equation, our method could be more than 1000 times faster. The advantage is largest when there is only a single genetic covariance structure. The method is particularly useful for multivariate analysis, including multi-trait models and random regression models for studying reaction norms. We applied our proposed method to publicly available mice and human data and discuss advantages and limitations.

scholarly journals A Novel Approach to the Design and Analysis of Field Experiments to Study Variation in the Tolerance and Resistance of Cultivars to Root Lesion Nematodes (Pratylenchus spp.)

2020 ◽  
Vol 110 (10) ◽  
pp. 1623-1631
Author(s):  
Karyn L. Reeves ◽  
Clayton R. Forknall ◽  
Alison M. Kelly ◽  
Kirsty J. Owen ◽  
Joshua Fanning ◽  
...  
Keyword(s):  
Mixed Model ◽  
Field Experiments ◽  
Linear Mixed Model ◽  
Random Regression ◽  
Yield Response ◽  
Response Curves ◽  
Model Framework ◽  
Management Options ◽  
Nematode Reproduction ◽  
Yield Response Curves

The root lesion nematode (RLN) species Pratylenchus thornei and P. neglectus are widely distributed within cropping regions of Australia and have been shown to limit grain production. Field experiments conducted to compare the performance of cultivars in the presence of RLNs investigate management options for growers by identifying cultivars with resistance, by limiting nematode reproduction, and tolerance, by yielding well in the presence of nematodes. A novel experimental design approach for RLN experiments is proposed where the observed RLN density, measured prior to sowing, is used to condition the randomization of cultivars to field plots. This approach ensured that all cultivars were exposed to consistent ranges of RLN in order to derive valid assessments of relative cultivar tolerance and resistance. Using data from a field experiment designed using the conditioned randomization approach and conducted in Formartin, Australia, the analysis of tolerance and resistance was undertaken in a linear mixed model framework. Yield response curves were derived using a random regression approach and curves modeling change in RLN densities between sowing and harvest were derived using splines to account for nonlinearity. Groups of cultivars sharing similar resistance levels could be identified. A comparison of slopes of yield response curves of cultivars belonging to the same resistance class identified differing tolerance levels for cultivars with equivalent exposures to both presowing and postharvest RLN densities. As such, the proposed design and analysis approach allowed tolerance to be assessed independently of resistance.

scholarly journals Up hill, down dale: quantitative genetics of curvaceous traits

2005 ◽  
Vol 360 (1459) ◽  
pp. 1443-1455 ◽  
Author(s):  
Karin Meyer ◽  
Mark Kirkpatrick
Keyword(s):  
Quantitative Genetics ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Selection Response ◽  
Repeated Measurements ◽  
Random Regression ◽  
Model Framework ◽  
Covariance Functions ◽  
Continuous Scale ◽  
Estimated Breeding Values

‘Repeated’ measurements for a trait and individual, taken along some continuous scale such as time, can be thought of as representing points on a curve, where both means and covariances along the trajectory can change, gradually and continually. Such traits are commonly referred to as ‘function-valued’ (FV) traits. This review shows that standard quantitative genetic concepts extend readily to FV traits, with individual statistics, such as estimated breeding values and selection response, replaced by corresponding curves, modelled by respective functions. Covariance functions are introduced as the FV equivalent to matrices of covariances. Considering the class of functions represented by a regression on the continuous covariable, FV traits can be analysed within the linear mixed model framework commonly employed in quantitative genetics, giving rise to the so-called random regression model. Estimation of covariance functions, either indirectly from estimated covariances or directly from the data using restricted maximum likelihood or Bayesian analysis, is considered. It is shown that direct estimation of the leading principal components of covariance functions is feasible and advantageous. Extensions to multi-dimensional analyses are discussed.

scholarly journals Reducing Aggression by Developing Emotional and Inhibitory Control

2021 ◽  
Vol 18 (10) ◽  
pp. 5263
Author(s):  
Miriam Romero-López ◽  
María Carmen Pichardo ◽  
Ana Justicia-Arráez ◽  
Judit Bembibre-Serrano
Keyword(s):  
Psychosocial Development ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Emotional Control ◽  
Control Group ◽  
Post Intervention ◽  
Mixed Model Analysis ◽  
Intervention Measures ◽  
Experimental Group

The objective of this study is to measure the effectiveness of a program on improving inhibitory and emotional control among children. In addition, it is assessed whether the improvement of these skills has an effect on the reduction of aggressive behavior in pre-school children. The participants were 100 children, 50 belonging to the control group and 50 to the experimental group, aged between 5 and 6 years. Pre-intervention and post-intervention measures of inhibitory and emotional control (BRIEF-P) and aggression (BASC) were taken. A Generalized Linear Mixed Model analysis (GLMM) was performed and found that children in the experimental group scored higher on inhibitory and emotional control compared to their peers in the control group. In addition, these improvements have an effect on the decrease in aggressiveness. In conclusion, preventive research should have among its priorities the design of such program given their implications for psychosocial development.

scholarly journals Methods to Assess Fat Mass in Infants and Young Children: A Comparative Study Using Skinfold Thickness and Air-Displacement Plethysmography

Life ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 75
Author(s):  
Stefanie M. P. Kouwenhoven ◽  
Nadja Antl ◽  
Jos W. R. Twisk ◽  
Berthold V. Koletzko ◽  
Martijn J. J. Finken ◽  
...  
Keyword(s):  
Young Children ◽  
Fat Mass ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Correlation Coefficients ◽  
Skinfold Thickness ◽  
Limited Information ◽  
Air Displacement Plethysmography ◽  
Mixed Model Analysis ◽  
Infants And Young Children

Background: Traditionally, fat mass is estimated using anthropometric models. Air-displacement plethysmography (ADP) is a relatively new technique for determining fat mass. There is limited information on the agreement between these methods in infants and young children. Therefore we aimed to longitudinally compare fat mass percentage values predicted from skinfold thicknesses (SFTs) and ADP in healthy infants and young children. Methods: Anthropometry and body composition were determined at the ages of 1, 4, and 6 months and 2 years. We quantified the agreement between the two methods using the Bland–Altman procedure, linear mixed-model analysis, and intra-class correlation coefficients (ICC). Results: During the first 6 months of life, fat mass% predicted with SFT was significantly different from that measured with ADP in healthy, term-born infants (n = 245). ICCs ranged from 0.33 (at 2 years of age) and 0.47 (at 4 months of age). Although the mean difference (bias) between the methods was low, the Bland–Altman plots showed proportional differences at all ages with wide limits of agreement. Conclusions: There is poor agreement between ADP and SFTs for estimating fat mass in infancy or early childhood. The amount of body fat was found to influence the agreement between the methods.

Factors influencing the occurrence of high ultimate pH in three muscles of lamb carcasses in Australia

2014 ◽  
Vol 54 (10) ◽  
pp. 1853 ◽  
Author(s):  
N. G. McPhail ◽  
J. L. Stark ◽  
A. J. Ball ◽  
R. D. Warner
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Rectus Femoris ◽  
Carcass Weight ◽  
Mixed Model Analysis ◽  
Factors Influencing ◽  
South Wales ◽  
Generalised Linear Mixed Model ◽  
Processing Plants ◽  
Few Data

Chilled lamb meat exported from Australia has, on occasions, been rejected by importing countries due to greening, after only 6 weeks of storage time. Greening is known to be more prevalent in high ultimate pH (pHu) beef meat (>5.9). There are few data available for lamb carcasses in Australia on the occurrence of high pHu meat, which may have an impact on the understanding and control of quality and greening during storage. The aim of this project was to determine the prevalence of, and influencing factors for, high pHu meat in a range of muscle types in lamb carcasses in Australia. Muscle pHu data were collected from a total of 1614 carcasses from 78 lots at four lamb processing plants in Victoria and New South Wales in autumn and spring of 2013. The pHu of the knuckle (rectus femoris), rack (longissimus) and blade (infraspinatus) was measured and data on carcass and lot characteristics were recorded. Data were subjected to restricted maximum likelihood and generalised linear mixed model analysis. The mean pHu of the knuckle, rack and shoulder were 6.06, 5.79 and 6.12 respectively, and the main factors influencing muscle pHu and occurrence of dark-cutting were breed, season, electrical stimulation and carcass weight. Merino lambs had a higher pHu in the blade and knuckle than did other breeds (P < 0.05, P < 0.01 respectively). Lambs processed in autumn had a higher predicted pHu in the blade and knuckle and a higher percentage dark-cutting (DC; pHu >6.0) for those muscles, than did those processed in spring (P < 0.05). Carcasses that had been electrically stimulated had a higher %DC and a higher pHu in all three muscles (P < 0.05). Carcass weight had a significant effect on the pHu of all three muscles (P < 0.001), with heavier carcasses having a lower pHu and lower %DC. The pHu of the rack was not a reliable predictor for the pHu in other muscles of the lamb carcass. In conclusion, the high occurrence of DC in the muscles, particularly the blade and knuckle, suggests that these muscles may be at risk for producing greening in the vacuum bag during storage.

Size-related boldness is not altered by stomach flushing in a terrestrial salamander

2021 ◽  
pp. 1-6
Author(s):  
Sebastiano Salvidio ◽  
Andrea Costa ◽  
Fabrizio Oneto
Keyword(s):  
Body Condition ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Animal Personality ◽  
Model Analysis ◽  
Mixed Model Analysis ◽  
Linear Mixed Model Analysis ◽  
Before And After ◽  
Trophic Strategy ◽  
The Relationship

Abstract Animal personality is a relatively neglected field in amphibian research. In this study we assessed the influence of stomach flushing, a non-lethal technique used in amphibian dietary studies, on the boldness behaviour of the cave salamander Speleomantes strinatii. The time of emergence from a shelter located in an unfamiliar environment (a proxy for individual boldness) was measured in 26 cave salamanders before and after stomach flushing, while 14 non-flushed salamanders were tested as controls. Boldness was a repeatable behaviour for salamanders and larger individuals emerged from their shelter more rapidly than smaller ones. Linear mixed model analysis showed that flushing, sex and body condition had no effect on this behaviour. These findings are promising in the framework of the study of salamander personality. In particular, our results will be useful when exploring the relationship between individual trophic strategy and boldness, aggression or exploration behaviours in terrestrial salamanders.

scholarly journals Maximin Efficiencies under Treatment-Dependent Costs and Outcome Variances for Parallel, AA/BB, and AB/BA Designs

2018 ◽  
Vol 2018 ◽  
pp. 1-15
Author(s):  
Math J. J. M. Candel
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Optimal Allocation ◽  
Power Level ◽  
Equal Treatment ◽  
Small Samples ◽  
Asymptotic Results ◽  
Crossover Designs ◽  
Mixed Model Analysis ◽  
Intraclass Correlations

If there are no carryover effects, AB/BA crossover designs are more efficient than parallel (A/B) and extended parallel (AA/BB) group designs. This study extends these results in that (a) optimal instead of equal treatment allocation is examined, (b) allowance for treatment-dependent outcome variances is made, and (c) next to treatment effects, also treatment by period interaction effects are examined. Starting from a linear mixed model analysis, the optimal allocation requires knowledge on intraclass correlations in A and B, which typically is rather vague. To solve this, maximin versions of the designs are derived, which guarantee a power level across plausible ranges of the intraclass correlations at the lowest research costs. For the treatment effect, an extensive numerical evaluation shows that if the treatment costs of A and B are equal, or if the sum of the costs of one treatment and measurement per person is less than the remaining subject-specific costs (e.g., recruitment costs), the maximin crossover design is most efficient for ranges of intraclass correlations starting at 0.15 or higher. For other cost scenarios, the maximin parallel or extended parallel design can also become most efficient. For the treatment by period interaction, the maximin AA/BB design can be proven to be the most efficient. A simulation study supports these asymptotic results for small samples.

scholarly journals GWAS-Flow: A GPU accelerated framework for efficient permutation based genome-wide association studies

2019 ◽  
Author(s):  
Jan A. Freudenthal ◽  
Markus J. Ankenbrand ◽  
Dominik G. Grimm ◽  
Arthur Korte
Keyword(s):  
Complex Traits ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Association Studies ◽  
Large Datasets ◽  
Genome Wide Association ◽  
Small Data ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Non Gaussian

AbstractMotivationGenome-wide association studies (GWAS) are one of the most commonly used methods to detect associations between complex traits and genomic polymorphisms. As both genotyping and phenotyping of large populations has become easier, typical modern GWAS have to cope with massive amounts of data. Thus, the computational demand for these analyses grew remarkably during the last decades. This is especially true, if one wants to implement permutation-based significance thresholds, instead of using the naïve Bonferroni threshold. Permutation-based methods have the advantage to provide an adjusted multiple hypothesis correction threshold that takes the underlying phenotypic distribution into account and will thus remove the need to find the correct transformation for non Gaussian phenotypes. To enable efficient analyses of large datasets and the possibility to compute permutation-based significance thresholds, we used the machine learning framework TensorFlow to develop a linear mixed model (GWAS-Flow) that can make use of the available CPU or GPU infrastructure to decrease the time of the analyses especially for large datasets.ResultsWe were able to show that our application GWAS-Flow outperforms custom GWAS scripts in terms of speed without loosing accuracy. Apart from p-values, GWAS-Flow also computes summary statistics, such as the effect size and its standard error for each individual marker. The CPU-based version is the default choice for small data, while the GPU-based version of GWAS-Flow is especially suited for the analyses of big data.AvailabilityGWAS-Flow is freely available on GitHub (https://github.com/Joyvalley/GWAS_Flow) and is released under the terms of the MIT-License.

scholarly journals Which Test of Divergent Thinking Is Best?

2016 ◽  
Vol 3 (1) ◽  
pp. 4-18 ◽  
Author(s):  
Mark A. Runco ◽  
Ahmed M. Abdulla ◽  
Sue Hyeon Paek ◽  
Fatima A. Al-Jasim ◽  
Hanadi N. Alsuwaidi
Keyword(s):  
Divergent Thinking ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Mixed Model Analysis ◽  
Demographic Questionnaire ◽  
Problem Generation ◽  
Behavior Scale ◽  
Realistic Problem ◽  
Post Hoc ◽  
Better Than

AbstractDivergent thinking (DT) tests are probably the most commonly used measures of creative potential. Several extensive batteries are available but most research relies on one or two specific tests rather than a complete battery. This may limit generalizations because tests of DT are not equivalent. They are not always highly inter-correlated. Additionally, some DT tests appear to be better than others at eliciting originality. This is critical because originality is vital for creativity. The primary purpose of the present study was to determine which test of DT elicits the most originality. Seven measures of DTwere administered on a sample of 611 participants in eight Arabic countries. The tests were Figural, Titles, Realistic Presented Problems, Realistic Problem Generation, Instances, Uses, and Similarities. The Quick Test of Convergent Thinking, Runco’s Ideational Behavior Scale, and a demographic questionnaire were also administered. A linear mixed model analysis confirmed that the originality scores in the DT tests differed by test. Post-hoc tests indicated that the Titles and Realistic Problem Generation tests produced the highest mean originality scores, whereas the Realistic Presented Problems test produced the lowest mean originality scores. These differences confirm that research using only one DT test will not provide generalizable results.

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