368 results for ""10.37717"+DELTAS+Africa+SFA+Foundation+grant+DOI"

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• Genetics and Networks of Congenital Heart Defects

  Exome sequencing of families with Congenital Heart Defects of diverse sub-phenotypes. Comprises both parent-offspring trios for sporadic cases and multiplex families. Collaboration with David Brook, University of Nottingham. Funded by the British Heart Foundation.

  Dataset EGAD00001002251

• A novel orthotopic patient-derived xenograft model of radiation-induced glioma following medulloblastoma

  DNA methylation arrays were performed to molecularly subtype these samples based on Capper D, Jones DTW, Sill M, et al. DNA methylation-based classification of central nervous system tumours. Nature. 2018;555(7697):469-474. doi:10.1038/nature26000

  Dataset EGAD00010002017

• HIV-phyloTSI: BEEHIVE

  This dataset includes sample numbers TSI_0203 to TSI_0315 for the BEEHIVE cohort of the study. Samples were sequenced using the Illumina NovaSeq system and the veSEQ-HIV method (see Bonsall, Golubchik et al 2020, DOI: 10.1128/JCM.00382-20). Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001310

• Genetic Markers of Caries Risk in Diverse Underserved Children: CIDR

  The study Predicting Caries Risk In Underserved Children, From Toddlers To The School-age Years In Primary Healthcare Settings, is a renewal of an initial project designed to develop a dental caries risk tool for use in primary medical and dental healthcare settings to identify high dental caries risk children, expanding from the toddler (1-4 years old, referred to as Stage 1 grant) to the school-age years (6-9 years old, referred to as Stage 2 grant); and to determine the relationships between dental caries risk profiles and dental caries disease patterns. 1326 children, 12 +/- 3 months of age, and their primary caregivers, were enrolled in the study. This cohort represents a diverse population, including ethnic and racial minorities and low socio-economic status groups. There are a total of six in-person visits (at child age 1, 2.5, 4, 6.5, 8 and 9.5 years), and at each one the primary caregiver (PCG) completes a dental caries risk questionnaire, and the child receives a detailed dental caries examination. Saliva samples were collected during the age 8 visit (2019-2020) from 1,059 racially and ethnically diverse individuals (543 children and 516 PCGs) for the purposes of human genetic testing, to study the genetics of dental caries experience of children and their primary caregivers.

  Study phs003280

• APCDR AGV Project: WGS of South African Zulu

  The African Genome Variation Project (AGVP) provides a resource to help design, implement and interpret genomic studies in sub-Saharan Africa (SSA) and worldwide. The AGVP represents dense genotypes from 1,481 and whole genome sequences (WGS) from 320 individuals across SSA. As part of the AGVP we sequenced the genome of 100 unrelated Zulu from Durban area to about 4x depth.

  Study EGAS00001000286

• APCDR AGV Project: WGS of an Ugandan population

  The African Genome Variation Project (AGVP) provides a resource to help design, implement and interpret genomic studies in sub-Saharan Africa (SSA) and worldwide. The AGVP represents dense genotypes from 1,481 and whole genome sequences (WGS) from 320 individuals across SSA. As part of the AGVP we sequenced the genome of 100 unrelated Baganda from rural Uganda to about 4x depth.

  Study EGAS00001000363

• BrainCloud: Data from human postmortem brain procurement for the neuropathology section

  This study explores the temporal dynamics and genetic control of transcription and DNA methylation in the human dorsolateral prefrontal cortex in postmortem tissue. This study examines 269 subjects for gene expression (version 1) and 108 subjects for DNA methylation (version 2). The subjects are normal controls without neuropathological and neuropsychiatric diagnosis and range in age from fetal weeks 14-20 through old age (>80). We discover fast changes in gene expression occurring during early brain development. Later in life, the changes are considerably slower. Many genes reverse pattern of expression between fetal and early postnatal development. We identify thousands of strong associations of SNPs with gene expression. We examine DNA methylation in ~14,500 genes at ~27,000 CpG loci focused on 5' promoter regions. The fastest changes in DNA methylation also occur during the prenatal period, slow down markedly after birth and continue to slow further with aging. DNA methylation is strongly associated with genotypic variants and correlates with expression of a subset of genes. DNA for genotyping was obtained from the cerebella and applied to either Illumina 650K or 1 million BeadArrays - only genotypes common to both platforms are analyzed here. Genotypes were called using BeadExpress software. Doi: 10.1038/nature10524 Nature, 478:519-524, 2011; doi:10.1016/j.ajhg.2011.12.020, AJHG 90, 1-13, Feb 10, 2012. The methylation data can be downloaded at: BrainCloud.

  Study phs000417

• Sahel Data Access Committee

  Genome-wide genotype array data of Fulani populations presented in Fortes-Lima et al. 2025. Citation: Population History and Admixture of the Fulani People from the Sahel. Cesar A. Fortes-Lima, Mame Y. Diallo, Václav Janoušek, Viktor Černý, and Carina M. Schlebusch. American Journal of Human Genetics 112(2), February 6, 2025. doi: https://doi.org/10.1016/j.ajhg.2024.12.015

  Dac EGAC50000000290

• Single Cell Transcriptomics of peripheral immune cells pre- and post-Immune Checkpoint Blockade

  This is raw sequencing data, analysis of which is presented in the paper "Sensitivity to Immune Checkpoint Blockade and Progression-Free Survival is associated with baseline CD8+ T cell clone size and cytotoxicity", DOI: https://doi.org/10.1101/2020.11.15.383786

  Dataset EGAD00001007942

• Assessment of Complex Chromosomal Changes in De-Identified Cell Lines

  In this study, we obtained DNA from the Coriell Repository from individuals with complex chromosomal changes. The database ("Chromosome Abnormalities") of these de-identified samples contains 1,366 individuals as per https://www.coriell.org/1/NIGMS. We started with 16 individuals in this pilot study that we will hopefully expand out in a potential large NIH grant using information derived in this pilot study. De-identified samples were sequenced using internal funding from Washington University in St. Louis. A description of the sequencing we did on these individuals is provided in our medRxiv preprint at https://www.medrxiv.org/content/10.1101/2025.03.28.25324850v1.

  Study phs004000