Yemen_Somali.Omni5
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00010001651 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:The three new samples (two from Yemen and one from Somalia) that carry a maternal lineage affiliated with the Malagasy motif were assayed for genome-wide SNP genotypes using the Illumina Human Omni5 Bead Chip (Illumina), which surveys 4,284,426 single nucleotide markers regularly spaced across the genome.
| EGAS00001003425 | EGA
Project description:Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis and public release of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with geographic distance from Africa, as expected under a serial founder effect for an out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected—including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas—the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations. Keywords: High Density SNP array
2008-02-05 | GSE10331 | GEO
Project description:We performed whole genome single nucleotide polymorphism (SNP) based analysis of all available Venezuelan equine encephalitis (VEE) virus antigenic complex genomes and developed a high resolution genome-wide SNP microarray. We used the SNP microarray to analyze a broad panel of VEEV isolates, found excellent concordance between array and sequence based genotypes for previously sequenced strains, and genotyped unsequenced strains.
2016-03-24 | GSE79530 | GEO
Project description:The Illumina SNP bead arrays were done for two metachronous tumors and the blood from a given patient. It was used to define copy number abnormalities in order to support subclonal population analysis in this patient.
2014-07-01 | GSE50666 | GEO
Project description:Fusarium head blight (FHB) incited by Fusarium graminearum Schwabe is a devastating disease of barley and other cereal crops worldwide. Fusarium head blight is associated with trichothecene mycotoxins such as deoxynivalenol (DON), where contaminated grains are unfit for malting or animal feed industries. While genetically resistant cultivars offer the best economic and environmentally responsible means to mitigate disease, parent lines with adequate resistance are limited in barley. Resistancebreeding based upon quantitative genetic gains has been slow to date, due to intensive labour requirements of disease nurseries. The development of high throughput genome-wide molecular markers, allow application in genomic prediction models. A diverse genomic panel consisting of 400 two-row spring barley lines was assembled to focus on Canadian barley breeding programs. The panel was evaluated for FHB and DON content in three environments and over two years. Moreover, it was genotyped using an Illumina Infinium HTS iSelect custom beadchip array of single nucleotide polymorphic molecular markers (50K SNP), where over 23K molecular markers were polymorphic. Genomic prediction has been successfully demonstrated for reducing FHB and DON content in cereals using various statistically-based models of different underlying assumptions. Herein, we have studied an alternative method basedon machine learning and compare it with a statistical approach. Two encoding techniques were utilized (categorical or Hardy-Weinberg frequencies), followed by selecting essential genomic markers for phenotype prediction. Subsequently, we applied a transformer-based deep learning algorithm to predict FHB and DON. Apart from the transformer method, we also implemented a Residual Fully Connected Neural Network (RFCNN). Pearson correlation coefficients were calculated to compare true vs. predicted outputs. Under most model scenarios, the use of all markers vs. selected markers marginally improved prediction performance except for RFCNN method for FHB (27.6%). Hardy-Weinberg encoding generally improved correlation for FHB (6.9%) and DON (9.6%) for transformer. This study suggests the potential of the transformer based method for genomic prediction of complex traits such as FHB or DON, having performed better or equally compared with existing machine learning and statistical method. To genomic prediction in barley for Fusarium head blight and deoxynivalenol content using a custom Illumina Infinium array (BarleySNP50-JHI) (www.illumina.com). Sample types included leaves from 400 barley genotypes mostly of Canadian origin. This series includes 400 genotypes assayed on an Illumina infinium HTS platform 50K BeadChip.
2022-01-05 | GSE188791 | GEO
Project description:This dataset contains PLINK processed (PED and MAP) genotype data, from 1000 samples from the UAE using the Illumina Omni5 Exome Bead Chip
| EGAD00010001886 | EGA
Project description:The identification of surrogate single nucleotide polymorphism (SNP) markers that can predict responses to preoperative chemoradiotherapy (CRT) in rectal cancer patients. Genome-wide association studies in clinical populations are theoretically capable of identifying markers that are capable of tumor regression after CRT. We used Affymetrix’s SNP Array 6.0 to detail genetic polymorphism of patient’s group showing differential responsiveness to preoperative CRT and profiled SNP biomarkers.
2012-12-31 | GSE35282 | GEO
Project description:Genetic factors contribute to the development of ischemic stroke but their identity remains largely unknown. We tested the association with ischemic stroke of 210 single nucleotide polymorphisms (SNPs) associated with pathways functionally related to stroke. We observed an association between the rs7956957 SNP in LRP1 and next performed microarrays analysis in healthy individuals to investigate possible associations of LRP genotypes with the expression of other genes. Twelve blood samples were obtained from twelve different healthy subjects carrying different genotypes for the rs7956957 SNP of the LRP1 gene (GG, CG or CC).
2010-11-17 | GSE25414 | GEO
Project description:DNA methylation markers in thyroid tumor We used Illumina HumanMethylation EPIC bead array containing over the 850,000 CpG sites in 34 thyroid normal and tumor samples to identify thyroid subtype-specfic DNA methylation markers.
2020-01-01 | GSE121377 | GEO
Project description:The identification of surrogate single nucleotide polymorphism (SNP) markers that can predict responses to preoperative chemoradiotherapy (CRT) in rectal cancer patients. Genome-wide association studies in clinical populations are theoretically capable of identifying markers that are capable of tumor regression after CRT. We used Affymetrix’s SNP Array 6.0 to detail genetic polymorphism of patient’s group showing differential responsiveness to preoperative CRT and profiled SNP biomarkers. The chemoradiosensitivity of tumor tissue from the initial cohort of 43 patients was assessed using clinical responses of tumor regression grade (TRG). TRG was clinically categorized as complete response (CR) as TRG 1, dominant response (ER or finally as DR) as TRG 1 and 2, and efficient response (RYN or finally as ER) as TRG 1, 2, and 3 (TRG grade from Mandard et al, 1994). Blood DNAs were prepared from each patients and hybridized to Affymetrix’s SNP Array 6.0. Genotypes were determined using the Affymetrix Genotyping Console software (version 2.1) based on the BRLMM-P algorithm. We used an ANOVA test to identify SNPs associated with quantitative TRG responses.
2012-12-31 | E-GEOD-35282 | biostudies-arrayexpress