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• NHLBI TOPMed: MESA and MESA Family AA-CAC

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Comprehensive phenotypic and pedigree data for MESA study participants are available through dbGaP entry phs000209. MESA Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by five examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study.

  Study phs001416

• GAW16 Framingham and Simulated Data

  Important links to apply for individual-level data Genetic Analysis Workshop Instructions to Request Authorized Access Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Research Use Statement Questions regarding GAW16 should be directed to Vanessa Olmo at vanessa@business-endeavors.com. Problem 2: Description of the Framingham Heart Study In GAW16, we use data drawn from the Framingham Heart Study. The Framingham Heart Study — under the direction of National Heart, Lung, and Blood Institute; NHLBI — began in 1948 with the recruitment of adults from the town of Framingham, Massachusetts. At the time, little was known about the general causes of heart disease and stroke, but the death rates for cardiovascular disease (CVD) had been increasing steadily since the beginning of the 20th century and had become an American epidemic. The Framingham Heart Study is now conducted in collaboration with Boston University. The objective of the Framingham Heart Study was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Between 1948 and 1953 the researchers recruited 5,209 subjects (2,336 men and 2,873 women) between the ages of 29 and 62 from the town of Framingham, Massachusetts and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Subjects were recruited from lists of addresses recorded for the town. Two out of every three households were approached for participation in the study. While there was no intention to recruit families for family studies, the plan was to recruit all household members in the ages 30-60 within each house that was selected for study. Hence, many biologically related individuals were recruited, including 1644 spouse pairs. Since 1948, these participants have returned to the study every two years for a detailed medical history, physical examination, and laboratory tests. Now in 2008 at 60 years of follow up, there remain about 500 participants from this cohort. Between 1971 and 1975 the study enrolled a second-generation group — 5,124 of the original participants' children and the spouses of these children — to participate in similar examinations. 2,616 subjects are offspring of the original spouse pairs and 34 are stepchildren. A total of 898 offspring are children of cohort members where only one parent was a study participant and 1,576 are spouses of the offspring. The Offspring Cohort has been followed every four years through 2001 (except between Exams 1 and 2 with an intervening 8 years) using protocols similar to those used for study of the Original Cohort. Between 2002 and 2005 the study enrolled the third generation (Gen3) of the Framingham Heart Study - 4095 offspring of the second generation. None of their spouses were recruited. An additional 103 parents of this third generation, who were not recruited between 1971 and 1975, were also recruited at this time. The latter group is not included in the GAW16 data. With the recruitment of this third generation, the study has increasingly focused on genetic factors associated with the development of cardiovascular disease and its associated risk factors. To date, there is only one examination of this generation of participants. A description of the recruitment of this third generation and comparison with the earlier generations at their initial recruitment is presented in Splansky GL et al., 2007. Further information on the Study can be found at http://www.nhlbi.nih.gov/about/framingham/index.html. Genome-wide Dense SNP Scan in Framingham Heart Study Genetic studies did not begin in the FHS until the 1990s. In the late 1980s and through the 1990s DNA was extracted from blood samples of surviving FHS participants. In 2007, the FHS entered a new phase with the conduct of genotyping for the FHS SHARe (SNP Health Association Resource) project, for which dense SNP genotyping was performed using approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel) in 10,775 samples (some duplicates) from the three generations of subjects (including over 900 pedigrees). Affymetrix conducted all genotyping for the FHS SHARe project, using the 250K Sty, 250K Nsp, and the supplemental 50K platforms. Eighty-nine percent of the DNA samples were collected during the 1990s. To maximize the power of the study, we also extracted DNA from 1133 blood samples, drawn from subjects who had no DNA, to include in the SHARe project. These samples had been sitting in our refrigerators for some time, a few as far back as the 1970s. We refer to these DNA samples as the legacy samples. These samples had a higher failure rate in the genotyping process (40%) than the other eighty-nine percent (3%). Affymetrix invoked its own criteria for a sample to succeed in genotyping. All non-legacy samples must succeed on all three platforms, while legacy samples needed to pass on at least one platform. When a sample failed, additional attempts were made. Samples that repeatedly failed 2-4 times were called failures. Other samples failed due to issues of genotyped sex identification not matching our records or low SNP concordance among SNPs common across arrays or contamination. Eighty-nine percent of the legacy samples for which genotyping results are available passed all three platforms. The genotyping data from the 10,043 samples from 9354 subjects that passed the Affymetrix criteria were additionally checked for gender consistency and consistency with family structure, resulting in genotyping data for 9,274 participants in FHS SHARe. Genotype calls were made with the BRLMM algorithm. The SHARe database is housed at the National Center for Biotechnology Information database of genotypes and phenotypes (NCBI dbGaP) and contains all ~550,000 SNPs. This genome-wide dense SNP scan and a subset of phenotypes from the Framingham Heart Study are the focus of the Genetic Analysis Workshop 16. Further information on the specific variables in the Problem 2 dataset can be found by clicking on the Documents tab at the top of the page. Problem 3: Description of the Simulated Data Set The focus of this simulation is gene discovery in genome-wide association scans (GWAS). The Framingham Heart Study data set (distributed as "Problem 2") is the basis for the FHS* simulated data. The pedigree structures are derived from the data distributed for Problem 2, and we distribute an accompanying triplet file (triplet_sim) containing person ID, father ID, mother ID, to ensure the identical subjects, pedigrees, and singletons are used in the simulated data analysis. Consistent with standard practice, founders and singletons are designated as subjects with both fshare and mshare equal to zero (missing). The simulated data includes a total of 6,479 subjects with both phenotype and genotype data, in 942 pedigrees distributed among 3 generations and 188 singletons. Data inclusion is consistent with the subjects' consent for use by both for-profit and not-for-profit researchers. The genotypes for all Problem 3 replicates are fixed as measured and distributed for Problem 2 for both the genomewide scan and the additional candidate gene SNPs, for a total of approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel). Thus, to analyze the Problem 3 simulated data you also will need to download the Problem 2 genotypes. Note that there are slight discrepancies in counts between Problems 2 and 3 due to a change in consents between the two datasets. Several phenotypes that contribute to coronary heart disease (CHD) were simulated for all individuals with genotypes across three different time points, 10 years apart. All genotyped individuals have complete data; the effects of missing values can be investigated by user-specified missing value patterns. There are 200 longitudinal datasets created, based on the generating model, and each replication is found in a separate dataset. We suggest that if only one replication is to be analyzed, that it be replication 1 to enable more precise comparisons among analytical approaches. The 'shareid' will allow you to merge the simulated phenotype data with the Problem 2 genotype data, and reconstruction of the pedigrees using the distributed 'triplet_sim' file or for larger families' relationships with the triplet distributed with the Problem 2. The simulated data problem is further described in the associated readme file, and a data dictionary is provided defining all the variables. For disclosure of the generating model for these data, please contact Jean MacCluer at jean@sfbrgenetics.org.

  Study phs000128

• HCC.GNE RNA-Seq

  RNA-Sequencing data (raw read sequences) for 23 samples, from 12 patients, for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma"

  Dataset EGAD00001000886

• CCA methylation data (12 CCA, 7 normal)

  Raw idat files for DNA methylation profiling for 12 CCAs and 7 normal bile duct tissues. DNA methylation profiling was performed using Infinium MethylationEPIC v2.0 Kit.

  Dataset EGAD00010002613

• RNA-seq data for Heterogeneity of IKZF1 genomic alterations and risk of relapse in childhood BALL

  RNA-seq data for 14 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000151

• Single-cell RNA-seq of Bone marrow samples

  For two donors, we collected CD34 plus and CD34 minus hematopoietic cells for the single-cell RNA-seq analysis.

  Dataset EGAD50000000514

• WGS data for genomic determinants of response and resistance to inotuzumab in B-ALL

  Whole genome sequencing data for 45 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000096

• WES data for genomic determinants of response and resistance to inotuzumab in B-ALL

  Whole exome sequencing data for 69 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000097

• Haukeland University Hospital Data Access Committee for STRAT-PARK datasets archived in Federated EGA Norway

  This is the Data Access Committee mandated by Haukeland University Hospital for the STRAT-PARK cohort: an initiative to stratify Parkinson's disease.

  Dac EGAC50000000428

• DAC for "Identification and characterization of tertiary lymphoid structures in brain metastases"

  This is the DAC for the study "Identification and characterization of tertiary lymphoid structures in brain metastases" of Prof. Dr. Guido Reifenberger (Guido.Reifenberger@med.uni-duesseldorf.de)

  Dac EGAC50000000369

• Whole exome sequencing of prDLBCL

  To investigate the mutational landscape of prDLBCL, 34 cases were selected for whole exome sequencing.

  Study EGAS50000000403

• sc-DECISION

  Data derived from PBMC and blood samples for the single cell and bulk RNAseq analysis for the sc-DECISION paper. https://doi.org/10.1101/2025.02.04.25321370

  Dataset EGAD50000001622

• HeLa S3 (CCL-2.2) HiC Sequencing

  HiC chromatin conformation sequencing was performed for the purpose of chromosome fusion and structural rearrangement identification.

  Study phs000665

• Data Access Committee for Translational analyses from a phase II study of pembrolizumab and epigenetic modification with azacitidine in platinum-resistant epithelial ovarian cancer

  This DAC is responsible for request review and handling related to the study above.

  Dac EGAC50000000697

• Liver Regulatory Genomics Data Access Committee

  Data access committee for genomic datasets generated for human liver tissue and human primary liver cells by the Regulatory Genomics of Metabolic Disease group (Imperial College London, Section of Genetics and Genomics).

  Dac EGAC50000000715

• DAC for "Drug Development against Tumor Microtube Networks in Glioblastoma"

  This is the DAC for the study "Drug Development against Tumor Microtube Networks in Glioblastoma" of Dirk C. Hoffmann, Dirk.Hoffmann@dkfz.de and Frank Winkler, Frank.Winkler@med.uni-heidelberg.de

  Dac EGAC50000000326

• single cell transcriptomic analysis of tumor samples collected from 5 patients with EMM

  Contains the raw single cell RNAseq data used for the study

  Study EGAS50000000034

• McGill EMC Release 4 in tissue "venous blood" for cell type "B cell"

  McGill EMC Release 4 in tissue "venous blood" for cell type "B cell"

  Dataset EGAD00001001278

• VALCAP files for Ma et al. (2019) SCMC Hybrid

  VALCAP files for Ma et al. (2019) Genome Biology (accepted) titled “Analysis of error profiles in deep next-generation sequencing data"

  Dataset EGAD00001004595

• McGill EMC Release 4 in tissue "fat pad" for cell type "fat cell"

  McGill EMC Release 4 in tissue "fat pad" for cell type "fat cell"

  Dataset EGAD00001001277

• McGill EMC Release 4 in tissue "venous blood" for cell type "T cell"

  McGill EMC Release 4 in tissue "venous blood" for cell type "T cell"

  Dataset EGAD00001001283

• RNAseq files for CHEN WTPDX RNASEQ

  RNAseq files for CHEN WTPDX RNASEQ paper titled "Forty-Five patient-derived xenografts capture the clinical and biological heterogeneity of Wilms tumor"

  Dataset EGAD00001004507

• WES files for Newman MAP3K8 melanoma

  WES files for Newman MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004566

• WGS files for Newman MAP3K8 melanoma

  WGS files for Newman MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004579

• Dataset for "Genome-wide analysis of HPV integration in human cancers reveals recurrent, focal genomic instability"

  Dataset for "Genome-wide analysis of HPV integration in human cancers reveals recurrent, focal genomic instability"

  Dataset EGAD00001000691