3d3b8497-f8c9-46ae-b9e2-4fb21c4a53f2 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001005337 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Here we report an expression dataset of isolated neutrophils from 114 healthy individuals of Chinese ethnicity collected in Singapore.
2015-08-10 | GSE70044 | GEO
Project description:Here we report an expression dataset of isolated neutrophils from 114 healthy individuals of Chinese ethnicity collected in Singapore. A total of 114 individuals with no case control stratification.
2015-08-10 | E-GEOD-70044 | biostudies-arrayexpress
Project description:Genotyping of hundreds of healthy individuals with Kazakh ethnicity as a reference cohort for further genetic investigations
2024-10-04 | GSE199322 | GEO
Project description:LC-MS/MS data obtained from subglottic biopsies collected from 12 individuals with idiopathic subglottic stenosis, as well as 3 age-, sex-, and race/ethnicity-matched controls. All tissue donors were women of White race and non-Latino or Hispanic ethnicity. Sample preparation, mass spectrometry, and data analysis details are available in the published article.
2020-11-21 | MSV000086498 | MassIVE
Project description:Datasets used in the article "The admixture histories of Cabo Verde", by Romain Laurent et al. 2022 - doi pending
File name "eGAdeposit_233CaboVerde_GEOcoordFULL_FINAL_01062022.txt"
Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file
Column 2-3 corresponds to X-Y GPS coordinates of individual's interview location in Cabo Verde
Column 4-5 corresponds to X-Y GPS coordinates of individual's self-reported residence location at the time of the interview
Column 6-7 corresponds to X-Y GPS coordinates of individual's self-reported birth-place location
Column 8-9 corresponds to X-Y GPS coordinates of individual's self-reported paternal birth-place location
Column 10-11 corresponds to X-Y GPS coordinates of individual's self-reported maternal birth-place location
| EGAD00001008977 | EGA
Project description:(1) In clinical practice and biomedical research populations are often divided categorically into distinct racial and ethnic groups. In reality, these categories comprise diverse groups with highly heterogeneous histories, cultures, traditions, religions, as well as social and environmental exposures. While the factors captured by these categories contribute to clinical practice and biomedical research, the use of race/ethnicity is widely debated. As a response to this debate, genetic ancestry has been suggested as a complement or alternative to this categorization. However, few studies have examined the effect of genetic ancestry, racial/ethnic identity, and environmental exposures on biological processes. Herein, we examine the contribution of self-identification within ethnicity, genetic ancestry, and environmental exposures on epigenetic modification of DNA methylation, a phenomenon affected by both genetic and environmental factors. We typed over 450,000 variably methylated CpG sites in primary whole blood of 573 individuals of Mexican and Puerto Rican descent who also had high-density genotype data. We found that methylation levels at a large number of CpG sites were significantly associated with ethnicity even when adjusting for genetic ancestry. In addition, we found an enrichment of ethnicity-associated sites amongst loci previously associated with environmental and social exposures. Interestingly, one of the strongest associated sites is driven by the Duffy Null blood type variant, demonstrating a new function of the locus in lymphocytes. Overall, the methylation changes associated with race/ethnicity, driven by both genes and environment, highlight the importance of measuring and accounting for both self-identified race/ethnicity and genetic ancestry in clinical and biomedical studies and the benefits of studying diverse populations. (2) In epigenome-wide association studies (EWAS), different methylation profiles of distinct cell-types may lead to false discoveries. We introduce ReFACTor, a method based on principal component analysis (PCA) for the correction of cell-type heterogeneity in EWAS. ReFACTor does not require knowledge of the cell counts, and it obtains improved estimates of the cell-type composition, resulting in improved power and control for false positives in EWAS.
2016-02-29 | GSE77716 | GEO
Project description:Whole peripheral blood samples collected into Tempus tubes from 189 adult participants in the Center for Health Discovery and Well Being study of Emory University and Georgia Tech, in Midtown Atlanta. The sample is of mixed ethnicity, and is part of a survey of the impact of genetics and lifestyle on gene expression and clinical attributes. Sample annotations include gender, self-reported ethnicity, zipcode of current address, and percent body fat, as well as technical features of the study (Sentrix plate ID, date of hybridization, and RNA quality RIN score. 189 individuals in the Center for Health Discovery and Well Being study of Emory University and Georgia Tech, in Midtown Atlanta., 65 men and 124 women. The age of individulas were between 26 and 79 (mean 51). 140 Caucasian (CAU), 37 African American (AFR), 11 Asian (ASN), 1 American Indian (AMI).
2013-03-01 | E-GEOD-35846 | biostudies-arrayexpress
Project description:The influence of genetics on DNA methylation (DNAme) variation is well documented, yet confounding from population stratification is often unaccounted for in DNAme association studies. Existing approaches have been developed to address confounding by population stratification by directly using DNAme data, but have not been validated in additional human populations or tissues, such as the placenta. Results: To aid future placental DNAme studies in assessing population stratification, we developed an ethnicity classifier, PLANET (placental elastic net DNAme ethnicity classifier), on combined Infinium Human Methylation 450k BeadChip array (HM450k) data from placental samples. We used data from five North American cohorts from private and public repositories (n = 509) and show that PLANET can not only accurately predict (accuracy = 0.9379, kappa = 0.8227) major classes of self-reported ethnicity/race (African: n = 58, Asian: n = 53, Caucasian: n = 389), but can also produce probabilities that are highly correlated with genetic ancestry inferred from genome-wide SNP (>2.5 million SNP) and ancestry informative markers (n=50) data. We found that PLANET’s ethnicity classification relies on 1860 DNAme microarray sites, and over half of these were also linked to nearby genetic polymorphisms (n=955). Lastly, we found our placental-optimized method outperforms existing approaches in assessing population stratification in our placental samples from individuals of Asian, African, and Caucasian ethnicities. Conclusion: PLANET outperforms existing methods and heavily relies on the genetic signal present in DNAme microarray data. PLANET can be used to address population stratification in future placental DNAme association studies, and will be especially useful when ethnicity information is missing and genotyping markers are unavailable.
2020-10-14 | GSE128827 | GEO
Project description:(1) In clinical practice and biomedical research populations are often divided categorically into distinct racial and ethnic groups. In reality, these categories comprise diverse groups with highly heterogeneous histories, cultures, traditions, religions, as well as social and environmental exposures. While the factors captured by these categories contribute to clinical practice and biomedical research, the use of race/ethnicity is widely debated. As a response to this debate, genetic ancestry has been suggested as a complement or alternative to this categorization. However, few studies have examined the effect of genetic ancestry, racial/ethnic identity, and environmental exposures on biological processes. Herein, we examine the contribution of self-identification within ethnicity, genetic ancestry, and environmental exposures on epigenetic modification of DNA methylation, a phenomenon affected by both genetic and environmental factors. We typed over 450,000 variably methylated CpG sites in primary whole blood of 573 individuals of Mexican and Puerto Rican descent who also had high-density genotype data. We found that methylation levels at a large number of CpG sites were significantly associated with ethnicity even when adjusting for genetic ancestry. In addition, we found an enrichment of ethnicity-associated sites amongst loci previously associated with environmental and social exposures. Interestingly, one of the strongest associated sites is driven by the Duffy Null blood type variant, demonstrating a new function of the locus in lymphocytes. Overall, the methylation changes associated with race/ethnicity, driven by both genes and environment, highlight the importance of measuring and accounting for both self-identified race/ethnicity and genetic ancestry in clinical and biomedical studies and the benefits of studying diverse populations. (2) In epigenome-wide association studies (EWAS), different methylation profiles of distinct cell-types may lead to false discoveries. We introduce ReFACTor, a method based on principal component analysis (PCA) for the correction of cell-type heterogeneity in EWAS. ReFACTor does not require knowledge of the cell counts, and it obtains improved estimates of the cell-type composition, resulting in improved power and control for false positives in EWAS. Bisulphite converted DNA from 573 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip and a complete blood count with automated white blood cell differential was performed by automated flow cytometry for 95 of the samples.
2016-02-29 | E-GEOD-77716 | biostudies-arrayexpress
Project description:The use of induced pluripotent stem cells (iPSC) derived from independent patients and sources holds considerable promise to improve the understanding of development and disease. However, optimized use of iPSC depends on our ability to develop methods to efficiently qualify cell lines and protocols, monitor genetic stability, and evaluate self-renewal and differentiation potential. To accomplish these goals, 57 stem cell lines from 10 laboratories were differentiated to 7 different states, resulting in 248 analyzed samples. Cell lines were differentiated and characterized at a central laboratory using standardized cell culture methodologies, protocols, and metadata descriptors. Stem cell and derived differentiated lines were characterized using RNA-seq, miRNA-seq, copy number arrays, DNA methylation arrays, flow cytometry, and molecular histology. All materials, including raw data, metadata, analysis and processing code, and methodological and provenance documentation are publicly available for re-use and interactive exploration at https://www.synapse.org/pcbc . The goal is to provide data that can improve our ability to robustly and reproducibly use human pluripotent stem cells to understand development and disease. 114 samples This submission represents DNA methylation component of study.
2016-08-20 | E-GEOD-85828 | biostudies-arrayexpress