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• HV31 - 10x linked-read sequencing

  10x linked-read sequencing data for individual HV31 generated using DNA from CD14+ monocytes, to a sequencing depth of ~40×. Sequencing was performed at Bart’s and the London Genome Centre on the Illumina HiSeq platform.

  Dataset EGAD00001007046

• 10x Genomics Single Cell Gene Expression for SA1035X8XB03425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 8

  Dataset EGAD00001009148

• 10x Genomics Single Cell Gene Expression for SA1184SA

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1184

  Dataset EGAD00001009145

• 10x Genomics Single Cell Gene Expression for OV2295

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295

  Dataset EGAD00001009143

• Single Cell Genome Sequence for DLP+ library A96141A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96141A

  Dataset EGAD00001009777

• Genome-wide array data Tunisia and Morocco

  This dataset contains genome-wide array data from Tunisian and Moroccan individuals. Tunisian individuals were sampled in the city of Tunis (n = 64), and Moroccan individuals in different urban areas in the country (n = 45).

  Dataset EGAD00001009071

• 10x Genomics Single Cell Gene Expression for SA604X8XB02164

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 8

  Dataset EGAD00001009118

• The University of Hong Kong Gastric Cancer XClone Study Single Cell CNV Data

  Single cell encapsulation and DNA libraries were prepared by Chromium™ Single Cell DNA Reagent Kits and Chromium™ Single Cell C and D Chip Kits.

  Dataset EGAD00001015383

• 10x Genomics Single Cell Gene Expression for SA1035X4XB02879

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 4

  Dataset EGAD00001009147

• Multiome

  This dataset contains the raw sequencing data (Runs) from all of the 10x Genomics single-cell Multiome Experiments

  Dataset EGAD00001009824

• 200PT : SNV vcf files

  200PT : SNV vcf files. SNV calls generated using SomaticSniper and PhyloWGS, from the CPCGene 200PT Subclonality study

  Dataset EGAD00001004072

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - TLR_pathway_study

  upcoming publication

  Dataset EGAD00001001960

• CNA vcf files for CPCG Subclonal Heterogeneity

  CNA calls generated using the SomaticSniper-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004405

• SNV vcf files for CPCG Subclonal Heterogeneity

  SNV calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004401

• 4C-seq data

  4C-seq data was generated for regions of interest to confirm enhancer-gene promoter interactions

  Dataset EGAD00001001847

• WGS and RNA-Seq data from a GBM patient PT-AR5365

  WGS and RNA-Seq data from a GBM patient PT-AR5365

  Dataset EGAD00001004227

• CNA vcf files for CPCG Subclonal Heterogeneity

  CNA calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004404

• Triple Negative BC RNA Sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001339

• SNV vcf files for CPCG Subclonal Heterogeneity

  SNV calls generated using the SomaticSniper-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004402

• CNA vcf files for CPCG Subclonal Heterogeneity

  CNA calls generated using the MuTect-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004403

• WGS and RNA-Seq data from a GBM patient PT-RW9277

  WGS and RNA-Seq data from a GBM patient PT-RW9277

  Dataset EGAD00001004259

• SNV vcf files for CPCG Subclonal Heterogeneity

  SNV calls generated using the MuTect-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004400

• ICGC Benchmark 1 (CLL)

  Raw fastq files from WGS sequencing of CLL and matching blood normal for the ICGC Techval Benchmark1 study. Sequence data was provided to multiple centers for independent analysis and comparison.

  Dataset EGAD00001001858

• Single-cell RNA-Seq (Chromium Next GEM Single Cell 3' Reagent Kits v3.1 from 10X Genomics )

  Human data for transcriptome (scRNA-Seq) in CD34+ B cell precursors.

  Dataset EGAD00001010907

• LBC1921 bam files

  297 members of the LBC1921 were sequenced using the Illumina HiSeq X platform. This dataset contains the bam files.

  Dataset EGAD00001011667

• RNA-seq dataset of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Dataset EGAD00001015771

• Genome and transcriptome sequence data from a diffuse aarge B-cell lymphoma (relapse) tumor patient

  Genome and transcriptome sequence data from a diffuse large B-cell lymphoma (relapse) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015308

• Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm tumor patient

  Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015312

• Genome and transcriptome sequence data from a metastatic malignant peripheral nerve sheath tumor tumor patient

  Genome and transcriptome sequence data from a metastatic malignant peripheral nerve sheath tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015322

• Genome and transcriptome sequence data from a CNS non-germinoma germ cell tumour tumor patient

  Genome and transcriptome sequence data from a CNS non-germinoma germ cell tumour patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015327

• WES raw data for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 123 patient samples including 38 normal (22 paired normal and 16 unpaired), 85 tumor-initial, FASTQ file types, Agilent SureSelect Human All Exon V6 Kit

  Dataset EGAD00001006400

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 1)

  Whole genome sequencing data of 6 high-grade serous carcinoma (HGSC) patients (11 samples) sequenced with MGISEQ-2000

  Dataset EGAD00001011353

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  The Environmental Determinants of Diabetes in the Young (TEDDY) Study investigates genetic and genetic-environmental interactions, including gestational infection or other gestational events, childhood infections and other environmental factors after birth, in relation to the development of pre-diabetic islet autoimmunity and type 1 diabetes (T1D). Beginning in 2002, a consortium of six centers assembled to participate in the development and implementation of studies to identify environmental factors that trigger the development of islet autoimmunity and T1D in genetically susceptible individuals. The TEDDY study screened around 400,000 newborns and recruited 7,749 neonates from the general population with a pre-determined T1D risk of 3% and 919 neonates with first degree relatives who have T1D and who have a pre-determined T1D risk of 10%. Thus, TEDDY proposes to follow over 8,000 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) until the age of 15. Participants are followed every three months for islet autoantibody measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive subjects continue to be followed at 3 month intervals and autoantibody negative subjects are followed at six month intervals. In addition to the analysis of autoantibodies, additional data and sample collection is performed at each visit. The parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. DNA extracted from the 9-month TEDDY blood sample was used for SNP genotyping. Samples were available for 7,082 participants. SNPs were genotyped by the Center for Public Health Genomics at the University of Virginia, using the Illumina ImmunoChip SNP microarray of around 196,000 SNPs selected from 186 regions associated with 12 autoimmune diseases (including T1D) (Hadley et al., 2015). "Data quality control (QC) steps included eliminating subjects with a low call rate (> 5% SNPs missing) and discrepancies between reported gender and prior genotyping at the HLA laboratory. Secondly, SNPs were removed from analysis due to low call rate, Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements)" (Törn et al., 2015). QC resulted in a total of 7,023 subjects with data on 176,586 SNPs. Additional information on the TEDDY study are available in the following articles: The Environmental Determinants of Diabetes in the Young (TEDDY) Study. TEDDY Study Group. Annals of the New York Academy of Science, 2008 and TEDDY - The Environmental Determinants of Diabetes in the Young - An Observational Clinical Trial. Annals of the New York Academy of Science, 2006 Details of the TEDDY protocol can be found in The Environmental Determinants of Diabetes in the Young (TEDDY): Genetic Criteria and International Diabetes Risk Screening of 421,000 infants. Pediatric Diabetes, 2011

  Study phs001037

• Rapid Acceleration of Diagnostics - Underserved Populations (RADx-UP): COVID-19 Testing and Prevention in Correctional Settings

  This study will work with diverse correctional facilities across MN, RI, WA, and FL to characterize the incidence of COVID-19 disease progression and related outcomes. The goal is to identify barriers and facilitators to develop strategies to improve testing in these under-served populations by: Increasing the reach, access, uptake, and impact of COVID-19 testing among incarcerated people and staff in prison and jails. Individuals in congregate settings have been disproportionately affected by COVID-19, with correctional settings accounting for 39 of the 50 largest cluster outbreaks in the country to date. Schema of Correctional Facilities: Correctional facilities are amplifiers of infectious diseases for structural reasons: 1) Dormitory-style living and overcrowded conditions make social distancing nearly impossible 2) They have a focus primarily on security not health 3) Their medical departments are under-resourced and often disconnected from local public health agencies. Correctional facilities must be the focus of urgent intervention to understand the incidence of COVID-19, how it spreads in correctional facilities, and durable long-term strategies to reduce transmission, including testing and vaccines. However, our work from the COVID Prison Project shows that correctional systems have implemented a range of testing strategies, without coordination, such that synthesizing the information on COVID-19 incidence, outcomes and optimal testing strategies (including repeat testing and contact tracing) has been challenging. Incarcerated people decline testing due to concerns about confidentiality, implications for release, and fear of placement in solitary confinement. Through interviews we will identify ethical concerns and potential solutions for COVID-19 testing and vaccine strategies in correctional facilities using a community-engaged strategy. The project's work from the COVID Prison Project shows that correctional systems have implemented a range of testing strategies, without coordination, such that synthesizing the information on COVID-19 incidence, outcomes and optimal testing strategies (including repeat testing and contact tracing) has been challenging. Incarcerated people decline testing due to concerns about confidentiality, implications for release, and fear of placement in solitary confinement. Through interviews we will Identify ethical concerns and potential solutions for COVID-19 testing and vaccine strategies in correctional facilities using a community-engaged strategy. Goals: 1. Identify ethical concerns and potential solutions for COVID-19 testing and vaccine strategies in correctional facilities using a community-engaged strategy. 2. Characterize incidence of COVID-19, disease progression, and related-outcomes and effectiveness of testing and contact tracing in correctional facilities. Participant Selection: a. Potential subjects must be currently incarcerated at key facilities in Washington, Rhode Island, Minnesota, and Florida. These facilities are Everglades Correctional Institution and Homestead Correctional Institution in Florida, Shakopee and Stillwater correctional facilities in Minnesota, the Rhode Island Department of Corrections, and Yakima County Jail in Washington. b. Participating correctional facilities in Florida, Minnesota, Rhode Island, and Washington will provide de-identified data on approximately 16,859 incarcerated adults and correctional staff. Data sources include deidentified data from medical records, administrative data, and policy documents pertaining to COVID-19. c. 3 series of focus groups (6, 12, 18 months) x 3 distinct groups (incarcerated people, medical providers, and correctional leaders) x 4 sites=36 total focus groups over the study period. d. Will utilize 74,812 COVID-19 tests to test and re-test a total of 16,859 incarcerated people and correctional staff for active infection over a six-month period in the FL, MN, and RI state prison systems and the Yakima County Jail in WA.

  Study phs003361

• Heart Failure Network - Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection Fraction (HFN NEAT-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Related StudiesEcho images are available with HFN-NEAT Imaging.ObjectivesTo determine the effect of isosorbide mononitrate on daily activity in patients with heart failure and preserved ejection fraction.Background Nitrates are commonly prescribed for symptom relief in patients with heart failure. Early studies in patients with heart failure with a reduced ejection fraction concluded that long-acting nitrates improve activity tolerance; however, approximately half of heart failure patients have preserved ejection fraction. The effects of nitrates in patients with heart failure and a preserved ejection fraction have not been extensively studied and the overall effect of nitrates on activity tolerance in such patients is uncertain. ParticipantsThere were a total of 110 participants enrolled with 51 participants assigned to receive isosorbide mono-nitrate first and placebo second, and 59 participants assigned to receive placebo first and isosorbide mononitrate second. Design Enrolled participants underwent baseline assessments, including echocardiography, quality-of-life scores, 6-minute walk test distance, and NT-proBNP levels. participants were also supplied with two kinetic activity monitors containing high-sensitivity triaxis accelerometers, to be worn 24 hours per day. The accelerometer measurements were expressed as arbitrary accelerometer units and stored every 15 minutes equaling 96 data points per day. The 15-minute cumulative accelerometer units were totaled over a 24-hour period to provide daily accelerometer units. Participants were assigned to one of two treatment groups: 6 weeks of placebo first with crossover to 6 weeks of isosorbide mononitrate, or 6 weeks of isosorbide mononitrate first with crossover to 6 weeks of placebo. The study drugs were prepared as 30-mg tablets of isosorbide mononitrate and matching placebo. During each 6-week period, participants were instructed to take no study drug for the first 2 weeks followed by one tablet (30 mg daily) for 1 week, two tablets (60 mg once daily) for 1 week, and four tablets (120 mg once daily) until the next study visit, for a treatment duration of at least 2 weeks and up to 4 weeks. After each 6-week period, participants returned to the study center to repeat end-point assessments. The primary outcome for the study was the comparison of average daily accelerometer units during the period in which participants were receiving the 120-mg dose of isosorbide mononitrate compared to the period in which participants received the placebo. Other secondary end points included the 6-minute walk distance and the post-walk Borg dyspnea score, scores on the Kansas City Cardiomyopathy Questionnaire and the Minnesota Living with Heart Failure Questionnaire, and NT-proBNP levels. In addition, participants completed a questionnaire indicating in which period (first, second, no preference) they felt better. Conclusions Participants were active for fewer hours of the day during the 120-mg phase of receipt of isosorbide mononitrate as compared with placebo. Furthermore, during all study-drug regimens combined (30 mg to 120 mg), participants were less active during receipt of isosorbide mononitrate as compared with placebo. There was no significant effect of isosorbide mononitrate on secondary outcomes.

  Study phs003548

• Heart Failure Network - Imaging from Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection Fraction (HFN NEAT-Imaging)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To determine the effect of isosorbide mononitrate on daily activity in patients with heart failure and preserved ejection fraction.Background: Nitrates are commonly prescribed for symptom relief in patients with heart failure. Early studies in patients with heart failure with a reduced ejection fraction concluded that long-acting nitrates improves activity tolerance; however, approximately half of heart failure patients have preserved ejection fraction. The effects of nitrates in patients with heart failure and a preserved ejection fraction have not been extensively studied and the overall effect of nitrates on activity tolerance in such patients is uncertain.Subjects: There were a total of 110 patients enrolled with 51 patients assigned to receive isosorbide mono-nitrate first and placebo second, and 59 patients assigned to receive placebo first and isosorbide mononitrate second.Design: Enrolled subjects underwent baseline assessments, including echocardiography, quality-of-life scores, 6-minute walk test distance, and NT-proBNP levels. Subjects were also supplied with two kinetic activity monitors containing high-sensitivity triaxis accelerometers, to be worn 24 hours per day. The accelerometer measurements were expressed as arbitrary accelerometer units and stored every 15 minutes equaling 96 data points per day. The 15-minute cumulative accelerometer units were totaled over a 24-hour period to provide daily accelerometer units.Subjects were assigned to one of two treatment groups: 6 weeks of placebo first with crossover to 6 weeks of isosorbide mononitrate, or 6 weeks of isosorbide mononitrate first with crossover to 6 weeks of placebo. The study drugs were prepared as 30-mg tablets of isosorbide mononitrate and matching placebo. During each 6-week period, patients were instructed to take no study drug for the first 2 weeks followed by one tablet (30 mg daily) for 1 week, two tablets (60 mg once daily) for 1 week, and four tablets (120 mg once daily) until the next study visit, for a treatment duration of at least 2 weeks and up to 4 weeks. After each 6-week period, patients returned to the study center to repeat end-point assessments. The primary outcome for the study was the comparison of average daily accelerometer units during the period in which patients were receiving the 120-mg dose of isosorbide mononitrate compared to the period in which patients received the placebo. Other secondary end points included the 6-minute walk distance and the post-walk Borg dyspnea score, scores on the Kansas City Cardiomyopathy Questionnaire and the Minnesota Living with Heart Failure Questionnaire, and NT-proBNP levels. In addition, subjects completed a questionnaire indicating in which period (first, second, no preference) they felt better. Conclusions: Patients were active for fewer hours of the day during the 120-mg phase of receipt of isosorbide mononitrate as compared with placebo. Furthermore, during all study-drug regimens combined (30 mg to 120 mg), patients were less active during receipt of isosorbide mononitrate as compared with placebo. There was no significant effect of isosorbide mononitrate on secondary outcomes.

  Study phs004254

• Cross-Sectional Characterization of Idiopathic Bronchiectasis

  This GDMCC protocol will study adult patients with non-CF, idiopathic bronchiectasis, whose genetic etiologies are not known. Idiopathic bronchiectasis is reportedly more common in females with certain tall, thin body types and associated with environmental organisms, such as nontuberculous mycobacterium (NTM). The other susceptibility factors predisposing to bronchiectasis or acquisition of NTM are unclear. The study will attempt to broaden the understanding of this disease by comparing gender-associated factors and NTM status. A relatively equal number of both females/males and NTM/non-NTM infected subjects will be enrolled. Approximately 300 people may be screened to find 260 eligible subjects, since a small number (e.g., 40 patients) may be diagnosed with PCD, vCF, or other known etiology as an explanation for the bronchiectasis. This single-visit protocol will use a systematic approach to characterize the physical features, radiographic patterns, and associated lower airway microbial flora. There is no natural history of disease course follow-up component to this protocol. Participants will have one outpatient clinic visit for evaluation with a physical examination including detailed body size measurements, medical history, collection of blood samples for routine lab tests and genetic analyses, and a chest X-ray if no recent one is available. Participants will also have tests of lung function, and measurement of a gas called nitric oxide in the nose. Participants whose initial tests show abnormal results may also be asked to have a nasal scrape to collect cell samples and/or a skin sweat test to measure salt concentrations. Participants will also have a sputum specimen collected during the visit and will be asked to collect two additional early morning sputum samples and a mouth rinse at home within 2 weeks of the clinic visit, and mail the sample collection materials to the research team. Careful evaluation and characterization of the physical and clinical characteristics will guide the genetic characterization of idiopathic bronchiectasis, and likely lead to an improved diagnostic approach. Identification of disease causing genes may provide new therapeutic targets.

  Study phs001279

• Population Architecture using Genomics and Epidemiology (PAGE): Causal Variants Across the Life Course (CALiCo): Strong Heart Study (SHS) and Strong Heart Family Study (SHFS)

  The SHS is a study of cardiovascular disease and its risk factors among American Indian men and women. Using standardized methodology, it was designed to estimate cardiovascular disease mortality and morbidity and the prevalence of known and suspected cardiovascular disease risk factors and to assess the significance of these risk factors in a longitudinal analysis. The study included 13 American Indian tribes and communities in three geographic areas: an area near Phoenix, Arizona, the southwestern area of Oklahoma, and western and central North and South Dakota. The SHS included three components: The first was a survey to determine cardiovascular disease mortality rates from 1984 to 1994 among tribal members aged 35-74 years of age residing in the 3 study areas (the community mortality study). The second was the clinical examination of 4,500 tribal members aged 45-74. The SHS has completed three clinical examinations of the original Cohort (Phase I: 1989-1991; Phase II: 1993-1995; Phase III: 1998- 1999, respectively). The third component is the morbidity and mortality (M&M) surveillance of these 4,500 participants. Yearly SHS surveillance has only 0.2% loss to follow-up. All deaths and all nonfatal CVD events are classified by standardized criteria, including details of stroke and HF. The Strong Heart Family Study (SHFS) is a genetic epidemiological study designed to investigate the heritability of CVD and its risk factors and to localize genes that contribute to CVD risk in American Indians. SHFS participants include 3,838 family members that were >/=15 years old, and ascertained through sibships of the original SHS, from 94 extended (large, multigenerational) families. Exams have occurred in a pilot Phase III (1998-1999, 900 SHFS participants), in Phase IV (2001-2003), and Phase V (2006-2009). SHFS morbidity and mortality surveillance has occurred throughout the study phases, with 0.3% lost to follow-up. Genetic data includes complete pedigree information, DNA samples from all family members, a 10cM-spaced microsatellite map used for IBD estimation and to perform linkage analysis, genotypes for more than 12,000 SNPs in candidate regions, and genotypes from commercially available SNP assays.

  Study phs000580

• Metagenomics-Guided Pathogen Discovery in Travelers' Diarrhea

  Traveler's diarrhea (TD) is caused by enterotoxigenic Escherichia coli (ETEC), other pathogenic gram-negative pathogens, norovirus and some parasites. Nevertheless, standard diagnostic methods fail to identify pathogens in more than 30% of TD patients, so it is predicted that new pathogens or groups of pathogens may be causative agents of disease. A comprehensive metagenomic study of the fecal microbiomes from 23 TD patients and seven healthy travelers was performed, all of which tested negative for the known etiologic agents of TD in standard tests. Metagenomic reads were assembled and the resulting contigs were subjected to semi-manual binning to assemble independent genomes from metagenomic pools. Taxonomic and functional annotations were conducted to assist identification of putative pathogens. We extracted 560 draft genomes, 320 of which were complete enough to be enough characterized as cellular genomes and 160 of which were bacteriophage genomes. We made predictions of the etiology of disease in individual subjects based on the properties and features of the recovered cellular genomes. Three subtypes of samples were observed. First were four patients with low diversity metagenomes that were predominated by one or more pathogenic E. coli strains. Annotation allowed prediction of pathogenic type in most cases. Second, five patients were co-infected with E. coli and other members of the Enterobacteriaceae, including antibiotic resistant Enterobacter, Klebsiella, and Citrobacter. Finally, several samples contained genomes that represented dark matter. In one of these samples we identified a TM7 genome that phylogenetically clustered with a strain isolated from wastewater and carries genes encoding potential virulence factors. We also observed a very high proportion of bacteriophage reads in some samples. The relative abundance of phage was significantly higher in healthy travelers when compared to TD patients. Our results highlight that assembly-based analysis revealed that diarrhea is often polymicrobial and includes members of the Enterobacteriaceae not normally associated with TD and have implicated a new member of the TM7 phylum as a potential player in diarrheal disease.

  Study phs001352

• Copy-Number Analysis of Understudied Black Women Ovarian Cancers

  Two general types of genetic alterations drive cancer progression: mutations and copy number alterations (CNAs). With the exception of p53, single nucleotide variant mutations (here, simply "mutations") are not drivers of 80% of tumors within the most frequent and deadly histotype of ovarian cancer: serous ovarian cancer (SOC). Rather, CNAs are more prevalent in SOC than any other cancer type studied by phs000178 The Cancer Genome Atlas (TCGA). Fully two-thirds of genes are altered by CNAs in the average SOC. Bioinformatic methods have shown that these CNAs modulate specific molecular pathways, such as autophagy, and this finding enabled effective pathway-targeted therapies1. Unfortunately, TCGA ovarian cancer data lacks racial diversity. Only 6% of SOC tumors (n=32) studied are from African origin. Black women diagnosed with ovarian cancer are more likely to die from their disease than white women. Five-year survival after diagnosis is 31% among blacks versus 42% among whites, and this disparity is seen in every age group and tumor stage distribution. Dr. Kelemen examined data from 365 white and 95 black ovarian cancer patients from the Hollings Cancer Center (HCC) Cancer Registry between 2000 and 2015 and found that black women had an 81% higher risk of death after diagnosis compared to white women (HR 1.81, 95% CI 1.35-2.43), independent of diagnosis center (98% were treated at HCC but half were diagnosed elsewhere), tumor stage, histology, extent of residual tumor remaining following surgery, insurance status, smoking, type of treatment for ovarian cancer, and age-adjusted Charlson comorbidity index. This disparity remained even when restricted to women who received the standard of care, surgery-chemotherapy sequence (HR 1.79, 95% CI 1.10-2.89). Despite receiving the same treatment, black race was still associated with inferior survival. A similar disparity has been reported by others, indicating that the HCC experience is representative of national data. Here, an additional set of high-grade serous ovarian cancer primary tumors were acquired from biorepositories with a focus on expanding data originating from African American women. Data were analyzed for copy-number alterations using exome sequencing and control-FREEC software.

  Study phs002313

• NHLBI and NIDDK Sponsored GWAS in Benign Ethnic Neutropenia/Leukopenia (BEN) in African-Americans (age >45 yrs old) from the REGARDS

  Benign ethnic neutropenia (BEN) is a clinical condition more commonly observed in African-Americans. It is characterized by a relative reduction in neutrophil count by about 1000 cells per microliter, leading to a decrease in total leukocyte count by similar decrement. Previous reports of this condition showed that there was neither higher frequency nor increased severity of infections in affected individuals. Bone marrow examinations showed normal white cell maturation; and ex vivo culture of marrow cells showed low normal or slightly reduced number of myeloid colonies. Under physiologic stress, the increases in neutrophil and leukocyte counts of BEN individuals are slightly lower, compared to normal African-Americans or Caucasians. These clinical observations suggest that BEN results from a lower 'set point' for cell number in the marrow. Additionally, case reports of familial BEN, the persistence of BEN over many decades in the US, UK, and Africa, and the recent report of Duffy antigen and chemokine receptor (DARC) being associated with neutropenia, all suggest a strong genetic association to neutropenia/leukopenia. Our initial look into microarray analyses in a pilot trial of subjects showed that there were no significant differences in mRNA signals between BEN and normal subjects. Therefore, we are now proposing a larger study, utilizing Illumina Omni Express chips, to look for genetic associations. We have partnered with the Reasons for Geographic and Racial Differences in Stroke study (REGARDS), where nearly half of the cohort are African-Americans. This will be one of the few GWAS being performed in only African-Americans, and will provide valuable genetic information to link with neutropenia and possibly other conditions/diseases. Genotyping was performed by the Johns Hopkins University Center for Inherited Disease Research (CIDR). Quality control of the genotypic and phenotypic data was performed through a collaboration between CIDR and the Genetics Coordinating Center, Department of Biostatistics at the University of Washington, which is funded by a federal contract supported by 14 NIH Institutes (HHSN268200782096C).

  Study phs000507

• National Institute of Mental Health (NIMH) Duke Cognition Cohort

  The overall goal is to identify genetic variants influencing normal variation between humans, with a focus on cognitive and neurosensory traits. Because of the focus of funding agencies on disease, very few studies of the genetics of non-disease traits have been performed. The genetic variation underlying the vast majority of differences between humans therefore remains not only undiscovered, but also unexplored. We have assessed >1,200 healthy volunteers for >70 diverse, non-disease phenotypes, with a focus on cognitive and neurosensory traits that are understudied and seem to have a strong biological basis. Our study includes measurements of face recognition, night vision, cognitive performance, auditory pitch discrimination, contagious yawn susceptibility, time perception, sense of direction, taste preferences, personality, sexual behaviors, sleep habits, acne, headache locations, synesthesia, and teeth sensitivity. This method is very different from the focus of most studies on collecting cohorts of patients with disease and controls with minimal phenotypic information. Because we phenotype the same healthy volunteers for multiple highly variable yet heritable traits, we can perform genetic analyses on a large number of phenotypes by just investing once in sequencing the DNA of these participants. An additional >2,000 participants in our cohort have been measured just for cognitive performance instead of for the more extensive phenotyping. Most of the genetic studies in this cohort have been about cognitive perfromance. The number of participants with genetic data generated who have undergone the more extensive phenotyping is limited. Our studies of the more novel traits like contagious yawning have therefore focused more on correlations between different phenotypes until we have a sufficient sample size to truly attempt to make genetic discoveries. . The dataset also includes two small challenge studies. In one study, the cognitive performance of 150 healthy volunteers was measured before and after an acute dose of the antiepileptic drug topiramate. In the other study, the cognitive performance of 13 healthy volunteers was measured before and after 24 hours of sleep deprivation.

  Study phs001406

• NHLBI TOPMed: Outcome Modifying Genes in Sickle Cell Disease (OMG)

  Sickle cell disease (SCD) is caused by homozygosity for a single mutation of the beta hemoglobin gene. Despite the constancy of this genetic abnormality, the clinical course of patients with SCD is remarkably variable. SCD can affect the function and cause the failure of multiple organ systems through the pathophysiologic processes of vaso-occlusion and hemolysis. These pathophysiological processes are complex and expected to impact multiple organ systems in a variety of ways. This study, therefore, was designed to identify genetic factors that predispose SCD patients to develop specific end-organ complications and to experience more or less severe clinical courses. We enrolled > 700 patients with Hb SS, Hb S-beta0 thalassemia and HbSC being followed primarily at three southeastern U.S. regional institutions (Duke University Medical Center, University of North Carolina Medical Center, and Emory University Medical Center). Medical information obtained included the presence or absence of specific targeted outcomes (overall disease severity as well as specific types of end organ damage). Clinical data include medical status (history, physical, examination, and laboratory results) and information regarding potentially confounding environmental factors. Limited plasma samples are available for correlative studies (e.g. of cytokine levels, coagulation activation). Targeted SNP for candidate gene analysis as well as GWAS has been performed on most samples. Whole genome sequencing has been conducted through the TOPMed Consortium. The subjects in this analysis were collected as part of a larger study, "Outcome Modifying Genes in Sickle Cell Disease" (OMG-SCD) aimed at identifying genetic modifiers for sickle cell disease. More information about the study can be found in Elmariah et al. (2014), PMID: 24478166. Clinical and genetic data have been used to identify genetic characteristics predisposing patients with SCD to a more or less severe overall clinical course as well as to individual organ-specific complications. It is anticipated that identification of such genetic factors will reveal new therapeutic targets individualized to specific complications of SCD, leading to improved outcomes and increased life expectancy for patients with SCD.

  Study phs001608

• National Institute on Aging (NIA) SardiNIA Study

  Sardinia is the second largest island in the Mediterranean and constitutes a genetically isolated founder population. This population has aided in the identification of genes involved in several Mendelian disorders and is attractive for genetic studies due to its organization in long-established settlements that developed from an initial group of founder settlers (~1,000) thousands of years ago. The current study has recruited 6,148 Sardinians aged 14 and older, from a cluster of four towns in the Lanusei Valley in the Ogliastra region of the province of Nuoro. This sample corresponds to approximately 62% of the population eligible in the area for recruitment. Information collected during enrollment allowed the individuals to be organized into 711 complex pedigrees, each up to five generations deep, with an average kinship coefficient of 0.1628. All volunteers have been characterized for 98 quantitative traits. Traits include anthropomorphic measures, plasma and serum markers (including cholesterol and other markers of cardiovascular disease), and personality traits (using the five-factor model). The main goal of the study is to examine phenotypic similarities between relatives that yield information on the overall contributions of genes to trait variability. Data given here provide p-values for 98 traits studied in 1,412 individuals, based on genotyping with the Affymetrix 500K chip and imputed markers using the HapMap population as a reference (N=2,259,179). Sharing this genome assessment data at high level of resolution for a variety of quantitative traits will be useful for other groups to validate newly observed associations and to investigate possible pleiotropic effects. For ulterior information, and in particular for any individual genotype information, a formal request should be addressed to the Steering Committee, c/o David Schlessinger, Chief, Laboratory of Genetics, National Institute on Aging, National Institutes of Health, NIH Biomedical Research Center, 251 Bayview Blvd., Suite 100 Baltimore, MD 21224 USA and should include IRB approval of a detailed proposal, along with a signed statement guaranteeing that no attempt will be made to identify any individual participant.

  Study phs000338

• Investigation of Brain Nitrogen Metabolism in Partial Ornithine Transcarbamylase Deficiency (OTCD) Using 1H MRS, DTI, and fMRI

  This is a case controlled, observational study. This project studies cognitive and motor dysfunction in adult and pediatric patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation (outside of the newborn period) of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non-invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies ranged from ages 7-60 years and were compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

  Study phs001296

• National Institutes of Health The Cancer Genome Atlas (TCGA)

  The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

  Study phs000178

• National Eye Institute (NEI) Ocular Hypertension Treatment Study (OHTS)

  The Ocular Hypertension Treatment Study (OHTS) is an National Eye Institute-sponsored multi-center, randomized, prospective treatment trial designed to determine whether lowering intraocular pressure (IOP) in individuals with ocular hypertension delays or prevents the development of primary open angle glaucoma (POAG). A total of 1,636 individuals with ocular hypertension between 40 and 80 years old were enrolled in the study. In addition to ocular hypertension, subjects in the OHTS were required to have normal optic nerve appearance as determined by the OHTS Optic Disc Reading Center and normal and reliable visual field tests at the time of enrollment by the OHTS Visual Field Reading Center. OHTS subjects were randomly assigned to either an observational group which received close observation or a topical medication group which received medication as needed to achieve a 20% reduction in IOP from their baseline levels. Subjects then were examined at regular intervals for optic disc cupping or visual field defects. Other clinical measures were also obtained from OHTS subjects including central corneal thickness (CCT) and intraocular pressure. The primary outcome monitored for the OHTS was the development of glaucoma in one or both eyes as defined by reproducible visual field abnormality or reproducible optic disc deterioration attributed to POAG by the masked OHTS Endpoint Committee. The OHTS study design has been reported in detail (Gordon, 1999; PMID: 10326953). The OHTS confirmed that ocular hypertension is a risk factor for developing POAG and showed that lowering IOP reduced the risk for developing POAG (Kass, 2002; PMID: 12049574). The OHTS also demonstrated that thin CCT is a significant risk factor for the development of POAG (Gordon, 2002; PMID: 12049575). Blood samples were also collected from 1,077 OHTS participants for an ancillary genetics study. DNA was prepared from these samples and used in a genome-wide association scan (GWAS) designed to identify genetic factors that control the magnitude of quantitative features of glaucoma (baseline IOP, baseline cup-to-disc ratio, and CCT). Genotypes from the GWAS and these clinical data (IOP, cup-to-disc ratio, and CCT) have been provided to dbGaP.

  Study phs000240

• Exploring the Genetic Variants Associated with Brain Growth in Children

  Understanding the genetic factors that control brain growth during childhood and adolescence is a priority for neuroscience. Its importance lies partly in the finding that disturbances in the course of brain development characterizes many common childhood behavioral problems. Recent advances in neuroimaging such as the use of non-invasive magnetic resonance imaging have provided a chance to define these trajectories in the living child. The intramural programs of the NIMH and NHGRI have conducted repeated neuroanatomic imaging on children along with the banking of DNA, providing a cohort which is studied for defining developmental trajectories of the brain. A central goal of this cohort is to define the disturbances in brain development that are linked with common behavioral problems, such as excessive impulsivity, hyperactivity and inattention. Studies have demonstrated that problems in these domains are distributed across the entire population and that children with Attention Deficit Hyperactivity Disorder (ADHD) lie at the extreme end of these behavioral dimensions. We found a similar dimensionality in the development of brain regions that are associated with these behavioral problems. Specifically, we showed that the rate of change in both the lateral prefrontal cortex and interconnected striatum during childhood and adolescence was linked to the severity of symptoms of hyperactivity and impulsivity. As symptoms increased, the rate of growth of both structures decreased. The lateral prefrontal cortex and striatum are core components of richly interconnected 'loops' that support a host of cognitive processes, including attention, cognitive control and motor planning. Anomalies in these structures and their connections have been implicated in many childhood behavioral problems, including ADHD. In summary, we aim to identify the common and rare genetic variants that are associated with the developmental trajectories of the lateral-prefrontal cortex and striatum. Identifying genetic variants influencing the growth of these structures may reveal the biological mechanisms underlying dysregulated control of attention, impulse and activity level, which in the extreme constitute ADHD. The study thus could inform our understanding of neurobiology underpinning one of the most common neuropsychiatric disorders of childhood.

  Study phs000962

• Acute Respiratory Distress Syndrome Clinical Network: Fluid and Catheter Treatment Trial (ARDSNet FACTT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-FACTT include plasma, DNA, and serum. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: This study evaluated the benefits and risks of Pulmonary Artery Catheters (PACs) in patients with established acute lung injury in a trial comparing hemodynamic management guided by a PAC with hemodynamic management guided by a central venous catheter (CVC) using an explicit management protocol.Background: Optimal fluid management in patients with acute lung injury is unknown. Diuresis or fluid restriction may improve lung function but could jeopardize extrapulmonary organ perfusion.Participants: This randomized study compared a conservative and a liberal strategy of fluid management using explicit protocols applied for seven days in 1000 patients with acute lung injury. The primary end point was death at 60 days. Secondary end points included the number of ventilator-free days and organ-failure-free days and measures of lung physiology. Design: Participants were randomly assigned to a strategy involving either conservative or liberal use of fluids with concealed allocation in permuted blocks of eight with the use of an automated system. Participants were simultaneously and randomly assigned to receive either a pulmonary-artery catheter or a central venous catheter in a two-by-two factorial design.Conclusions: There was no significant difference in the primary outcome of 60-day mortality; however, the conservative strategy of fluid management was associated with improved lung function and shortened the duration of mechanical ventilation and intensive care without increasing non-pulmonary organ failures. These results support the use of a conservative strategy of fluid management in patients with acute lung injury. (NEJM June 15, 2006; Vol 354, No. 24, pp 2564-75; NEJM May 25, 2006; Vol 354, No. 21, pp 2213-24)

  Study phs004165

• UK10K NEURO IOP COLLIER

  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. The Genetics and Psychosis (GAP) set consists of samples from subjects with schizophrenia, ascertained as a new-onset sample. This set is of UK origin, with data on cognition, brain imaging and other endophenotypes. The Maudsley twin series consists of probands ascertained from the Maudsley Twin Register, defined as patients of multiple birth who had suffered psychotic symptoms. This set is of UK origin, with data on cognition, brain imaging and other endophenotypes, with DNA available from an MZ or DZ affected or unaffected co-twin. The Maudsley family study (MFS) consists of over 250 families who have a history of schizophrenia or bipolar disorder Within the Maudsley Family Study, biological markers of psychosis include neuropsychological tests, Evoked Response Potentials Tests (ERPs), MRI scans, dermatoglyphics and eye tracking. Early risk factors for psychosis and clinical symptoms are also investigated. This set is of UK origin, with DNA available from both affected and unaffected relatives in many of the probands. For further information on this study please contact David Collier (david.collier@kcl.ac.uk).

  Study EGAS00001000121

• APOBEC mutagenesis is a common process in normal human small intestine

  The single base substitution mutational signatures SBS2 and SBS13, likely caused by APOBEC cytosine deaminases, are common in many human cancer types. However, the stimulus activating APOBEC mutagenesis is unknown and understanding of when it occurs in the progression from normal to cancer cell is limited. Here, as part of a wider survey of human tissues, we whole genome sequenced 342 microdissected normal epithelial crypts from the small intestines of 39 individuals. SBS2/13 mutations were present in 17% normal small intestine crypts and were likely due to APOBEC3A activity. Localised clusters of SBS2/13 mutations (kataegis) were also commonly found. APOBEC mutation burdens were variable between individuals and between crypts from the same individual. Crypts with SBS2/13 often had immediate crypt neighbours without SBS2/13, suggesting that the underlying cause of SBS2/13 is cell-intrinsic rather than a widely distributed microenvironmental exposure, or needs to be permitted by cell-intrinsic conditions. APOBEC mutagenesis occurred throughout the human lifespan, including in young children, and was episodic with a small number of episodes occurring during the life history of a single cell. The results indicate that APOBEC mutagenesis is more common in the small intestine epithelium than in many other cell types, and is an episodic process in vivo initiated or permitted by cell intrinsic factors.

  Dataset EGAD00001008764

• Cellular indexing of transcriptomes and epitopes sequencing of peritoneal fluid from patients with achalasia

  The data published here contains cellular indexing of transcriptomes and epitopes sequencing (CITEseq) using the oligo-tagged TotalSeq™-B Human Universal Cocktail, V1.0 from BioLegend on peritoneal fluid (PF) from patients with achalasia. Sequencing was performed in a paired-ended fashion on the NovaSeq6000. Below an overview of the epitopes to oligotags as obtained from BioLegend: DNA_ID Description clone Sequence Ensembl ID B0006 anti-human CD86 IT2.2 GTCTTTGTCAGTGCA ENSG00000114013 B0007 anti-human CD274 (B7-H1, PD-L1) 29E.2A3 GTTGTCCGACAATAC ENSG00000120217 B0020 anti-human CD270 (HVEM, TR2) 122 TGATAGAAACAGACC ENSG00000157873 B0023 anti-human CD155 (PVR) SKII.4 ATCACATCGTTGCCA ENSG00000073008 B0024 anti-human CD112 (Nectin-2) TX31 AACCTTCCGTCTAAG ENSG00000130202 B0026 anti-human CD47 CC2C6 GCATTCTGTCACCTA ENSG00000196776 B0029 anti-human CD48 BJ40 CTACGACGTAGAAGA ENSG00000117091 B0031 anti-human CD40 5C3 CTCAGATGGAGTATG ENSG00000101017 B0032 anti-human CD154 24-31 GCTAGATAGATGCAA ENSG00000102245 B0033 anti-human CD52 HI186 CTTTGTACGAGCAAA ENSG00000169442 B0034 anti-human CD3 UCHT1 CTCATTGTAACTCCT ENSG00000167286 B0046 anti-human CD8 SK1 GCGCAACTTGATGAT ENSG00000153563 B0047 anti-human CD56 (NCAM) 5.1H11 TCCTTTCCTGATAGG ENSG00000149294 B0050 anti-human CD19 HIB19 CTGGGCAATTACTCG ENSG00000177455 B0052 anti-human CD33 P67.6 TAACTCAGGGCCTAT ENSG00000105383 B0053 anti-human CD11c S-HCL-3 TACGCCTATAACTTG ENSG00000140678 B0058 anti-human HLA-A,B,C W6/32 TATGCGAGGCTTATC ENSG00000206503 B0063 anti-human CD45RA HI100 TCAATCCTTCCGCTT ENSG00000081237 B0064 anti-human CD123 6H6 CTTCACTCTGTCAGG ENSG00000185291 B0066 anti-human CD7 CD7-6B7 TGGATTCCCGGACTT ENSG00000173762 B0068 anti-human CD105 43A3 ATCGTCGAGAGCTAG ENSG00000106991 B0070 anti-human/mouse CD49f GoH3 TTCCGAGGATGATCT ENSG00000091409 B0071 anti-human CD194 (CCR4) L291H4 AGCTTACCTGCACGA ENSG00000183813 B0072 anti-human CD4 RPA-T4 TGTTCCCGCTCAACT ENSG00000010610 B0073 anti-mouse/human CD44 IM7 TGGCTTCAGGTCCTA ENSG00000026508 B0081 anti-human CD14 M5E2 TCTCAGACCTCCGTA ENSG00000170458 B0083 anti-human CD16 3G8 AAGTTCACTCTTTGC ENSG00000203747 B0085 anti-human CD25 BC96 TTTGTCCTGTACGCC ENSG00000134460 B0087 anti-human CD45RO UCHL1 CTCCGAATCATGTTG ENSG00000081237 B0088 anti-human CD279 (PD-1) EH12.2H7 ACAGCGCCGTATTTA ENSG00000188389 B0089 anti-human TIGIT (VSTM3) A15153G TTGCTTACCGCCAGA ENSG00000181847 B0090 Mouse IgG1, κ isotype MOPC-21 GCCGGACGACATTAA B0091 Mouse IgG2a, κ isotype MOPC-173 CTCCTACCTAAACTG B0092 Mouse IgG2b, κ isotype MPC-11 ATATGTATCACGCGA B0095 Rat IgG2b, κ isotype RTK4530 GATTCTTGACGACCT B0100 anti-human CD20 2H7 TTCTGGGTCCCTAGA ENSG00000156738 B0101 anti-human CD335 (NKp46) 9E2 ACAATTTGAACAGCG ENSG00000189430 B0124 anti-human CD31 WM59 ACCTTTATGCCACGG ENSG00000261371 B0127 anti-Human Podoplanin NC-08 GGTTACTCGTTGTGT ENSG00000162493 B0134 anti-human CD146 P1H12 CCTTGGATAACATCA ENSG00000076706 B0136 anti-human IgM MHM-88 TAGCGAGCCCGTATA ENSG00000211899 B0138 anti-human CD5 UCHT2 CATTAACGGGATGCC ENSG00000110448 B0141 anti-human CD195 (CCR5) J418F1 CCAAAGTAAGAGCCA ENSG00000160791 B0142 anti-human CD32 FUN-2 GCTTCCGAATTACCG ENSG00000143226 B0143 anti-human CD196 (CCR6) G034E3 GATCCCTTTGTCACT ENSG00000112486 B0144 anti-human CD185 (CXCR5) J252D4 AATTCAACCGTCGCC ENSG00000160683 B0145 anti-human CD103 (Integrin αE) Ber-ACT8 GACCTCATTGTGAAT ENSG00000083457 B0146 anti-human CD69 FN50 GTCTCTTGGCTTAAA ENSG00000110848 B0147 anti-human CD62L DREG-56 GTCCCTGCAACTTGA ENSG00000188404 B0149 anti-human CD161 HP-3G10 GTACGCAGTCCTTCT ENSG00000111796 B0151 anti-human CD152 (CTLA-4) BNI3 ATGGTTCACGTAATC ENSG00000163599 B0152 anti-human CD223 (LAG-3) 11C3C65 CATTTGTCTGCCGGT ENSG00000089692 B0153 anti-human KLRG1 (MAFA) SA231A2 CTTATTTCCTGCCCT ENSG00000139187 B0154 anti-human CD27 O323 GCACTCCTGCATGTA ENSG00000139193 B0155 anti-human CD107a (LAMP-1) H4A3 CAGCCCACTGCAATA ENSG00000185896 B0156 anti-human CD95 (Fas) DX2 CCAGCTCATTAGAGC ENSG00000026103 B0158 anti-human CD134 (OX40) Ber-ACT35 (ACT35) AACCCACCGTTGTTA ENSG00000186827 B0159 anti-human HLA-DR L243 AATAGCGAGCAAGTA ENSG00000204287 B0160 anti-human CD1c L161 GAGCTACTTCACTCG ENSG00000158481 B0161 anti-human CD11b ICRF44 GACAAGTGATCTGCA ENSG00000169896 B0162 anti-human CD64 10.1 AAGTATGCCCTACGA ENSG00000150337 B0163 anti-human CD141 (Thrombomodulin) M80 GGATAACCGCGCTTT ENSG00000178726 B0164 anti-human CD1d 51.1 TCGAGTCGCTTATCA ENSG00000158473 B0165 anti-human CD314 (NKG2D) 1D11 CGTGTTTGTTCCTCA ENSG00000213809 B0167 anti-human CD35 E11 ACTTCCGTCGATCTT ENSG00000203710 B0168 anti-human CD57 Recombinant QA17A04 AACTCCCTATGGAGG ENSG00000109956 B0170 anti-human CD272 (BTLA) MIH26 GTTATTGGACTAAGG ENSG00000186265 B0171 anti-human/mouse/rat CD278 (ICOS) C398.4A CGCGCACCCATTAAA ENSG00000163600 B0174 anti-human CD58 (LFA-3) TS2/9 GTTCCTATGGACGAC ENSG00000116815 B0176 anti-human CD39 A1 TTACCTGGTATCCGT ENSG00000138185 B0179 anti-human CX3CR1 K0124E1 AGTATCGTCTCTGGG ENSG00000168329 B0180 anti-human CD24 ML5 AGATTCCTTCGTGTT ENSG00000272398 B0181 anti-human CD21 Bu32 AACCTAGTAGTTCGG ENSG00000117322 B0185 anti-human CD11a TS2/4 TATATCCTTGTGAGC ENSG00000005844 B0187 anti-human CD79b (Igβ) CB3-1 ATTCTTCAACCGAAG ENSG00000007312 B0189 anti-human CD244 (2B4) C1.7 TCGCTTGGATGGTAG ENSG00000122223 B0206 anti-human CD169 7-239 TACTCAGCGTGTTTG ENSG00000088827 B0214 anti-human/mouse integrin β7 FIB504 TCCTTGGATGTACCG ENSG00000139626 B0215 anti-human CD268 (BAFF-R) 11C1 CGAAGTCGATCCGTA ENSG00000159958 B0216 anti-human CD42b HIP1 TCCTAGTACCGAAGT ENSG00000203618 B0217 anti-human CD54 HA58 CTGATAGACTTGAGT ENSG00000090339 B0218 anti-human CD62P (P-Selectin) AK4 CCTTCCGTATCCCTT ENSG00000174175 B0219 anti-human CD119 (IFN-γ R α chain) GIR-208 TGTGTATTCCCTTGT ENSG00000027697 B0224 anti-human TCR α/β IP26 CGTAACGTAGAGCGA B0236 Rat IgG1, κ isotype RTK2071 ATCAGATGCCCTCAT B0238 Rat IgG2a, κ Isotype RTK2758 AAGTCAGGTTCGTTT B0242 anti-human CD192 (CCR2) K036C2 GAGTTCCCTTACCTG ENSG00000121807 B0246 anti-human CD122 (IL-2Rβ) TU27 TCATTTCCTCCGATT ENSG00000100385 B0352 anti-human FcεRIα AER-37 (CRA-1) CTCGTTTCCGTATCG ENSG00000179639 B0353 anti-human CD41 HIP8 ACGTTGTGGCCTTGT ENSG00000005961 B0355 anti-human CD137 (4-1BB) 4B4-1 CAGTAAGTTCGGGAC ENSG00000049249 B0358 anti-human CD163 GHI/61 GCTTCTCCTTCCTTA ENSG00000177575 B0359 anti-human CD83 HB15e CCACTCATTTCCGGT ENSG00000112149 B0363 anti-human CD124 (IL-4Rα) G077F6 CCGTCCTGATAGATG ENSG00000077238 B0364 anti-human CD13 WM15 TTTCAACGCCCTTTC ENSG00000166825 B0367 anti-human CD2 TS1/8 TACGATTTGTCAGGG ENSG00000116824 B0368 anti-human CD226 (DNAM-1) 11A8 TCTCAGTGTTTGTGG ENSG00000150637 B0369 anti-human CD29 TS2/16 GTATTCCCTCAGTCA ENSG00000150093 B0370 anti-human CD303 (BDCA-2) 201A GAGATGTCCGAATTT ENSG00000198178 B0371 anti-human CD49b P1E6-C5 GCTTTCTTCAGTATG ENSG00000164171 B0373 anti-human CD81 (TAPA-1) 5A6 GTATCCTTCCTTGGC ENSG00000110651 B0384 anti-human IgD IA6-2 CAGTCTCCGTAGAGT ENSG00000211898 B0385 anti-human CD18 TS1/18 TATTGGGACACTTCT ENSG00000160255 B0386 anti-human CD28 CD28.2 TGAGAACGACCCTAA ENSG00000178562 B0389 anti-human CD38 HIT2 TGTACCCGCTTGTGA ENSG00000004468 B0390 anti-human CD127 (IL-7Rα) A019D5 GTGTGTTGTCCTATG ENSG00000168685 B0391 anti-human CD45 HI30 TGCAATTACCCGGAT ENSG00000081237 B0393 anti-human CD22 S-HCL-1 GGGTTGTTGTCTTTG ENSG00000012124 B0394 anti-human CD71 CY1G4 CCGTGTTCCTCATTA ENSG00000072274 B0396 anti-human CD26 BA5b GGTGGCTAGATAATG ENSG00000197635 B0398 anti-human CD115 (CSF-1R) 9-4D2-1E4 AATCACGGTCCTTGT ENSG00000182578 B0404 anti-human CD63 H5C6 GAGATGTCTGCAACT ENSG00000135404 B0406 anti-human CD304 (Neuropilin-1) 12C2 GGACTAAGTTTCGTT ENSG00000099250 B0407 anti-human CD36 5-271 TTCTTTGCCTTGCCA ENSG00000135218 B0408 anti-human CD172a (SIRPα) 15-414 CGTGTTTAACTTGAG ENSG00000198053 B0419 anti-human CD72 3F3 CAGTCGTGGTAGATA ENSG00000137101 B0420 anti-human CD158 (KIR2DL1/S1/S3/S5) HP-MA4 TATCAACCAACGCTT ENSG00000125498 B0446 anti-human CD93 VIMD2 GCGCTACTTCCTTGA ENSG00000125810 B0575 anti-human CD49a TS2/7 ACTGATGGACTCAGA ENSG00000213949 B0576 anti-human CD49d 9F10 CCATTCAACTTCCGG ENSG00000115232 B0577 anti-human CD73 (Ecto-5'-nucleotidase) AD2 CAGTTCCTCAGTTCG ENSG00000135318 B0579 anti-human CD9 HI9a GAGTCACCAATCTGC ENSG00000010278 B0581 anti-human TCR Vα7.2 3C10 TACGAGCAGTATTCA B0582 anti-human TCR Vδ2 B6 TCAGTCAGATGGTAT B0591 anti-human LOX-1 15C4 ACCCTTTACCGAATA ENSG00000173391 B0592 anti-human CD158b (KIR2DL2/L3, NKAT2) DX27 GACCCGTAGTTTGAT ENSG00000243772 B0599 anti-human CD158e1 (KIR3DL1, NKB1) DX9 GGACGCTTTCCTTGA ENSG00000167633 B0822 anti-human CD142 NY2 CACTGCCGTCGATTA ENSG00000117525 B0830 anti-human CD319 (CRACC) 162.1 AGTATGCCATGTCTT ENSG00000026751 B0864 anti-human CD352 (NTB-A) NT-7 AGTTTCCACTCAGGC ENSG00000162739 B0867 anti-human CD94 DX22 CTTTCCGGTCCTACA ENSG00000134539 B0871 anti-human CD162 KPL-1 ATATGTCAGAGCACC ENSG00000110876 B0896 anti-human CD85j (ILT2) GHI/75 CCTTGTGAGGCTATG ENSG00000104972 B0897 anti-human CD23 EBVCS-5 TCTGTATAACCGTCT ENSG00000104921 B0902 anti-human CD328 (Siglec-7) 6-434 CTTAGCATTTCACTG ENSG00000168995 B0918 anti-human HLA-E 3D12 GAGTCGAGAAATCAT ENSG00000204592 B0920 anti-human CD82 ASL-24 TCCCACTTCCGCTTT ENSG00000085117 B0944 anti-human CD101 (BB27) BB27 CTACTTCCCTGTCAA ENSG00000134256 B1046 anti-human CD88 (C5aR) S5/1 GCCGCATGAGAAACA ENSG00000197405 B1052 anti-human CD224 KF29 CTGATGAGATGTCAG ENSG00000100031

  Dataset EGAD50000000252

• Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss

  The Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss, which constitute the Epidemiology of the Weiss Cohort Projects, consist of a series of inter-connected projects, building upon a set of cohort projects of various groups, mainly drug users from medication-assisted treatment programs, that Dr. Stanley H. Weiss first developed in the 1980’s plus several newer initiatives, each with an array of collaborators. Beginning in the 1980’s, Dr. Stanley H. Weiss started several long-term studies of persons who inject drugs (PWID) across the United States, ultimately enrolling over 10,000 participants through the early 1990’s with an average age then in their 30’s. About a quarter were enrolled from sites in New Jersey (NJ). These studies included the first testing of PWID for the human immunodeficiency virus (HIV) and the human T-cell lymphotropic viruses (HTLV I and HTLV II). Cumulative past support (initiation thru ~ 1999) for these cohort studies included ~ $20 million from intramural resources from the National Cancer Institute (NCI) and the National Institute on Drug Abuse (NIDA), plus multiple grants and in-kind support from the New Jersey Department of Health (NJDOH) totaling ~ $1 million. The Weiss Cohort Projects include the first large AIDS-era cohorts to include women at high risk for HIV. A high percentage of subjects in these studies are black or Latino. Thus, this is an ethnically diverse US cohort, with a high proportion of women included. These subjects are at high risk of parenteral and sexual infection from both drug use and sexual practices. Samples from other studies conducted by Dr. Weiss, in which detailed interviews were conducted, are included as controls (persons documented by us not to have a history of opioid drug use). As one of our groups of subjects have many persons of Haitian ancestry, we specifically included some Haitians who had never used opioids as controls. Our documentation includes such ancestry. These cohorts demonstrated high rates of HIV and HTLV-II infection in PWIDs, including one study initiated in 1981 with confirmation in the later cohorts. In the first two decades of these studies, among numerous publications was the first study showing a very high rate of hepatitis C infection among PWIDs. An example of how the studies’ long-time horizon proved essential was that it first became possible to test whether a person had ever been infected with hepatitis C virus (HCV), as well as how much HCV was in each person’s blood, many years after the specimens were collected. This allowed HCV amounts in blood to be compared for subjects who had died of liver disease early in the study versus those who survived. Then a sequence of published papers culminated in demonstrating, using a nested case-control design, that a high baseline HCV titer was predictive of early progression to death from end-stage liver failure. Outcomes related to HCV (end stage liver disease and hepatocellular carcinoma) remain under study. In the original cohort studies, the mean age at enrollment was ~ 33 years old, so that those still alive in 2022 are mainly now ~ 60 - 75 years old. Many participants have already died. The tincture of time has led to subjects reaching ages when many more are dying from a wide array of outcomes, including from many chronic diseases (including cancer) as well as from infectious agents (especially HIV, HCV) or drug overdose. Renewed collaboration with local drug treatment programs has led to new field-based studies, including examination of some currently evolving problems among drug users. Dr. Weiss joined the National Institute on Drug Abuse (NIDA) Genetics Consortium (NGC) in 2017, and through the NIDA project officer has had access to NGC contract resources (see below). NIH Certificate of Confidentiality, CC-DA-16-214 (attached) protects these studies. Past arrangements related to data on our subjects leads to restrictions on the use of data emanating from our study, such as potential commercialization and restrictions on whom may access and use these data. NIDA Genetics Consortium (NGC) resources further support these endeavors and will be used as part of the NGC analyses studying the genetics of substance use. Study participants signed informed consent for the information collected from them to be used with no time limit and for biologic specimens collected from them to be used without restriction in future research. Serum samples were collected from participants, and from many also plasma, white blood cells and/or urine samples. About 100,000 vials were stored. All specimens have been continuously preserved at sufficiently cold temperatures to prevent deterioration, and many subjects separated white blood cells were processed and frozen in such a way as to maintain viability. Detailed data from the participants has been accumulated over time, and in general, linkage has been retained in each sub-study in accordance with the consent forms and protocols. For some participants, specimens were collected at multiple times (that is, sequential specimens). Multiple specimens from a single person exist in this database, and efforts at de-duplication remain ongoing. Dr. Weiss should be contacted if an investigator requires unique individuals since: • Multiple phases of enrollment occurred, and as our prospective follow-up continues; Dr. Weiss may identify new instances of multiple enrollment. • Some persons are related to each other. • In general, in this dataset for dbGaP, only a single specimen/record form a given person is included. Advances in laboratory testing techniques now permit innovative new uses for our linked research biospecimen repository. The ongoing focus of an interdisciplinary research program based on these cohorts relates subjects’ diseases, behaviors, medical history, and outcomes with biological and exposure markers. Participants’ use of various substances was ascertained on study enrollments, many serially over time. Quantitative frequency of use data, also sometimes sequential over time, were ascertained. Active ascertainment of outcomes is being conducted, including matching to mortality and cancer databases. Investigators interested in collaborations on specific outcomes (which is not part of this dbGaP dataset) or in the use of our stored specimens are encouraged to contact the principal investigator, Dr. Weiss. The processing of the genomic data was done in conjunction with NIDA, and in accordance with some longstanding data cleaning steps used by NIDA in the NIDA Genetics Consortium (NGC), a group to which we shall be contributing these data for collaborative analyses. Since there is the potential for these steps to introduce certain types of potential biases, we summarize these here. Under contract from NIDA, cryopreserved sera or plasma (-80 C) or cells (in liquid nitrogen) were used, with most stored having been stored for 30 to 40 years in our biorepository. In the case of serum or plasma, in which only (largely) cell-free DNA fragments were available, DNA was extracted and restored prior to amplification. Industry standard DNA amplification techniques were done on all samples prior to genotyping in accord with established protocols of the NIDA Genetics Consortium. Our genotype data were run and processed on the Illumina Infinium OmniExpress_v_1.3 array. This array has 714,238 SNPs, and was designed many years ago. There were 628 SNPs on the array that do not correspond to any chromosome position, and these were removed. Genotype data were submitted by NIDA’s contracted genotyping laboratory in six batches over time to NIDA’s contracted dbGaP data management group, which conducted quality control (QC) analyses. QC analysis included an assessment of batch effects on for five of the six batches. (One of the batches, with only 12 samples, was too small for QC analysis of batch effects.) Standard NIDA Genetic Consortium cleaning was performed. Samples with a call rate <.85 were removed. Only one sample per person was retained. When more than one specimen was genotyped from one subject, only the sample with the higher call rate was retained (provided, of course, that that call rate was ≥ 0.85). We have retained some people we know are related, including some found to have been related through genotyping; the pedigree file describes those relationships. In summary, key cleaning steps include: 1. Using PLINK to check gender discrepancy. 2. Using PREST-PLUS and KING (Kinship-based Inference for GWAS) to check relatedness. 3. Using PEDCHECK and PLINK to check/zero-out Mendelian error. 4. Using PLINK to perform sample QC, SNP QC, along with KING to perform chromosome X and chromosome Y QC. 5. SNP-QC: Batch-effect: 5 Batches were compared (one batch, with few samples, was not). These five batches were compared to each other in all ten possible pairs, one batch vs. another batch, examining SNP allele frequency discrepancies by population (from GRAF), Fisher Exact Allelic test, with the criterion of p<5e-8 for removal. 6. SNP-QC: discordant SNPs in QC duplicates. Compared 25 QC duplicated samples with call rate > 0.95, removed SNPs with 3+ discordance. 7. There were 1,056 SNPs that were monomorphic; these have been retained so they can be included in analyses in which our dbGaP data are combined with those from other cohorts (in the latter of which those SNPs may not be monomorphic). The final cleaned dataset submitted has 8,898 samples and 606,793 SNPs.

  Study phs002140

• EGAD00000000003

  WTCCC1 project Bipolar Disorder (BD) samples

  Dataset EGAD00000000003

• Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Dataset EGAD00001000284

• Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Dataset EGAD00001000290

• Sensitive circulating tumor DNA based residual disease detection in epithelial ovarian cancer

  We analyzed 264 plasma samples collected between June 2016 and September 2021 from 63 epithelial ovarian cancer patients using tumor-guided plasma cell-free DNA analysis to detect residual disease after treatment.

  Dataset EGAD50000000360

• The natural history of clonal haematopoiesis: colony WGS

  Whole-genome sequencing of 288 single-cell-derived blood colonies from 3 elderly individuals with clonal haematopoiesis.

  Dataset EGAD00001007684

• HV31 - PacBio continuous long read (CLR) sequencing

  PacBio continuous long read (CLR) sequencing data for individual HV31 generated on PacBio Sequel II instrument, using DNA from CD14+ monocytes, to a sequencing depth of ~35×. Sequencing was performed at the Wellcome Sanger Institute.

  Dataset EGAD00001007047

• 10x Genomics Single Cell Gene Expression for SA535X6XB03099

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009116

• 10x Genomics Single Cell Gene Expression for SA535X4XB05462

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009115

• Target pilot trial

  In vitro and in vivo drug screens of tumor cells identify novel therapies for high-risk child cancer

  Dataset EGAD00001008358

• 10x Genomics Single Cell Gene Expression for SA535X6XB03101

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009149

• 10x Genomics Single Cell Gene Expression for SA535X5XB02891

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009155

• 10x Genomics Single Cell Gene Expression for SA535X5XB02895

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009156

• 10x Genomics Single Cell Gene Expression for SA604X9XB02425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 9

  Dataset EGAD00001009159

• 10x Genomics Single Cell Gene Expression for SA535X4XB02498

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009152

• Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) tumor patient

  Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015291

• WXS dataset of Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

  Creation of living organoid biobank for ewing and ewing-like sarcomas

  Dataset EGAD00001015417

• Clinical data

  Clinical data from this cohort of patients, including hormone sensitive or castration resistant prostate cancer, overall survival, NMF subtypes, tumor TMB, prior treatment status, PD-L1 IC and TC scores from SP142 and SP263 as well as percentage of CD8 IHC at tumor center.

  Dataset EGAD00001008761

• Embryonal Rhabdomyosarcoma sequencing data

  This dataset contains samples from 9 patients with embryonal rhabdomyosarcoma. 9 samples have whole exome tumor data (one has multiple). 7 samples have tumor RNAseq data. 1 sample has matched normal dna sequence data

  Dataset EGAD00001007939

• 10x Genomics Single Cell Gene Expression for SA1056

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 116.126

  Dataset EGAD00001009112

• 10x Genomics Single Cell Gene Expression for SA604X6XB01979

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 6

  Dataset EGAD00001009117

• 10x Genomics Single Cell Gene Expression for SA604X7XB02089

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 7

  Dataset EGAD00001009119

• 10x Genomics Single Cell Gene Expression for SA609X6XB01899

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA609 passage 6

  Dataset EGAD00001009120

• 10x Genomics Single Cell Gene Expression for SA605X3XB01966

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA605 passage 3

  Dataset EGAD00001009142

• 10x Genomics Single Cell Gene Expression for SA1035X7XB03502

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 7

  Dataset EGAD00001009151

• 10x Genomics Single Cell Gene Expression for SA610X3XB03802

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA610 passage 3

  Dataset EGAD00001009160

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03216

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009154

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WXS

  Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WXS

  Dataset EGAD00001010043

• 10x Genomics Single Cell Gene Expression for SA1188

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTert L9 116.66

  Dataset EGAD00001009114

• Hi-C for Junvenile Pilocytic Astrocytomas

  5 Hi-C datasets (4 JPA and 1 LGG). Hi-C data for the remaining 5 JPAs used in our paper as well as all controls have been uploaded to EGA under EGAS00001005476.

  Dataset EGAD00001009044

• Whole exome genome sequencing data to study "A biobank of patient-derived pediatric brain tumor models"

  Whole exome sequencing data to 30 PDOX models (28 early passages, 3 late passages (1 overlap)), 3 cell lines, and 20 matching human tumors

  Dataset EGAD00001003544

• McGill EMC Release 4 for assay "ATAC-seq"

  McGill EMC Release 4 for assay "ATAC-seq": Sequencing of transposase-accessible chromatin as described by Buenrostro et al. (Nature Methods 10, 1213?1218 (2013) doi:10.1038/nmeth.2688)

  Dataset EGAD00001001300

• 200PT : CNA vcf files

  200PT : CNA vcf files. Copy Number Abberation calls generated using TITAN and PhyloWGS, from the CPCGene 200PT Subclonality study

  Dataset EGAD00001004073

• ChIP-seq and Hodgkin lymphoma

  ChIP-seq data (H3K4Me3, H3K27Ac histone modifications) of Hodgkin lymphoma cell line L-428. Samples were processed as previously described (Sud et al., 2018). The files are in bam format, aligned to build 37 of the human genome.

  Dataset EGAD00001004322

• Covacta RNAseq counts

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes read counts per gene. Read counts were generated for the Gencode v27 annotation using the summarize Overlaps method from bioC in mode “IntersectionStrict”

  Dataset EGAD00001011164

• BIOCLOCK Phenotype Information Dataset

  This dataset contains phenotypic metadata from participants in the BIOCLOCK endurance exercise intervention and epigenetic aging study. It includes intervention status, cardiorespiratory fitness (VO2 max), body composition, estimated leukocyte proportions, and other relevant traits linked to epigenetic aging outcomes.

  Dataset EGAD00001015799

• 10x Genomics Single Cell Gene Expression for SA535X9XB03617

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 9

  Dataset EGAD00001009157

• WES data of one tumor of B-cell lymphoma

  paired EXOME sequencing on Illumina HiSeq 4000 using Agilent SureSelect V6 of one tumor sample of one patient with B-cell lymphoma. The bam-file was mapped to the hg19 genome.

  Dataset EGAD00001006060

• IMpower133 processed RNA-seq data for genes utilized for cluster assignments

  This dataset contains log2(TPM + 1) for 271 tumor samples profiled by RNA-seq for the subset of genes used for validation of the NMF cluster assignments.

  Dataset EGAD00001006928

• HV31 - Illumina PCR-free sequencing

  Illumina PCR-free sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~44×. Sequencing was performed at the Wellcome Centre for Human Genetics on the Illumina Novaseq platform.

  Dataset EGAD00001007042

• Segmental Cherry Angioma case

  Cherry angiomas are common benign blood vessel growths on the skin. In this study we characterise mutational profile of a cherry angioma and adjacent skin biopsied from a patient with multiple lesions with segmental presentation.

  Dataset EGAD00001015641

• ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium.

  The telomeric amplicon at 8p12 is common in oestrogen receptor-positive (ER+) breast cancers. Array-CGH and expression analyses of 1172 primary breast tumours revealed that ZNF703 was the single gene within the minimal amplicon and was amplified predominantly in the Luminal B subtype. Amplification was shown to correlate with increased gene and protein expression and was associated with a distinct expression signature and poor clinical outcome. ZNF703 transformed NIH 3T3 fibroblasts, behaving as a classical oncogene, and regulated proliferation in human luminal breast cancer cell lines and immortalized human mammary epithelial cells. Manipulation of ZNF703 expression in the luminal MCF7 cell line modified the effects of TGFβ on proliferation. Overexpression of ZNF703 in normal human breast epithelial cells enhanced the frequency of in vitro colony-forming cells from luminal progenitors. Taken together, these data strongly point to ZNF703 as a novel oncogene in Luminal B breast cancer.

  Study EGAS00000000082

• A microRNA-signature that correlates with cognition and is a target against cognitive decline

  While some individuals age without pathological memory impairments, others develop age-associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3-microRNA signature that reflect key processes linked to neural homeostasis and informs about cognitive status. We furthermore provide evidence that expression changes of this signature represent multiple mechanisms de-regulated in the aging and diseased brain and are a suitable target for RNA therapeutics.

  Study EGAS00001005627

• Loss of Epigenetic Barrier is Required for Enhancer Hijacking-Mediated Oncogenic Transcription

  Structural variants (SVs) involving enhancer hijacking can disrupt chromatin topologies to cause oncogene activation in cancer genomes, yet the molecular determinants for the transcriptional output of enhancer hijacking remain largely unknown. We developed a multimodal approach to integrate genome sequencing, chromosome conformation, and sequence-based deep learning for quantitative analysis of transcriptional effects and structural reorganization imposed by SVs in leukemic genomes. We identified candidate pathogenic SVs including recurrent t(5;14) translocations that cause the hijacking of BCL11B enhancers for oncogenic activation of TLX3-dependent transcriptional programs. By engineering patient-associated t(5;14) in isogenic leukemia cells, we uncovered an uncharacterized mechanism whereby DNA methylation serves as an epigenetic barrier to enhancer hijacking and loss of epigenetic barrier is a molecular determinant for the transcriptional output of pathogenic SVs. Hence, leveraging the epigenetic barriers of SV-mediated oncogenic programs may provide new opportunities to reprogram gene regulation as epigenetic therapies in human disease.

  Study EGAS00001006140

• Genetic Heterogeneity of the familial gastric neuroendocrine tumors (2018-06-06)

  Gastric neuroendocrine tumors (gNETs) occur with an estimated frequency of 2 per 100,000 in the general population. Type I gastric neuroendocrine tumors (NETs) represent the 75% of gNTEs and arise from gastric enterochromaffin-like (ECL) cells. They have late age of onset and usually benigh course. Classically, hypergastrinemia in patients who have autoimmune atrophic gastritis, causes hyperplasia of gastric ECL cells that progresses into type I gastric NETs and parietal cell (PC) destruction. The genetic bases in families with this disease are unknown. We performed an exome sequencing study of an atypical aggressive familial gNETs case (with early age onset, nodal infiltrations and gastric adenocarcinomas) that followed a recessive model. We identified a deleterious mutation in homozygosis in the ATP4A gene, which encodes the proton pump responsible for acid secretion by gastric parietal cells. This mutation lead to achlorhydria first, and hypergastrinemia and gNET developing as consequence (Calvete et al. 2014). Recently, two more families with gNETs, classical clinical traits and recessive model have been studies by WES but we didn't find any mutation in the ATP4a gene. However, putative mutations affecting genes that contribute to the development and the integrity of PC have been found suggesting that genetic alterations associated to this disorder target to a unique cell type (parietal cells). In order to cinfirm this hypothesis, it is necessary the search for new genes implicated in the gNETs, more familial cases are needed to be studied. We have identified four more new familial gNETs cases. Here, we propose their study by WES. The first family is formed by thress siblings with gNETs. The other families include two siblings with gNETs. 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 2018-06-06.

  Dataset EGAD00001004153

• Exome sequencing of patients with Ewings sarcoma

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing,s sarcoma tumours.

  Dataset EGAD00001000333

• ICGC Benchmarking Exercise

  The main objective of this benchmark is the comparison of the full sequencing pipeline of different ICGC partners, including procedures, methods and performance of library preparation and whole-genome deep-sequencing. A secondary objective will be a follow-up comparison of data analysis pipelines for identification of germline and somatic variants subsequent to the results of the ICGC Somatic Variant Calling Pipeline Benchmark.

  Dataset EGAD00001000625

• Colorectal cancer GWAS on the Spanish population

  Data on Affymetrix 6.0 arrays for Genome-Wide Association Study of colorectal cancer in the Spanish population. Additionally, geographical origin for each sample is provided, which constitutes the largest to-date Spanish genomic sample population

  Dataset EGAD00010001715