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Dimensionality of genomic information and its impact on genome-wide associations and variant selection for genomic prediction: a simulation study.
Genet Sel Evol
July 2023
Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA.
Background: Identifying true positive variants in genome-wide associations (GWA) depends on several factors, including the number of genotyped individuals. The limited dimensionality of genomic information may give insights into the optimal number of individuals to be used in GWA. This study investigated different discovery set sizes based on the number of largest eigenvalues explaining a certain proportion of variance in the genomic relationship matrix (G).
View Article and Find Full Text PDFGenetic diversity of European maize landraces: Dataset on the molecular and phenotypic variation of derived doubled-haploid populations.
Data Brief
June 2022
Plant Breeding, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.
Genetic variation is the basis of selection, evolution and breeding. Maize landraces represent a rich source of allelic diversity, but their efficient utilization in breeding and research has been hampered by their heterogeneous and heterozygous nature and insufficient information about most accessions. While molecular inventories of germplasm repositories are growing steadily, linking these data to meaningful phenotypes for quantitative traits is challenging.
View Article and Find Full Text PDFGenomic prediction in a numerically small breed population using prioritized genetic markers from whole-genome sequence data.
J Anim Breed Genet
January 2022
School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia.
The objective of this study was to investigate the accuracy of genomic prediction of body weight and eating quality traits in a numerically small sheep population (Dorper sheep). Prediction was based on a large multi-breed/admixed reference population and using (a) 50k or 500k single nucleotide polymorphism (SNP) genotypes, (b) imputed whole-genome sequencing data (~31 million), (c) selected SNPs from whole genome sequence data and (d) 50k SNP genotypes plus selected SNPs from whole-genome sequence data. Furthermore, the impact of using a breed-adjusted genomic relationship matrix on accuracy of genomic breeding value was assessed.
View Article and Find Full Text PDFQatari Genotype May Contribute to Complications in Type 2 Diabetes.
J Diabetes Res
June 2021
Diabetes Research Center (DRC), Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Doha, Qatar.
Objective: There is increasing evidence of a strong genetic component in type 2 diabetes (T2DM) that may contribute to diabetes complications. Given the high prevalence of diabetes with its associated complications in the Middle East, we sought to determine if the genotype within a Middle East population may be contributory. Therefore, three genotype-based Qatari ancestral groups, Q1 Arab Bedouin, Q2 Asian/Persian, and Q3 sub-Saharan African, with a fourth admixed group were correlated with T2DM prevalence and its complications to determine if they differed between the 4 Qatari ancestries, particularly for the SLMAP allele-associated diabetic retinopathy.
View Article and Find Full Text PDFA greedy feature selection algorithm for Big Data of high dimensionality.
Mach Learn
August 2018
1Computer Science Department, University of Crete, Heraklion, Greece.
We present the (PFBP) algorithm for (FS) for Big Data of high dimensionality. PFBP partitions the data matrix both in terms of rows as well as columns. By employing the concepts of -values of conditional independence tests and meta-analysis techniques, PFBP relies only on computations local to a partition while minimizing communication costs, thus massively parallelizing computations.
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