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• BLUEPRINT release August 2015, ChIP-Seq for Multiple myeloma, on genome GRCh38

  ChIP-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001592

• BLUEPRINT release August 2016, RNA-Seq for mature eosinophil, on genome GRCh38

  RNA-Seq data for 2 mature eosinophil sample(s). 3 run(s), 3 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002326

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC2884 (4h), on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 (4h) sample(s). 6 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002372

• BLUEPRINT release August 2016, ChIP-Seq for Chronic Lymphocytic Leukemia, on genome GRCh38

  ChIP-Seq data for 106 Chronic Lymphocytic Leukemia sample(s). 174 run(s), 163 experiment(s), 162 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002384

• BLUEPRINT release August 2016, ChIP-Seq for Mantle Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 5 Mantle Cell Lymphoma sample(s). 35 run(s), 35 experiment(s), 35 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002397

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs sample(s). 8 run(s), 8 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002408

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC3324, on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC3324 sample(s). 2 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002431

• BLUEPRINT release August 2016, ChIP-Seq for neutrophilic metamyelocyte, on genome GRCh38

  ChIP-Seq data for 4 neutrophilic metamyelocyte sample(s). 32 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002435

• BLUEPRINT release August 2016, RNA-Seq for Acute Myeloid Leukemia - CTR, on genome GRCh38

  RNA-Seq data for 7 Acute Myeloid Leukemia - CTR sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002443

• BLUEPRINT release August 2016, ChIP-Seq for mature eosinophil, on genome GRCh38

  ChIP-Seq data for 2 mature eosinophil sample(s). 14 run(s), 14 experiment(s), 14 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002477

• BLUEPRINT release August 2016, RNA-Seq for osteoclast, on genome GRCh38

  RNA-Seq data for 2 osteoclast sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002479

• BLUEPRINT release August 2016, Bisulfite-Seq for CD38-negative naive B cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD38-negative naive B cell sample(s). 51 run(s), 5 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002520

• Single-cell expression of Hodgkin lymphoma

  Single-cell gene expression was profiled for 22 Hodgkin lymphoma tumors and 5 reactive lymph nodes (2 replicates were performed for RLN-1). Library preparation was performed with the 10x Chromium platform (3' version 2 assay). Sequencing was performed on an Illumina NextSeq. The BAM files were generated from the raw sequencing data using Cell Ranger (v2.1.0) mkfastq and count commands.

  Dataset EGAD00001005739

• Clinical data

  Clinical data from IMvigor210, POPLAR, IMmotion150: Clinical data include demographics, tumor type, PD-L1 IHC, tumor mutation burden, objective response rate, overall survival and progression free survival for 611 patients across IMvigor210, POPLAR and IMmotion150. Clinical data from PCD4989g: Clinical data include tumor type, PD-L1 expression and objective response rate for 206 patients from PCD4989g.

  Dataset EGAD00001006630

• A108846B

  Whole genome sequencing for single cells for library A108846B 1636 cells; filetype=bam

  Dataset EGAD00001007092

• Genetic Progression of Head and Neck Squamous Cell Carcinoma

  These data are tumor/normal-matched exome sequencing results on 45 participants (median age of 58.6 years) treated for squamous cell carcinoma of the oropharynx at Mass Eye and Ear (MEE; Boston, MA, USA). Some tumors had two portions sequenced separately. All research complied with all relevant ethical regulations. Human subject research on patients at MEE was approved by the MEE Human Studies Committee under protocol HSC 11-024H, with informed consent obtained from participants. Participants were not compensated. Clinical data, including HPV status, were abstracted from patient records. Sequencing and clinical data were combined with TCGA data on 486 cases of head and neck squamous cell carcinoma (HNSCC). The PhylogicNDT suite of genomic analysis tools was used to infer the relative timing of genetic events during tumor progression for major molecularly defined classes of HNSCC: HNSCC negative for human papillomavirus (HPV), HPV-associated HNSCC, and HPV-negative HNSCC involving mutations in CASP8, NSD1, and NOTCH1. The timing of the development of whole-genome somatic events leading to tetraploidy or triploidy and to increased measures of intratumor genetic heterogeneity was determined. Associations of heterogeneity measures with clinical outcomes were assessed. The analysis identified genes with early mutations that likely play roles in HPV-tumor initiation (FBXW7, NOTCH1, CASP8, FAT1, NSD1, HRAS, EP300, CREBBP, KMT2D). Genes with mutations at later median relative timing (PK3CA, NFE2L2, HLA-A, SPEN, and KMT2C) were more likely to be important for progressing to later stages of the disease. Gain of chromosome arm 3q and loss of arm 11q were found to occur more frequent in HPV+ HNSCC cases. A high prevalence of 3p and 17p loss were also observed in HPV+ HNSCC cases.

  Study phs003139

• Identifying Novel Small RNA Biomarkers Unique to Patients with Gastric Cancer

  The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented. Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: 30097497 DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States).

  Study phs001767

• The Role of Germline Mutation and Parental Age in Autism Spectrum Disorders

  <p>We will apply whole genome sequencing of trio families to determine how patterns of germline mutation throughout the genome determine risk for Autism Spectrum Disorder (ASD). We will investigate the nature intrinsic hypermutability and the extrinsic forces, such as paternal age, that influence rates of germline mutation. We will accomplish these goals through the following specific aims: Specific Aim 1 will characterize germline de novo mutations (DNMs) by whole genome sequencing in families. These studies will identify and validate ~8,000 de novo point mutations and structural variants in trios and controls to determine the parent of origin of DNMs. Specific Aim 2 will identify hot spots for germline mutation based on the regional density of DNMs in the genome, and determine the effects of DNA sequence features on rates of mutation. We will determine the association of mutation hotspots with ASD in the discovery sample and in genomic datasets from an independent sample of 2700 cases and 2700 controls. Specific Aim 3 will characterize the effects of extrinsic factors, including parental age and environment, on genome-wide rates of mutation. We will quantify the effect of paternal age on pathogenic and neutral alleles in sperm and investigate whether some DNMs confer a germline selective advantage. The findings of this study will provide fundamental insights into the genetic basis of autism risk and the genetic mechanism of the observed parental age effects in ASD. We will identify genes that confer significant risk for autism, and we will determine how intrinsic properties of the genome interact with extrinsic forces to determining risk for disease in offspring.

  Study phs001164

• A Missense SNP in the Tumor Suppressor SETD2 Reduces H3K36me3 and Mitotic Spindle Integrity in Drosophila

  While examining DNA from renal cell carcinoma (RCC) patients we observed a single nucleotide polymorphism (SNP; rs58906143,chr3:47163422 C→G (hg19); E902Q*) within SETD2 that was overrepresented in kidney cancer patients compared to control patients. This original study utilized directed sequencing of 14 genes. In an expanded study using a Taqman assay to study the specific SNP, a G allele was found in 72/493 cases (14.6%) and 24/356 (6.7%) controls. Analysis by ancestry revealed that there was there was a G allele in 50/119 (42.0%) cases and 21/71 (29.6%) controls in patients with African Ancestry while there was a G allele in 19/335 cases (5.7%) and 3/269 (1.1%) controls in patients with European Ancestry. These differences did not reach statistical significance. Concurrently, we studied the functional effect of this SNP in a Drosophila model. The homologous amino acid substitution at E741Q reduces H3K36me3 levels which could be rescued by wild type Set2. Additionally, the mutation resulted in significant defects in spindle morphogenesis, consistent with a role for SETD2 in alpha-tubulin methylation during mitosis. Data available through dbGAP include the 14 gene sequence files of 52 control and 128 RCC patients, the results of Taqman SNP (rs58906143) analysis in text files for 221 controls and 357 RCC patients, and compiled phenotype data including age and assigned race. Due to data use limitations, genotyping data for 8 RCC patients and 83 controls as well as GWAS data for ancestry determination will not be available on dbGaP, but will be made available on request.

  Study phs003474

• Clinical and Molecular Features of Acquired Resistance to Immunotherapy in Non-Small Cell Lung Cancer

  PD-(L)1 blockade has been shown to promote durable responses in non-small cell lung cancer (NSCLC) patients and has been rapidly incorporated into the treatment regimens for many with advanced disease. Despite this, mechanisms of acquired resistance (AR) to PD-(L)1 have not been well understood. To address the clinical and molecular landscape of AR to PD-(L)1 blockade in NSCLC patients, a large clinical cohort of AR to PD-(L)1 blockade in lung cancer was examined. In conjunction, a systematic genomic and transcriptomic analysis in a subset of patients (n = 29) with available tissue samples was conducted. To investigate the molecular mechanisms of AR to PD-1 blockade from pre- and/or post-treatment tumors, microarray-based whole transcriptome expression data for 29 tumor samples, and whole exome sequencing (WES) data from 34 tumor samples was generated from this subset. Microarray data was uploaded to the Gene Expression Omnibus (GEO) database. Most AR tumors showed retained or increased inflammatory characteristics with significant upregulation of IFNγ which was suggestive of persistent albeit insufficient anti-tumor immune response. This finding expounds upon the prior pre-clinical and translational data supporting the intricate role of IFNγ in sensitivity and resistance to immunotherapy. Whereas initial IFNγ exposure may be fundamental to T cell activation (a hallmark of immune response), persistent IFNγ related effects and upregulation may potentially signal immune dysfunction and IFNγ insensitivity in contrast. The inflammatory phenotypes identified have implications for future rational development of new immunotherapy strategies for patients with AR.

  Study phs002834

• Puerto Rico Heart Health Program (PRHHP-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. Objectives: To investigate morbidity and mortality from Coronary Heart Disease (CHD) in Puerto Rican rural and urban men. The objectives of the study were: (1) to identify factors related to the development of CHD, (2) compare the etiology of disease in rural versus urban men, and (3) determine the prevalence and incidence of CHD and other cardiovascular diseases in Puerto Rican males.Background: As Puerto Rico became more industrialized in the 1940s and 1950s, mortality rates for CHD increased. Since many factors related to CHD can be relatively homogenous within a population, two contrasting subgroups were selected for study in Puerto Rico: a rural population of men from a mountainous community and an urban population selected from San Juan. The NHLBI initiated the Puerto Rico Heart Health Program in May, 1965 as a prospective study of lifestyle, environmental and biological factors in the progression of cardiovascular disease in Puerto Rican men.Participants: A total of 9,824 (2,976 rural, 6,848 urban) men, age 45 to 64 were examined at the baseline exam.Design: The examination consisted of standardized questionnaires to determine education, occupation, smoking habits, and physical activity. Trained interviewers conducted a nutritional survey through a 24 hour diet recall. Subjects were also examined to determine prevalent cardiovascular, cerebrovascular and peripheral vascular abnormalities. The examination included vital capacity, a 12-lead ECG, and laboratory tests for hematocrit, glucose, serum cholesterol, serum glycercides and lipoprotein electrophoresis. A medical history was also obtained. Three additional exams, approximately three years apart, were conducted and morbidity and mortality follow-up concluded in 1980.

  Study phs003930

• High Frequency Ventilation in Premature Infants (HIFI-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. Objectives: To evaluate the hypothesis that high frequency oscillatory ventilation in preterm infants would reduce the incidence of mortality and pulmonary complications compared to conventional mechanical ventilation.Background: With the introduction of mechanical ventilation in preterm infants, mortality and morbidity significantly improved but remained high. The improvement in survival that accompanied the use of mechanical ventilation also brought about an increase in the incidence of pulmonary complications. The principal complication occurs in the form of bronchopulmonary dysplasia. Barotrauma and oxygen toxicity are considered to be in the pathogenesis for this disorder. Considerable interest in high frequency ventilation for preterm infants was generated when animal studies indicated high frequency ventilation to be effective in promoting gas exchange without apparent adverse effects. High Frequency Ventilation (HFV) delivers small tidal volumes at high frequencies of 4 to 15 Hz, and animal studies had indicated that HFV was associated with effective gas exchange, less barotrauma, and lower mean airway pressure. However, the efficacy and safety of HFV in preterm infants had not been studied. The HIFI Planning Phase was initiated in August 1984, and recruitment and intervention began in February, 1986. Follow-up studies continued thru September, 1988.Participants: A total of 673 infants were enrolled.Conclusions: Bronchopulmonary dysplasia incidence was similar in the two groups as was mortality and the need for ventilatory support during the first 28 days. There was a significantly greater rate of pneumoperitoneum of pulmonary origin in the high frequency group as was a greater incidence rate of intracranial hemorrhage. (HIFI Study Group, 1989, PMID: 2643039)

  Study phs004032

• Response to Hepatitis B vaccine

  Approximately 5-10% of individuals, who are vaccinated with a hepatitis B (HB) vaccine designed based on the HBV genotype C, fail to acquire protective levels of antibodies. Host genetic factors behind low immune response to the HB vaccine were investigated by GWAS and HLA association tests. GWAS and HLA association tests were carried out using a total of 1,193 Japanese individuals including 107 low responders (HBsAb ?10 mIU/mL), 351 intermediate responders (10 mIU/mL< HBsAb <100 mIU/mL), and 735 high responders (HBsAb ?100 mIU/mL). Classical HLA class II alleles were statistically imputed using the genome-wide SNP typing data. GWAS identified independent associations of HLA-DRB1-DQB1 haplotypes, HLA-DPB1 alleles and BTNL2 gene with immune response to the HB vaccine designed based on the HBV genotype C. Five HLA-DRB1-DQB1 haplotypes and two DPB1 alleles showed significant associations with response to the HB vaccine in a comparison of three groups of 1,193 HB vaccinated individuals. When frequencies of DRB1-DQB1 haplotypes and DPB1 alleles were compared between low immune responders and HBV patients, significant associations were identified for three DRB1-DQB1 haplotypes, and no association was identified for any of DPB1 alleles. In contrast, no association for DRB1-DQB1 haplotypes and DPB1 alleles was identified in a comparison between high immune responders and healthy individuals. The findings in this study clearly show the importance of HLA-DR-DQ (i.e. recognition of a HB vaccine related HBsAg by specific DR-DQ haplotypes) and BTNL2 molecules (i.e. high immune response to the HB vaccine) for response to a HB vaccine designed based on the HBV genotype C.

  Study JGAS000341

• DATA ACCESS AGREEMENT CGNT- GROUP COMMITTEE for project "Exome sequencing of 22 Pheochromocytoma/paraganglioma tumors" at Gothenburg University.

  Dac EGAC00001000411

• DAC for Greenland Studies of University of Copenhagen and University of Southern Denmark.

  Dac EGAC00001000736

• The data access committee for Evolution of neoantigen landscape during immune checkpoint blockade in non-small cell lung cancer.

  Dac EGAC00001000757

• Data Access Committee for the study "Somatic chronology of treatment-resistant prostate cancer via deep whole-genome ctDNA sequencing"

  Dac EGAC00001002479

• Access Committee for Separation, characterization, and identification of individuals from multi-person blood mixtures

  Dac EGAC00001002646

• DATA FILES FOR SJRB

  Retinoblastoma whole genome sequencing

  Dataset EGAD00001000261

• WES for Verhaak GBM

  Dataset EGAD00001001109

• WES for verhaak-GBM

  Dataset EGAD00001001110

• TumorSNP

  SNP data for 473 tumor samples

  Dataset EGAD00010002038

• Genotypes_Farmers

  Genotype data for Palanan farmers Philippines

  Dataset EGAD00010002141

• Genotypes_BaYaka

  Genotype data for BaYaka hunter-gatherers Congo

  Dataset EGAD00010002139

• ASTAR Skin Research Laboratory

  Data Access Committee for A*STAR Skin Research Laboratory, A*STAR Research Institutes, Singapore.

  Dac EGAC50000000109

• Data for paper Mold, Weissman et al. 'Clonally heritable gene expression imparts a layer of diversity within cell types'

  Dac EGAC50000000102

• Patient WGS for #198

  Whole genome sequencing of patient tumour and blood

  Dataset EGAD50000000217

• PDX WGS for #264

  WGS of tumour PDX and matched patient blood

  Dataset EGAD50000000033

• PDX WES for #039 and #049

  Exome sequencing of PDX and matched patient blood

  Dataset EGAD50000000034

• DAC - organotypic co-cultures @IEO

  DAC for RNAseq data on patient-derived organotypic models (Battistini et al, CDDis 2024)

  Dac EGAC50000000238

• eQTL-CHiC DAC

  The Data Access Committee for eQTL-CHiC and related data from Ray-Jones et al., 2024.

  Dac EGAC50000000445

• DAC for Transcriptomic and genomic profiling of fragile X syndrome unmethylated full mutation carriers

  Dac EGAC50000000416

• Distinct Phenotypes of Human Intrahepatic and Extrahepatic Bile duct Organoids and their Applications for Biliary Disease Modeling

  Study EGAS00001003792

• DKFZ-HIPO DACO for "Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target"

  Dac EGAC00001003559

• Data Access Committee for Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  Dac EGAC00001003558

• DAC_Circadian_Neuroendocrinology

  DAC for projects of the group Circadian Neuroendocrinology at the Department of Endocrinology and Metabolism at Amsterdam UMC.

  Dac EGAC50000000692

• Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

  Study EGAS00001005115

• Nimblegen SeqCap Custom Panel Sequencing

  Nimblegen SeqCap Custom Panel Sequencing for pNet

  Dataset EGAD00001005494

• Genomic Sequencing of Triple Negative Breast Cancer - Exome data

  Exome data for study EGAS00001008261

  Dataset EGAD00001015687

• WGS dataset

  4 WGS bam files for 4 cases with fusion

  Dataset EGAD00001004359