Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes

2016 ◽  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Randomized Clinical Trials ◽  
Partial Least Square ◽  
Least Square ◽  
Complex Phenotypes ◽  
Genes And Environment ◽  
Polygenic Scores ◽  
Research Designs ◽  
Statistical Approaches

Findings from the Human Genome Project and from Genome-Wide Association (GWA) studies indicate that many diseases and traits manifest a more complex genomic pattern than previously assumed. These findings, and advances in high-throughput sequencing, suggest that there are many sources of influence—genetic, epigenetic, and environmental. This volume investigates the role of the interactions of genes and environment (G × E) in diseases and traits (referred to by the contributors as complex phenotypes) including depression, diabetes, obesity, and substance use.  The contributors first present different statistical approaches or strategies to address G × E and G × G interactions with high-throughput sequenced data, including two-stage procedures to identify G × E and G × G interactions, marker-set approaches to assessing interactions at the gene level, and the use of a partial-least square (PLS) approach. The contributors then turn to specific complex phenotypes, research designs, or combined methods that may advance the study of G × E interactions, considering such topics as randomized clinical trials in obesity research, longitudinal research designs and statistical models, and the development of polygenic scores to investigate G × E interactions. Contributors Fatima Umber Ahmed, Yin-Hsiu Chen, James Y. Dai, Caroline Y. Doyle, Zihuai He, Li Hsu, Shuo Jiao, Erin Loraine Kinnally, Yi-An Ko, Charles Kooperberg, Seunggeun Lee, Arnab Maity, Jeanne M. McCaffery, Bhramar Mukherjee, Sung Kyun Park, Duncan C. Thomas, Alexandre Todorov, Jung-Ying Tzeng, Tao Wang, Michael Windle, Min Zhang

scholarly journals Hyperspectral Shortwave Infrared Image Analysis for Detection of Adulterants in Almond Powder with One-Class Classification Method

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5855
Author(s):  
Mohammad Akbar Faqeerzada ◽  
Santosh Lohumi ◽  
Geonwoo Kim ◽  
Rahul Joshi ◽  
Hoonsoo Lee ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Analytical Techniques ◽  
Error Rates ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Analysis Model ◽  
One Class Classifier ◽  
Shortwave Infrared

The widely used techniques for analyzing the quality of powdered food products focus on targeted detection with a low-throughput screening of samples. Owing to potentially significant health threats and large-scale adulterations, food regulatory agencies and industries require rapid and non-destructive analytical techniques for the detection of unexpected compounds present in products. Accordingly, shortwave-infrared hyperspectral imaging (SWIR-HSI) for high throughput authenticity analysis of almond powder was investigated in this study. Two different varieties of almond powder, adulterated with apricot and peanut powder at different concentrations, were imaged using the SWIR-HSI system. A one-class classifier technique, known as data-driven soft independent modeling of class analogy (DD-SIMCA), was used on collected data sets of pure and adulterated samples. A partial least square regression (PLSR) model was further developed to predict adulterant concentrations in almond powder. Classification results from DD-SIMCA yielded 100% sensitivity and 89–100% specificity for different validation sets of adulterated samples. The results obtained from the PLSR analysis yielded a high determination coefficient (R2) and low error values (<1%) for each variety of almond powder adulterated with apricot; however, a relatively higher error rates of 2.5% and 4.4% for the two varieties of almond powder adulterated with peanut powder, which indicates the performance of quantitative analysis model could vary with sample condition, such as variety, originality, etc. PLSR-based concentration mapped images visually characterized the adulterant (apricot) concentration in the almond powder. These results demonstrate that the SWIR-HSI technique combined with the one-class classifier DD-SIMCA can be used effectively for a high-throughput quality screening of almond powder regarding potential adulteration.

scholarly journals Correlation: Between Autochthonous Microbial Diversity and Volatile Metabolites During the Fermentation of Nongxiang Daqu

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuke Deng ◽  
Dan Huang ◽  
Baolin Han ◽  
Xinqian Ning ◽  
Dong Yu ◽  
...  
Keyword(s):  
Microbial Diversity ◽  
High Throughput Sequencing ◽  
Vital Role ◽  
Partial Least Square ◽  
Least Square ◽  
Gas Chromatography Mass Spectrometry ◽  
Volatile Flavor Compounds ◽  
Volatile Metabolites ◽  
Partial Least Square Analysis ◽  
Volatile Flavor

Daqu is an important saccharifying and fermenting agent. It provides various microorganisms and enzymes for the fermentation of Baijiu and plays a vital role in the formation of Baijiu flavor. However, it is difficult to obtain information on microbial growth and metabolism in time for Daqu production. Therefore, the “Qu Xiang” obtained by smelling is an important index in the traditional production process to evaluate the microbial fermentation in the process of Daqu-making, “Qu Xiang” mainly represents the volatile flavor compounds in Daqu. The microbial diversity and volatile metabolites on 0, 6, 16, and 29 days of the fermentation process were measured using high-throughput sequencing and gas chromatography–mass spectrometry. Significant differences were found in the composition of the microbial community. Pseudomonas, Weissella, Bacillus, and Pelomonas were the main bacterial genera. Alternaria, Rhizopus, and Pichia are the main fungal genera. A total of 32 differential volatile metabolites were detected in samples at four time points using differential metabolic analysis. The correspondence of prevailing microorganisms with differential metabolites distinguished by Spearman correlation and two-way orthogonal partial least square analysis show that Saccharopolyspora exhibited a significant connection for the 12 differential metabolites. A significant positive correlation was observed between Rhizomucor and 13 different metabolites. These findings further understanding of the metabolism of microorganisms in Daqu fermentation and also help to control the microorganisms in the Daqu-making process, to obtain more stable Baijiu products.

scholarly journals HS-SPME-MS-Enose Coupled with Chemometrics as an Analytical Decision Maker to Predict In-Cup Coffee Sensory Quality in Routine Controls: Possibilities and Limits

Molecules ◽  
2019 ◽  
Vol 24 (24) ◽  
pp. 4515 ◽  
Author(s):  
Erica Liberto ◽  
Davide Bressanello ◽  
Giulia Strocchi ◽  
Chiara Cordero ◽  
Manuela Rosanna Ruosi ◽  
...  
Keyword(s):  
Decision Maker ◽  
High Throughput ◽  
Sensory Quality ◽  
Solid Phase ◽  
Screening Method ◽  
Partial Least Square ◽  
Least Square ◽  
Raw Material ◽  
Test Set ◽  
Sensory Score

The quality assessment of the green coffee that you will go to buy cannot be disregarded from a sensory evaluation, although this practice is time consuming and requires a trained professional panel. This study aims to investigate both the potential and the limits of the direct headspace solid phase microextraction, mass spectrometry electronic nose technique (HS-SPME-MS or MS-EN) combined with chemometrics for use as an objective, diagnostic and high-throughput technique to be used as an analytical decision maker to predict the in-cup coffee sensory quality of incoming raw beans. The challenge of this study lies in the ability of the analytical approach to predict the sensory qualities of very different coffee types, as is usual in industry for the qualification and selection of incoming coffees. Coffees have been analysed using HS-SPME-MS and sensory analyses. The mass spectral fingerprints (MS-EN data) obtained were elaborated using: (i) unsupervised principal component analysis (PCA); (ii) supervised partial least square discriminant analysis (PLS-DA) to select the ions that are most related to the sensory notes investigated; and (iii) cross-validated partial least square regression (PLS), to predict the sensory attribute in new samples. The regression models were built with a training set of 150 coffee samples and an external test set of 34. The most reliable results were obtained with acid, bitter, spicy and aromatic intensity attributes. The mean error in the sensory-score predictions on the test set with the available data always fell within a limit of ±2. The results show that the combination of HS-SPME-MS fingerprints and chemometrics is an effective approach that can be used as a Total Analysis System (TAS) for the high-throughput definition of in-cup coffee sensory quality. Limitations in the method are found in the compromises that are accepted when applying a screening method, as opposed to human evaluation, in the sensory assessment of incoming raw material. The cost-benefit relationship of this and other screening instrumental approaches must be considered and weighed against the advantages of the potency of human response which could thus be better exploited in modulating blends for sensory experiences outside routine.

MOTIVASI MEMEDIASI PENGARUH PELATIHAN DAN LINGKUNGAN KERJA TERHADAP KINERJA KARYAWAN PT. TELKOM WITEL YOGYAKARTA

2020 ◽  
Vol 28 (1) ◽  
pp. 71-88
Author(s):  
Tyas Tunjung Sari ◽  
Pandu Nuansa Luhur
Keyword(s):  
Work Environment ◽  
Significant Influence ◽  
Structural Equation ◽  
Employee Performance ◽  
Partial Least Square ◽  
Least Square ◽  
Primary Data ◽  
Version 2.0 ◽  
Analyze Data

This study aims to determine the motivation of work to mediate the effect of training and work environment on employee performance at PT. Telkom Witel Yogyakarta Yogyakarta. The purpose of this study is to determine and analyze 1) the effect of training on employee performance at PT. Telkom Witel Yogyakarta 2) the effect of training on employee performance through motivation at PT. Telkom Witel Yogyakarta 3) the influence of the work environment on employee performance at PT. Telkom Witel Yogyakarta 4) the influence of the work environment on employee performance through motivation at PT. Telkom Witel Yogyakarta. This study uses primary data through research on 62 respondents. Structural Equation is used to analyze data, using PLS (Partial Least Square) version 2.0. The results of this study indicate that there are 1) positive and significant influence of training on employee performance 2) positive and significant influence of work environment on employee performance 3) positive and significant effect of training on employee performance through motivation 4) positive and significant influence of work environment on employee performance through motivation.

Locus Of Control Sebagai Varibel Moderasi Hubungan Kompleksitas Tugas Dan Kinerja Auiditor

2018 ◽  
Vol 16 (2) ◽  
pp. 113
Author(s):  
Sri Hastuti ◽  
Siti Sundari
Keyword(s):  
Locus Of Control ◽  
Big Five ◽  
Partial Least Square ◽  
Least Square

Research Objectives to prove the influence of the complexity of the tasks faced by the Auditor on performance in carrying out duties as an Auditor. The complexity of tasks related to various problems in the company requires locus of control from internal and external to maintain independence and competence.The first auditor performance case occurred in 2002 with the disclosure of the Enron case involving the KAP in the big five, Athur Anderson. In 2008 the Telkom case affected the closure of KAP Edy Priyanto, and there were still many other cases which were violations of the accountant's code of ethics.This research is in the form of quantitative, with proof of the complexity of the task and locus of control on the performance of the auditor. Sample 46 Junior auditors from several KAPs in Surabaya, using the Partial Least Square test, the result that the complexity of the task affects the performance of the Auditor and the interaction of the complexity of the task with locus of control does not affect the performance of the Auditor.

ANALYSIS THE IMPACT OF THE IMPLEMENTATION OF QUALITY MANAGEMENT SYSTEM (QMS) AND SAFETY AND HEALTHY AT WORK MANAGEMENT SYSTEM (SHWMS / SMK3) ON THE JOB PERFORMANCE OF EMPLOYEES

2018 ◽  
Vol 3 (01) ◽  
pp. 45
Author(s):  
Nur Hidayat ◽  
Indah Kusuma Hayati
Keyword(s):  
Quality Management ◽  
Job Performance ◽  
Latent Variables ◽  
Management System ◽  
Quality Management System ◽  
Partial Least Square ◽  
Least Square ◽  
Global Challenges ◽  
The Impact ◽  
Work Management

Recently, the evolvement of globalization era has been the global challenges that cannot be avoided either by private or government sectors, and they are requested to be survived encountering such the condition. The implementation of Quality Management System (QMS) in the operational company is the way how to guarantee the quality of products or services offered to the people. One of the purposes of QMS implementation is to provide a prime satisfaction to the customers. The impact of QMS implementation is expected to increase job performance of the employees. Besides the implementation of Quality Management System (QMS), the impact of global challenges has been increasing the competitive efforts to execute more effective production process. However, it has required manpower protection accordingly. This research aims to find out whether the implementation of quality management system and safety and healthy at work management system have impacted on the job performance of employees. Objects of this research are the employees in the production department at PT Guna Senaputra Sejahtera Plant 1 Bogor. Data analysis technique of this research has applied software Smart PLS (Partial Least Square). PLS has estimated a model of correlation among the latent variables and correlation between latent variables and its indicators. Result of data processing has indicated that the implementation of Quality Management System (QMS) and system of safety and healthy at work have positively and significantly impacted job performance of employees.Keywords : Quality Management System (QMS), Safety and Healthy at Work System ( SHWS / SMK3), and Job Performance of Employees

A Consuequence of Statisfaction and Loyalty: How Brand nd Purchase Intention Affect Its (An empirical study of Bengkulu)

2020 ◽  
Vol 7 (2) ◽  
pp. 61-70
Author(s):  
Fachri Eka Saputra ◽  
Fedyah Anggriani
Keyword(s):  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Purchase Intention ◽  
Partial Least Square ◽  
Least Square ◽  
Primary Data ◽  
Price Fairness ◽  
Online Questionnaire ◽  
Positive Effect ◽  
Descriptive Method

The purpose of this study as to determine how the effect of waterpark image and price fairness on customer satisfaction and its implications for customer loyalty at Waterpark Wahana Surya Bengkulu. The measurement of this study uses 14 indicator items which are distributed using an online questionnaire. The number of samples in this study were 136 respondents and the data were analyzed using SEM PLS (Partial Least Square). Date were collected using a questionnaire using a Likert scale. This research used descriptive method with a quantitative approach. The type of data used in this study is primary data. The results of this study prove that 1. waterpark image has a positive effect on price fairness, 2. Waterpark image has a positive effect on customer satisfaction, 3. Fairness of price has a positive effect on customer satisfaction, 4. Waterpark image has a positive effect on customer loyalty, 5. Fairness of price has a positive effect on customer loyalty, 6. Customer satisfaction has no effect on customer loyalty.

Factors Influencing Green Purchase Behavior among Young Consumers in Saudi Arabia

2020 ◽  
Vol 8 (1) ◽  
pp. 51-73
Author(s):  
Abdulalem Mohammed ◽  
Abdo Homaid ◽  
Wail Alaswadi
Keyword(s):  
Saudi Arabia ◽  
Peer Pressure ◽  
Partial Least Square ◽  
Least Square ◽  
Purchase Behavior ◽  
Self Identity ◽  
Factors Influencing ◽  
Purchasing Intention ◽  
Young Consumers ◽  
Green Purchasing

For environmental and business reasons, understanding the consumer behaviour of the young towards green products is very important. Therefore, the main purpose of this study is to investigate the factors influencing green product buying intention and behaviour among young consumers in Saudi Arabia. The study has developed a set of hypotheses utilising the theory of planned behaviour (TPB) as a guiding principle. They were tested based on data collected from 257 individuals through the use of the Partial Least Square (PLS) method. The findings showed that a culture of collectivism was the best way to predict the green purchasing intentions of young Saudis, followed by a willingness to pay, environmental self-identity and peer pressure. Additionally, purchasing intention is a major factor influencing actual green purchasing behaviour.

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