Large-scale genotyping of SNPs has shown a great promise in identifying markers that could be linked to diseases. One of the major obstacles involved in performing these studies is that the underlying population substructure could produce spurious associations. Population substructure can be caused by the presence of two distinct subpopulations or a single pool of admixed individuals. In this work, we focus on the latter, which is significantly harder to detect in practice. New advances in this research direction are expected to play a key role in identifying loci that are different among different populations and are still associated with a disease. We evaluated current methods for inference of population substructure in such cases and show that they might be quite inaccurate even in relatively simple scenarios. We therefore introduce a new method, LAMP (Local Ancestry in adMixed Populations), which infers the ancestry of each individual at every single-nucleotide polymorphism (SNP). LAMP computes the ancestry structure for overlapping windows of contiguous SNPs and combines the results with a majority vote. Our empirical results show that LAMP is significantly more accurate and more efficient than existing methods for inferring locus-specific ancestries, enabling it to handle large-scale datasets. We further show that LAMP can be used to estimate the individual admixture of each individual. Our experimental evaluation indicates that this extension yields a considerably more accurate estimate of individual admixture than state-of-the-art methods such as STRUCTURE or EIGENSTRAT, which are frequently used for the correction of population stratification in association studies.
Different species, populations and individuals vary considerably in the copy number of discrete segments of their genomes. The manner and frequency with which these genetic differences arise over generational time is not well understood. Taking advantage of divergence among lineages sharing a recent common ancestry, we have conducted a genome-wide analysis of spontaneous copy number variation (CNV) in the laboratory mouse. We used high-resolution microarrays to identify 38 CNVs among 14 colonies of the C57BL/6 strain spanning approximately 967 generations of inbreeding, and we examined these loci in 12 additional strains. It is clear from our results that many CNVs arise through a highly nonrandom process: 18 of 38 were the product of recurrent mutation, and rates of change varied roughly four orders of magnitude across different loci. Recurrent CNVs are found throughout the genome, affect 43 genes and fluctuate in copy number over mere hundreds of generations, observations that raise questions about their contribution to natural variation.
transfer in the liquid, then the increased crystal growth rate Ishii: Iron Steel Inst.
The confocal laser scanning microscope (CLSM) allows crystallization behavior in liquid slags to be observed in situ at high temperatures. Slags in the lime-silica-alumina-magnesia system are easily under cooled and it is possible to construct time temperature transformation (TTT) diagrams for this system. The presence of solid alumina particles in these liquid slags was studied to determine if these particles act as heterogeneous nucleation sites that cause the precipitation of solid material within slags. The introduction of alumina particles reduced the incubation time for the onset of crystallization and increased the temperature at which crystallization was observed in the slags to close to the liquidus temperature for the slag. Crystal growth rates are in a good agreement with Ivantsov's solution of the problem of diffusion controlled dendritic growth. Alumina appears to be a potent nucleating agent in the slag systems that were studied.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.