• Title/Summary/Keyword: Genetic test

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Clinical application of prenatal chromosomal microarray

  • Chang Ahn Seol
    • Journal of Genetic Medicine
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    • v.19 no.2
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    • pp.43-48
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    • 2022
  • A prenatal chromosomal microarray (CMA) is generally recommended when a major anomaly is suspected on prenatal ultrasonography. As it can overcome the limitations of conventional karyotyping, it is expected that the number of prenatal CMA test requests will gradually increase. However, given the specificity of prenatal diagnosis, there are practical considerations compared to postnatal testing, such as the validation of prenatal specimens, maternal cell contamination, precautions when reporting variants of uncertain significance, and the need for comprehensive genetic counseling considering secondary findings. The purpose of this article is to provide necessary information to health care providers in consideration of these issues and to provide appropriate genetic counseling to patients.

Estimation of Genetic Parameters from Longitudinal Records of Body Weight of Berkshire Pigs

  • Lee, Dong-Hee;Do, Chang-Hee
    • Asian-Australasian Journal of Animal Sciences
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    • v.25 no.6
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    • pp.764-771
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    • 2012
  • Direct and maternal genetic heritabilities and their correlations with body weight at 5 stages in the life span of purebred Berkshire pigs, from birth to harvest, were estimated to scrutinize body weight development with the records for 5,088 purebred Berkshire pigs in a Korean farm, using the REML based on an animal model. Body weights were measured at birth (Birth), at weaning (Weaning: mean 22.9 d), at the beginning of a performance test (On: mean 72.7 d), at the end of a performance test (Off: mean 152.4 d), and at harvest (Finish: mean 174.3 d). Ordinary polynomials and Legendre with order 1, 2, and 3 were adopted to adjust body weight with age in the multivariate animal models. Legendre with order 3 fitted best concerning prediction error deviation (PED) and yielded the lowest AIC for multivariate analysis of longitudinal body weights. Direct genetic correlations between body weight at Birth and body weight at Weaning, On, Off, and Finish were 0.48, 0.36, 0.10, and 0.10, respectively. The estimated maternal genetic correlations of body weight at Finish with body weight at Birth, Weaning, On, and Off were 0.39, 0.49, 0.65, and 0.90, respectively. Direct genetic heritabilities progressively increased from birth to harvest and were 0.09, 0.11, 0.20, 0.31, and 0.43 for body weight at Birth, Weaning, On, Off, and Finish, respectively. Maternal genetic heritabilities generally decreased and were 0.26, 0.34, 0.15, 0.10, and 0.10 for body weight at Birth, Weaning, On, Off, and Finish, respectively. As pigs age, maternal genetic effects on growth are reduced and pigs begin to rely more on the expression of their own genes. Although maternal genetic effects on body weight may not be large, they are sustained through life.

Comparison of Trend Tests for Genetic Association on Censored Ages of Onset (미완결 발병연령에 근거한 연관성 추세 검정법의 비교)

  • Yoon, Hye-Kyoung;Song, Hae-Hiang
    • The Korean Journal of Applied Statistics
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    • v.21 no.6
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    • pp.933-945
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    • 2008
  • The genetic association test on age of onset trait aims to detect the putative gene by means of linear rank tests for a significant trend of onset distributions with genotypes. However, due to the selective sampling of recruiting subjects with ages less than a pre-specified limit, the genotype groups are subject to substantially different censored distributions and thus this is one reason for the low efficiencies in the linear rank tests. In testing the equality of two survival distributions, log-rank statistic is preferred to the Wilcoxon statistic, when censored observations are nonignorable. Therefore, for more then two groups, we propose a generalized log-rank test for trend as a genetic association test. Monte Carlo studies are conducted to investigate the performances of the test statistics examined in this paper.

An Adequacy Based Test Data Generation Technique Using Genetic Algorithms

  • Malhotra, Ruchika;Garg, Mohit
    • Journal of Information Processing Systems
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    • v.7 no.2
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    • pp.363-384
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    • 2011
  • As the complexity of software is increasing, generating an effective test data has become a necessity. This necessity has increased the demand for techniques that can generate test data effectively. This paper proposes a test data generation technique based on adequacy based testing criteria. Adequacy based testing criteria uses the concept of mutation analysis to check the adequacy of test data. In general, mutation analysis is applied after the test data is generated. But, in this work, we propose a technique that applies mutation analysis at the time of test data generation only, rather than applying it after the test data has been generated. This saves significant amount of time (required to generate adequate test cases) as compared to the latter case as the total time in the latter case is the sum of the time to generate test data and the time to apply mutation analysis to the generated test data. We also use genetic algorithms that explore the complete domain of the program to provide near-global optimum solution. In this paper, we first define and explain the proposed technique. Then we validate the proposed technique using ten real time programs. The proposed technique is compared with path testing technique (that use reliability based testing criteria) for these ten programs. The results show that the adequacy based proposed technique is better than the reliability based path testing technique and there is a significant reduce in number of generated test cases and time taken to generate test cases.

Statistical Algorithm in Genetic Linkage Based on Haplotypes (일배체형에 기초한 연쇄분석의 통계학적 알고리즘 연구)

  • Kim, Jin-Heum;Kang, Dae-Ryong;Lee, Yun-Kyung;Shin, Sun-Mi;Suh, Il;Nam, Chung-Mo
    • Journal of Preventive Medicine and Public Health
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    • v.37 no.4
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    • pp.366-372
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    • 2004
  • Objectives : This study was conducted to propose a new transmission/disequilibrium test(TDT) to test the linkage between genetic markers and disease-susceptibility genes based on haplotypes. Simulation studies were performed to compare the proposed method with that of Zhao et al. in terms of type I error probability and powers. Methods : We estimated the haplotype frequencies using the expectation-maximization(EM) algorithm with parents genotypes taken from a trio dataset, and then constructed a two-way contingency table containing estimated frequencies to all possible pairs of parents haplotypes. We proposed a score test based on differences between column marginals and their corresponding row marginals. The test also involved a covariance structure of marginal differences and their variances. In simulation, we considered a coalescent model with three genetic markers of biallele to investigate the performance of the proposed test under six different configurations. Results : The haplotype-based TDT statistics, our test and Zhao et al.'s test satisfied a type I error probability, but the TDT test based on single locus showed a conservative trend. As expected, the tests based on haplotypes also had better powers than those based on single locus. Our test and that of Zhao et al. were comparable in powers. Conclusion : We proposed a TDT statistic based on haplotypes and showed through simulations that our test was more powerful than the single locus-based test. We will extend our method to multiplex data with affected and/or unaffected sibling(s) or simplex data having only one parent s genotype.

Genetic and Environmental Trends for Milk Production Traits in Sheep Estimated with Test-day Model

  • Oravcova, Marta;Pesovicva, Dana
    • Asian-Australasian Journal of Animal Sciences
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    • v.21 no.8
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    • pp.1088-1096
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    • 2008
  • Data from milk performance testing were used to analyze genetic and environmental trends for purebred Tsigai, Improved Valachian and Lacaune sheep. 103,715 (Tsigai), 212,962 (Improved Valachian) and 2,196 (Lacaune) test-day records gathered by the State Breeding Institute of the Slovak Republic entered the analyses. The respective pedigree data comprised 23,724 (Tsigai), 51,401 (Improved Valachian) and 438 (Lacaune) records. The multiple-trait, mixed model methodology was used to predict the breeding values for daily milk yield, fat and protein content and to estimate the fixed and remaining random effects assumed to affect the above mentioned traits, separately for each breed. The breeding values for daily milk yield were adjusted for 150-day standardized lactation length by multiplying with the constant 150, as the breeding goal of the selection scheme in Slovakian sheep is to increase 150-day milk production and constant heritability throughout the whole lactation is assumed. The genetic trends were expressed as changes in averages of breeding values across birth years of animals. For Tsigai and Lacaune breeds, cumulative genetic changes over the analyzed period were 3.8 and 5.1 kg for 150-day milk, 0 and -0.16% for fat content and 0 and -0.12% for protein content. For Improved Valachian breed, either a low (1.6 kg for 150-day milk yield) or zero (fat and protein content) cumulative genetic change was found. The environmental trends were calculated as averages of solutions for flock-test day effect across years and months in which measurements were taken. A distinctive cyclical pattern which reflected short-time variation in milk production traits was found. Possible explanations for this phenomenon are given and discussed.

Estimation of genetic parameters for temperament in Jeju crossbred horses

  • Kim, Nam Young;Son, Jun Kyu;Cho, In Cheol;Shin, Sang Min;Park, Seol Hwa;Seong, Pil Nam;Woo, Jae Hoon;Park, Nam Geon;Park, Hee Bok
    • Asian-Australasian Journal of Animal Sciences
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    • v.31 no.8
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    • pp.1098-1102
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    • 2018
  • Objective: Temperament can be defined as a type of behavioral tendency that appears in a relatively stable manner in responses to various external stimuli over time. The aim of this study was to estimate genetic parameters for the records of temperament testing that are used to improve the temperament of Jeju crossbred (Jeju${\times}$Thoroughbred) horses. Methods: This study was conducted using 205 horses (101 females and 104 males) produced between 2010 and 2015. The experimental animals were imprinted and tamed according to the Manual for Horse Taming and Evaluation for Therapeutic Riding Horses and evaluated according to the categories for temperament testing (gentleness, patience, aggressiveness, sensitivity, and friendliness) between 15 months and 18 months of age. Each category was scored on a five-point linear scale. Genetic parameters for the test categories were analyzed using a multi-trait mixed model with repeated records. The ASReml program was used to analyze the data. Results: The heritability of gentleness, patience, aggressiveness, sensitivity and friendliness ranged from 0.08 to 0.53. The standard errors of estimated heritability ranged from 0.13 to 0.17. The test categories showed high genetic correlations with each other, ranging from 0.96 to 0.99 and high repeatability, ranging from 0.70 to 0.73. Conclusion: The results of this study showed that the test categories had moderate heritability and high genetic correlations, but additional studies may be necessary to use the results for the improvement programs of the temperament of Jeju crossbred horses.

Test-Generation-Based Fault Detection in Analog VLSI Circuits Using Neural Networks

  • Kalpana, Palanisamy;Gunavathi, Kandasamy
    • ETRI Journal
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    • v.31 no.2
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    • pp.209-214
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    • 2009
  • In this paper, we propose a novel test methodology for the detection of catastrophic and parametric faults present in analog very large scale integration circuits. An automatic test pattern generation algorithm is proposed to generate piece-wise linear (PWL) stimulus using wavelets and a genetic algorithm. The PWL stimulus generated by the test algorithm is used as a test stimulus to the circuit under test. Faults are injected to the circuit under test and the wavelet coefficients obtained from the output response of the circuit. These coefficients are used to train the neural network for fault detection. The proposed method is validated with two IEEE benchmark circuits, namely, an operational amplifier and a state variable filter. This method gives 100% fault coverage for both catastrophic and parametric faults in these circuits.

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Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle

  • Cho, C.I.;Alam, M.;Choi, T.J.;Choy, Y.H.;Choi, J.G.;Lee, S.S.;Cho, K.H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.29 no.5
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    • pp.607-614
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    • 2016
  • The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3-L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of $polynomials{\times}3$ types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea.

Genetic parameters of milk and lactation curve traits of dairy cattle from research farms in Thailand

  • Pangmao, Santi;Thomson, Peter C.;Khatkar, Mehar S.
    • Animal Bioscience
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    • v.35 no.10
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    • pp.1499-1511
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    • 2022
  • Objective: This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms. Methods: The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations. Results: The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period. Conclusion: Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.