Meta-analysis of genetic association studies is being increasingly used to assess phenotypic differences between genotype groups. When the underlying genetic model is assumed to be dominant or recessive, assessing the phenotype differences based on summary statistics, reported for individual studies in a meta-analysis, is a valid strategy. However, when the genetic model is additive, a similar strategy based on summary statistics will lead to biased results. This fact about the additive model is one of the things that we establish in this paper, using simulations. The main goal of this paper is to present an alternate strategy for the additive model based on simulating data for the individual studies. We show that the alternate strategy is far superior to the strategy based on summary statistics.
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http://dx.doi.org/10.1016/j.mgene.2018.02.004 | DOI Listing |
Anal Bioanal Chem
January 2025
Intercollege Graduate Degree Program in Plant Biology, Pennsylvania State University, University Park, PA, USA.
Species identification of botanical products is a crucial aspect of research and regulatory compliance; however, botanical classification can be difficult, especially for morphologically similar species with overlapping genetic and metabolomic markers, like those in the genus Ocimum. Untargeted LC-MS metabolomics coupled with multivariate predictive modeling provides a potential avenue for improving herbal identity investigations, but the current dearth of reference materials for many botanicals limits the applicability of these approaches. This study investigated the potential of using greenhouse-grown authentic Ocimum to build predictive models for classifying commercially available Ocimum products.
View Article and Find Full Text PDFIsotopes Environ Health Stud
January 2025
Research Institute of Biology, Yerevan State University, Yerevan, Republic of Armenia.
Plant test systems are a sensitive way to detect the genetic effects of various contaminants in environmental compartments: water, soil and sediments. Biotesting of the genotoxicity of soil samples with various activity concentrations of naturally occurring (Ra, Th, K) and artificial (Cs) radionuclides in soil, from the territory of the Aragats Massif (Armenia) was carried out with the application of the micronucleus (Trad-MСN) and stamen hair mutation (Trad-SHM) bioassays of (clone 02) model test-object in the soil - plant system. Undisturbed soil sampling was performed in the southern slopes of the Aragats Massif, from different altitudes (from 1000 to 3200 m above sea level).
View Article and Find Full Text PDFJ Vis Exp
January 2025
Department of Molecular Cellular and Developmental Biology, University of California, Santa Barbara; Neuroscience Research Institute, University of California, Santa Barbara.
The tardigrade Hypsibius exemplaris is an emerging model organism renowned for its ability to survive environmental extremes. To explore the molecular mechanisms and genetic basis of such extremotolerance, many studies rely on RNA-sequencing (RNA-seq), which can be performed on populations ranging from large cohorts to individual animals. Reverse transcription polymerase chain reaction (RT-PCR) and RNA interference (RNAi) are subsequently used to confirm RNA-seq findings and assess the genetic requirements for candidate genes, respectively.
View Article and Find Full Text PDFInt J Occup Saf Ergon
January 2025
Computer Science Department; Badji Mokhtar University, Algeria.
This study attempted to optimize the adaptive neuro-fuzzy inference system (ANFIS) using particle swarm optimization (PSO) and a genetic algorithm (GA) for calculating occupational risk. Numerous studies have shown that the ANFIS is a good approach for predicting engineering problems. However, it is not well investigated in the area of risk assessment.
View Article and Find Full Text PDFCPT Pharmacometrics Syst Pharmacol
January 2025
Pharmacokinetics Dynamics and Metabolism/Translational Medicine and Early Development, Sanofi R&D Montpellier, Montpellier, France.
A growing number of covariate modeling methods have been proposed in the field of popPK modeling, but limited information exists on how they all compare. The objective of this study was to perform a systematic review of all popPK covariate modeling methods, focusing on assessing the existing knowledge on their performances. For each method of each article included in this review, evaluation setting, performance metrics along with their associated values, and relative computational times were reported when available.
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