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11 results for “multi-ancestry”
MAGE: Multi-ancestry Analysis of Gene Expression
<p>MAGE comprises RNA-seq data from lymphoblastoid cell lines derived from 731 individuals from the <a href="https://doi.org/10.1038/nature15393" rel="nofollow">1000 Genomes Project (1KGP)</a>, representing 26 globally-distributed populations across five continental groups. These data offer a large, geographically diverse, open access resource to facilitate studies of the distribution, genetic underpinnings, and evolution of variation in human transcriptomes and include data from several ancestry groups that were poorly represented in previous studies.</p> <p>Briefly, this repo contains the following data:</p> <ol> <li>Sample metadata and sequencing metrics</li> <li>Gene expression and splicing matrices used for e/sQTL mapping and analyses of global trends of expression/splicing diversity</li> <li>cis-e/sQTL mapping results, including aFC estimates for cis-eQTLs</li> <li>Functional annotations of cis-e/sQTLs</li> <li>Results of colocalization analysis between MAGE e/sQTLs and complex trait GWAS from the <a href="https://doi.org/10.1038/s41586-019-1310-4" rel="nofollow">PAGE</a> study</li> <li>Results of analyses of global trends of expression/splicing diversity</li> <li>Jointly-generated top genotype PCs for samples in MAGE and other resources with paired WGS/RNA-seq data (Geuvadis, GTEx, AFGR)</li> </ol> <p>READMEs are provided for all data in the repo.</p>
Results from the revision of MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data
<p>afr47041.zip, lat36378.zip, and eur115620.zip contain All of Us Summary Statistics used in the revised version of "MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data". Summary statistics for three cohorts are included: Afr47k, Lat36k, and Eur116k. These cohorts have not been downsampled to have equal levels of missingness.</p> <p>pips.tsv contains fine-mapped variants with PIP > 0.01 via MultiSuSiE from the revised version of "MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data". Subcohorts with the _unmatched suffix have not been downsampled to have equal levels of phenotyped missingness across ancestries. </p> <p>MultiSuSiE-main.zip contains the MultiSuSiE software packages (corresponds to the Github repo on 10/16/2025).</p> <p>Please cite:</p> <p>Rossen, Jordan, et al. "MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data." <em>medRxiv</em> (2024): 2024-05.</p> <p> </p>
Improved multi-ancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk
<p>sushie.molqtl.weights.tar.gz contains ancestry-specific eQTL and pQTL weights trained on mRNA and protein levels measured in American European, American African, and American Hispanic ancestries from TOPMed-MESA and GENOA studies. Column “a1” is the counting allele.</p> <p>mesa.*.fusion.tar.gz contains the weights in FUSION format.</p> <p>sushie_real_data_results.tar.gz contains all the real data analyzed in the sushie project.</p> <p>sushie_sim_data_results.tar.gz contains all the sim data analyzed in the sushie project.</p> <p>sushie_analysis_codes.tar.gz contains all the codes and scripts to generate and analyze these data.</p>
X-linked multi-ancestry meta-analysis reveals tuberculosis susceptibility variants
<p>Globally, tuberculosis (TB) presents with a clear male bias that cannot be completely accounted for by environment, behaviour, socioeconomic factors, or the impact of sex hormones on the immune system. This suggests that genetic and biological differences, which may be mediated by the X chromosome, further influence the observed male sex bias. The X chromosome is heavily implicated in immune function and yet has largely been ignored in previous association studies. Here we report the first multi-ancestry X chromosome specific meta-analysis on TB susceptibility. We identified X-linked TB susceptibility variants using seven genotyping data sets and 20,255 individuals from diverse genetic ancestries. Sex-specific effects were also identified in polygenic heritability between males and females along with enhanced concordance in direction of genetic effects for males but not females. These sex-specific genetic effects were supported by a sex-stratified and combined meta-analysis conducted using the X chromosome specific XWAS software and a multi-ancestry analysis using the MR-MEGA software. Seven significant associations were identified. Two in the overall analysis (rs6610096, rs7888114) and a second for the female specific analysis (rs4465088) including all data sets. For the ancestry specific meta-analysis three significant associations were identified for males in the Asian cohorts (rs1726176, rs5939510, rs1726203) and one in females for the African cohort (rs2428212). Several genomic regions previously associated with TB susceptibility were reproduced in this study, along with strong ancestry-specific effects. These results support the hypothesis that the X chromosome and sex-specific effects could significantly impact the observed male bias in TB incidence rates globally. </p>
Multi-ancestry genome-wide association statistics of anxiety
<p><strong>Multi-Ancestry Genome-Wide Association Statistics of Anxiety</strong></p> <p><strong>Citation</strong>: Friligkou E, Lokhammer S, Cabrera Mendoza B, Shen J, He J, Deiana G, Zanoaga MD, Asgel Z, Pilcher A, Di Lascio L, Makharashvili A, Koller D, Tylee D, Pathak GA, Polimanti R. Gene Discovery and Biological Insights into Anxiety Disorders from a Large-Scale Multi-Ancestry Genome-wide Association Study. Nat Genet. doi: 10.1038/s41588-024-01908-2.</p> <p> </p> <p> </p> <p> </p>
Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci
<p>All full-sample files contain results generated in coronary artery tissue from 138 American adults. Subset analyses utilized 80 individuals selected from the original 138. Scripts accompanying some of these data in downstream analyses can be viewed on our Github, which also contains a link to the current version of our accompanying manuscript: https://github.com/MillerLab-CPHG/CAD_QTL</p> <p>Full summary statistics for eQTL associations using mixQTL (https://github.com/hakyimlab/mixqtl/wiki) by chromosome are located in UVA_coronary_mixQTL_sumstats_by_chromosome.zip</p> <p>Full summary statistics for eQTL associations using mixQTL in the subset of 100% European-ancestry study sample members by chromosome are located in Hodonsky_mixQTL_Euro_sumstats.zip</p> <p>Full summary statistics for eQTL associations using mixQTL in the genetically diverse downsampled subset by chromosome are located in Hodonsky_mixQTL_downsample_sumstats.zip</p> <p>Full summary statistics for nominal pass for all genes identified as significant in the permutation pass using QTLtools (https://qtltools.github.io/qtltools/) adjusting for local ancestry by gene by chromosome are located in Local_ancestry_UVA_coronary_QTLtools_nominal_sumstats.zip</p> <p>Full summary statistics for sQTL associations with splice junctions using QTLtools by gene are located in sQTL_results_UVA_coronary_full_sumstats.zip</p>
X-linked multi-ancestry meta-analysis reveals tuberculosis susceptibility variants
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Multi-ancestry meta-analysis of host genetic susceptibility to tuberculosis identifies shared genetic architecture
<p><span>The heritability of susceptibility to tuberculosis disease (TB) has been well recognized. Over one-hundred genes have been studied as candidates for TB susceptibility, and several variants were identified by genome-wide association studies (GWAS), but few replicates. We established the International Tuberculosis Host Genetics Consortium (ITHGC) to perform a multi-ancestry meta-analysis of GWAS including 14,153 cases and 19,536 controls of African, Asian, and European ancestry. Our analyses demonstrate a substantial degree of heritability (pooled polygenic h<sup>2</sup>=26.3% 95% CI 23.7–29.0%) for susceptibility to TB that is shared across ancestries, highlighting an important host genetic influence on disease. We identified one global host genetic correlate for TB at genome-wide significance (p < 5x10<sup>-8</sup>) in the human leukocyte antigen (HLA)-II region (rs28383206, p-value = 5.2x10<sup>-9</sup>). These data demonstrate the complex shared genetic architecture of susceptibility to TB and the importance of large-scale GWAS analysis across multiple ancestries experiencing different levels of infection pressures. </span></p>
Multi-ancestry meta-analysis of host genetic susceptibility to tuberculosis identifies shared genetic architecture
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Multi-ancestry genetic analysis of gene regulation in coronary artery prioritizes disease risk loci
GEO Series GSE225650. Homo sapiens. 138 samples. Type: Expression profiling by high throughput sequencing.
Summary statistics - Multi-ancestry GWAS of asthma exacerbations
<p>Summary statistics corresponding to the manuscript titled "Multi-ancestry genome-wide association study of asthma exacerbations" (doi: https://doi.org/10.1111/pai.13802) published in<em> Pediatric Allergy and Immunology.</em></p> <ul> <li>RSID: SNP ID (chromosome: hg19<em> </em>position :reference allele: tested allele)</li> <li>STUDY: Number of ethnic groups contributing to the multi-ancestry meta-analysis</li> <li>BETA_meta: Regression coefficient</li> <li>SEBETA_meta: Standard error for the regression coefficient</li> <li>PVALUE_meta: P-value </li> <li>PVALUE_Q: P-value of Cochran's Q.</li> </ul>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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