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• EGA file encryption types

  EGA file encryption The European Genome-Phenome Archive (EGA) stands as a significant initiative in the field of genomics, facilitating the secure storage and sharing of vast amounts of genomic data. Jointly hosted by the Centre for Genomic Regulation (CRG) and the European Bioinformatics Institute (EMBL-EBI), the EGA offers a robust infrastructure for managing encrypted data, ensuring the privacy and integrity of sensitive genomic information. Both CRG and EMBL-EBI play pivotal roles in the EGA, each institution bringing unique expertise in managing different types of encryptions. EMBL-EBI EGACryptor encryption system, while CRG utilises Crypt4GH, resulting in two distinct encryption file types: cip and c4gh, respectively. How can I check the file encryption? To access your dataset of interest on the European Genome-Phenome Archive (EGA) and determine the corresponding encryption file extension, please follow these step-by-step instructions: Utilise the search or navigation features provided on the EGA website to locate the dataset you are interested in. Once you find the dataset webpage, click on the "Files" tab, typically located on the dataset's webpage. Upon reaching the "Files" tab, you will be presented with a table containing comprehensive information about the files associated with the dataset. This table will include various columns, such as "File Name," "Size," and "Location." The "Location" column is particularly relevant for determining the encryption file extension. Figure 1: File table showing all the information available for the files in a dataset. This table is specific for each dataset. To identify the encryption file extension corresponding to a specific file, locate the "Location" column in the table. If the file is archived in Spain, the file will have the .c4gh extension, indicating that it is encrypted using Crypt4gh. Conversely, if the file is archived in the UK, the encrypted file extension will be .cip, indicating the usage of EGACryptor for encryption. It is worth noting that a file can be available in both locations, meaning it will be accessible with both file extensions (.c4gh and .cip). This allows users to choose the encryption method that aligns with their preferred platform or analysis tools.

  Documentation check-encryption-type

• Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants and parents), NIDDK

  Genetics of Kidneys in Diabetes (GoKinD) study is an initiative aimed at identifying susceptibility genes for diabetic nephropathy in type 1 diabetes. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents were also enrolled to form family trios. Altogether, GoKinD includes 3043 participants comprising 931 cases, 944 singletons, 268 pairs of parents of cases, and 316 pairs of parents of control. Accessible as a GAIN database are 905 of the cases, 890 of the controls, 10 pairs of parents of cases and 10 pairs of parents of controls (dbGaP phs000018 Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants), GAIN). The other parents and the remaining cases and controls are available by a separate application process through NIDDK. Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form available at http://www.niddkrepository.org or by contacting the Juvenile Diabetes Research Foundation.

  Study phs000088

• Cross-Species Single-Cell Analysis of Pancreatic Ductal Adenocarcinoma Reveals Antigen-Presenting Cancer-Associated Fibroblasts

  Cancer-associated fibroblasts (CAFs) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of several recently described subtypes, although the extent of CAF heterogeneity has remained undefined. Here we employ single-cell RNA-sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human PDAC tumors. Six human PDAC tumor specimens from six patients were collected, and processed for single-cell RNA-sequencing analysis. Adjacent-normal pancreas tissue was also collected from two of the patients. Tumor samples were digested, and fluorescence-activated cell sorting was used to isolate viable cells. For one tumor sample, viable, CD45-negative, CD31-negative, and EpCAM-negative cells were also isolated to enrich for CAFs. The 10X Chromium platform was then used to isolate single cells for RNA-sequencing analysis. This work has demonstrated the differences in immune cell populations between adjacent-normal and tumor tissues, and identified subpopulations of epithelial cells and CAFs present in PDAC tumors. This high-throughput analysis is a resource to better understand the cell populations present in PDAC, and may ultimately aid in the development of more effective therapies for this deadly malignancy.

  Study phs001840

• Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants), GAIN

  Genetics of Kidneys in Diabetes (GoKinD) study is an initiative aimed at identifying susceptibility genes for diabetic nephropathy in type 1 diabetes. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents were also enrolled to form family trios. Altogether, GoKinD includes 3043 participants comprising 931 cases, 944 singletons, 268 pairs of parents of cases, and 316 pairs of parents of control. Accessible as a GAIN database are 905 of the cases, 890 of the controls, 10 pairs of parents of cases and 10 pairs of parents of controls. The other parents and the remaining cases and controls are available by a separate application process through NIDDK (dbGaP phs000088 Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants and parents), NIDDK). Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form available at Juvenile Diabetes Research Foundation. Consent groups and participant set Diabetic complications only (DCO): 1825 (904 cases, 881 controls, 40 others)

  Study phs000018

• GDAP___Genome_Diversity_in_Africa_Project

  The Genomic Diversity in Africa Project (GDAP) started with the plan to develop a genomic resource from African populations, characterise genomic diversity and population history, and facilitate clinical studies in Africa. Currently, 25 individuals from 24 ethnolinguistic groups have been whole-genome sequenced at high depth totalling 585 individuals. An additional 41 individuals have been sequenced with 10X Genomics libraries. At this stage, the initial curation of this dataset has been finished and we are performing the analysis in coordination with our collaborators. The current state of the GDAP represents a very diverse panel of African populations that maximizes geographical and ethnic variation and represents a great starting point to achieve the aforementioned goals. However, southern sub-Saharan countries, Bantu speakers and hunter gatherer groups are currently underrepresented, despite being crucial to understand the evolutionary history of the continent. After extensive effort to collate studies documentation, we finally have the opportunity to sequence 600 new individuals from these groups, including countries as Gabon, Rwanda and Zambia, and address these deficiencies. We aim to proceed with the same strategy: to sequence at high depth 25 individuals with standard PCR free libraries, with 2 additional individuals with 10X Genomics Chromium libraries per ethnolinguistic group. The former allows a good representation of variants down to low frequency in any given population, and the latter allows accurate phasing and the analysis of structural variation. By including these new populations, we want to investigate three crucial questions in African history in addition to the initial objectives: the Bantu expansion, the evolutionary history of hunter gatherers and the transatlantic slave trade. Additionally, the expanded dataset will help us better discover the genetic variation present in Africa and characterize the African pangenome. 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/

  Study EGAS00001003602

• LuCaP cell line ChIP-seq

  ChIP-seq of 2 LuCaP cell lines with different factors. LuCaP cell line 189.4 was ChIP-sequenced for 6 factors with different conditions as well as the input DNA (n=31 in total). LuCaP 189.4 ChIP-sequence experiments include; 3 H3K27ac/DMSO, 3 H3K27ac/vorinostat, 3 H3K27ac/dexamethasone, 3 H3K27ac/dexamethasone/vorinostat, 3 GR dexamethasone, 3 GR dexamethasone/vorinostat, 3 HDAC3/DMSO, 3 AR, 3 FOXA1, 3 H3K27ac and 1 input sample. LuCaP 35 ChIP-sequence experiments as well as input include (n=10 in total); 3 H3K27ac, 3 AR, 3 FOXA1 and 1 input sample. All 41 samples were sequenced using paired-end reads on Illumina NovaSeq 6000. Each sample has 2 fastq files, one for the forward and reverse read, respectively.

  Dataset EGAD50000001345

• National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

  NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

  Study phs004180

• UK10K NEURO FSZNK

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This Finnish schizophrenia sample set has been collected from a population cohort using national registers. The entire sample collection consists of 2756 individuals from 458 families of whom 931 are diagnosed with schizophrenia spectrum disorder. Families outside Kuusamo (n=288) all had at least two affected siblings. All diagnoses are based on DSM-IV and for a large fraction of cases there is cognitive data.For further details/descriptions with regard to this data set please contact Tiina Paunio (tiina.paunio@thl.fi)

  Study EGAS00001000119

• Genomic_Advances_in_Sepsis__GAinS__genotyping

  This cohort comprises a subset of pateints enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 35 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected over the first five days of ICU admission. DNA was extracted from buffy coat or whole blood samples using the Qiagen DNA extraction protocol, the automated Maxwell Blood purification kit (Promega), or the QIAamp Blood Midi kit protocol (Qiagen). Genotyping data were generated using the Illumina HumanOmniExpress BeadChip (295 patients), the Infinium CoreExome BeadChip (655 patients), and the Infinium Global Screening Array BeadChip (307 patients). Genotyping QC and imputation into the Haplotype Reference Consortium was perfomed within each batch. The datasets were combined and following post-imputation filtering data were available on 1168 samples. 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/

  Study EGAS00001007786

• NHLBI TOPMed: Study of African Americans, Asthma, Genes and Environment (SAGE)

  This is a parallel case-control pharmacogenetic study of bronchodilator drug response among African American children with and without asthma. Each participant had spirometry measured using the KoKo PFT System. Asthmatic participants were administered with 4 puffs of HFA Albuterol. Healthy participants were given a baseline spirometry test. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants were 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications.

  Study phs000921