DAC

African Partnership for Chronic Disease Research (APCDR) DAC

Dac ID Contact Person Email Access Information
EGAC00001000237 Data Sharing datasharing [at] sanger [dot] ac [dot] uk No additional information is available

This DAC controls 17 datasets:

Dataset ID Description Technology Samples
EGAD00001001007 Low depth (4x) Illumina HiSeq raw sequence data for 100 unrelated Zulu from Durban area, South Africa. Illumina HiSeq 2000 100
EGAD00001001663 Low coverage (4x-8x) Illumina HiSeq curated sequence data from 3 African populations from the AGV project; 100 Baganda from Uganda (4x), 100 Zulu from South Africa (4x), and 120 Gumuz, Wolayta, Oromo, Somali and Amhara from Ethiopia (8x). Pre-processed, jointly called and filtered with GATK, refined with Beagle3, phased with SHAPEIT2. 1
EGAD00001003426 High depth whole genome sequencing from GemCode (10x Genomics) DNA libraries containing long range linkage information for one Baganda trio and one Baganda child (parent already sequenced at high depth). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ This dataset contains all the data available for this study on 2017-07-05. Illumina HiSeq 2500 16
EGAD00001006970 Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2021-02-16. HiSeq X Ten 53
EGAD00001006976 Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics . This dataset contains all the data available for this study on 2021-02-17. HiSeq X Ten,Illumina MiSeq 27
EGAD00010001045 APCDR AGV Project: Array data from 99 Igbo. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2.5-4v1_B 0
EGAD00010001046 APCDR AGV Project: Array data from 86 Sotho. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2-5_8v1_A 0
EGAD00010001047 APCDR AGV Project: Array data from 107 Ethiopians (Amhara, Oromo, Somali; subset of Ethiopian Genome Project Genotyping). Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2-5_8v1_A 0
EGAD00010001048 APCDR AGV Project: Array data from 79 Jola. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2-5_8v1_A 0
EGAD00010001049 APCDR AGV Project: Array data from 99 Kikuyu. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2.5-4v1_B 0
EGAD00010001050 APCDR AGV Project: Array data from 78 Wolof. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2-5_8v1_A 0
EGAD00010001051 APCDR AGV Project: Array data from 97 Barundi. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2-5_8v1_A 0
EGAD00010001052 APCDR AGV Project: Array data from 100 Kalenjin. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2.5-4v1_B 0
EGAD00010001053 APCDR AGV Project: Array data from 100 Banyarwanda. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2.5-4v1_B and HumanOmni2-5_8v1_A 0
EGAD00010001054 APCDR AGV Project: Array data from 74 Fula Illumina HumanOmni2-5_8v1_A 0
EGAD00010001056 APCDR AGV Project: Array data from 100 Zulu. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2.5-4v1_B and HumanOmni2-5_8v1_A 0
EGAD00010001057 APCDR AGV Project: Array data from 88 Mandinka. Raw data, intensity files and post-QC Plink files. Illumina HumanOmni2-5_8v1_A 0