Search Results - EGA European Genome-Phenome Archive

Identification of New Therapeutic Targets for Renal Medullary Carcinoma via Integrated Genomic and Transcriptomic Profiling

Renal medullary carcinoma (RMC) is a rare, aggressive kidney cancer associated with sickle cell trait, characterized by SMARCB1 loss and resistance to conventional therapies used for other renal cell carcinomas (RCC). We conducted whole exome sequencing (WES) on RMC samples. This study provides a large molecular characterization of RMC, highlighting TROP2 and other cell surface markers as promising therapeutic targets.

Study EGAS50000001280

scCRISPRi/a-seq Control and IFN treated iPS derived human GPC/OPCs

Datasets consists of 2 batches of human glial progenitors (iPS), cells were sequenced as controls and IFN treated. Using the 10Genomics platform from the samples 2 libraries were built forgene expression libraries (scRNA-seq) and captured guides sequencing library (gRNA) on a set of Multiple Sclerosis associated SNPs. Batch one includes KRAB and P300 perturbed cells in 2 rounds sequenced RNA libraries for Ctrl and IFN and 1 round of capture guides for Ctrl and IFN. Batch 2 includes 1 round of both RNA expresison library and captures guides for KRAB and P300 perturbations in Ctrl and IFN treated cells.

Dataset EGAD50000002053

scMethylation data of 5 regionally sampled GBM tissue for 2 patients

This dataset contains snRNA-seq data of 5 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed in an unbiased manner without any sorting procedure. Nuclei dissociation was performed following the nuclei isolation for single-cell ATAC-seq (10x Genomics; CG000169) with matched peri-tumoral and tumor core samples. Subsequent single-cell methylation sample preparation followed Scale Biosciences single-cell methylation kit protocol v1.0. mplification adaptors through ligation and adding a second barcode though indexed PCR reaction following Scale Biosciences single-cell methylation kit protocol v1.0. We employed the TWIST human methylome panel for targeted enrichment of informative methylation sites.

Dataset EGAD50000001837

ATAC sequencing raw data files of human Treg cell subsets

Assay for Transposase-Accessible Chromatin using sequencing (ATAC) sequencing of human CD38+, HLA-DR+, CD38+ HLA-DR+, and CD38- HLA-DR- regulatory T (Treg) cell subsets sorted from peripheral blood pooled from 4 healthy donors. After isolation and purification of Treg cell subsets with flow cytometry, samples were frozen and transferred to Active Motif for ATAC sequencing. The dataset contains one raw sequencing file (fastq) of accesible regions for each of the above-mentioned Treg cell subsets.

Dataset EGAD50000000664

Illumina GSA-MD v3 genotyping arrays for 183 samples

Genotyping arrays for 183 samples from patients with a neuroendocrine tumor of the small intestine. All samples have been hybridized on Illumina GSA-MD v3 arrays with standard automated protocols. Reading of the chips was performed on Illumina iScan+ scanners and this file is the result of primary analysis done using Illumina GenomeStudio software. It contains data for 147 tumors, 2 adenomas, 1 lymph node, 19 mesenteric nodules, 6 liver metastasis and 8 normal ileum samples.

Dataset EGAD50000000905

Genomic and Transcriptomic sequencing of neuroblastoma cell lines

Genomic and Transcriptomic sequencing of neuroblastoma HSR and ecDNA cell lines. Data represents five 96-well plates that were processed with G&T sequencing, resulting in genomic and transcriptomic data from the same single cells. Dataset contains 95 bam files containing the DNA sequencing data and 95 bam files containing the RNA sequencing data of CHP212 cells, 380 bam files (190 DNA and 190 RNA) for TR14 cells, 188 bam files (94 DNA and 94 RNA) for Kelly cells and 192 bam files (96 DNA and 96 RNA) for IMR5/75 cells.

Dataset EGAD50000000729

Targeted long-read snIso-Seq of the human brain in neurodegenerative diseases

Nuclei were extracted from postmortem human brain, and cDNA libraries were generated using the 10X Genomics 3' v3.1 kit. Prior to fragmentation, 75% of the library was reserved for long-read sequencing. This unfragmented library was used for target enrichment with a custom 50 gene probe panel from Twist Biosciences. The resulting amplified cDNA libraries were sequenced on a Sequel II. The files provided have undergone CCS generation, and we recommend following the guidelines in https://isoseq.how/ for further analysis starting with removal of primers using lima. The primer sequences that should be supplied are the Read 1 and TSO primers from the 10X Genomics kit.

Dataset EGAD50000000179

CentralAfricanCMC_Pemberton

The CentralAfricanCMC_Pemberton dataset encompasses 153,798 SNPs from the Illumina Cardio-MetaboChip (Voight et al. 2012) genotyped in 406 individuals from 19 Central African Populations from Gabon, Cameroon, Centralafrican Republic and Uganda). Individual phenotypic and cultural information at the individual level for this data set encompass gender, lifestyle (hunter-gatherer or farmer), and, when available, stature phenotype (standing height in cm, sitting-height in cm, and weight in kg). Other cultural, linguistic, and geographical location information about the sampled populations can be found in Pemberton et al. , Human Genetics, 2018 (https://doi.org/10.1007/s00439-018-1902-3).This dataset can only be accessed and used for non-commercial research purposes with a finality complying with the informed consent provided by Central African donors for the study of human evolutionary history only.

Dataset EGAD00010001584

BM xenograft TARGET-seq+ single-cell transcriptome sequencing

Single-cell whole transcriptome sequencing data for 5 xenografted bone marrow samples (4 cases with clonal haematopoiesis and 1 without clonal haematopoiesis). For each sample, mice were treated with two doses of PBS or hTNFa. CD34+ HSPCs and CD34-CD33+ myeloid cells were isolated from xenografted mice, sorted into plates, and TARGET-seq+ was performed to generate plate-based 3' transcriptome data. Additionally, cells from a control primary bone marrow sample (NOC153) were included on each plate. Each library consist of 192 cells sorted into a single plate. FASTQ files are provided; R1 contains cell barcodes and R2 contains the cDNA read. For demultiplexing and pre-processing instructions see: https://github.com/asgerjakobsen/TARGET-seq-plus-RNA.

Dataset EGAD50000002382

WGS data for MMML for Study EGAS00001002199

Whole genome sequencing data for MMML (tumor/control pairs and one cell_line)

Dataset EGAD00001003274

Normal prostatectomy project analysis and leftovers

Data collected as part of the Normal prostatectomy project analysis. Whole genome sequencing (WGS, targeted at 30X for normal tissue and 50X for tumour tissue) was performed on morphologically normal tissue samples from 30 patients with prostate cancer. In addition, seven prostate tissue samples were sequenced from 7 non-cancer patients: two collected after a cystoprostatectomy and five from samples collected at autopsy. Matched blood controls were included for all patients. An extra five samples were sequenced from the stroma of cell cultured fibroblasts. In addition a few tumour samples obtained at prostatectomy and their blood matched controls are included in this dataset from the main study that are not included elsewhere.

Dataset EGAD00001004125

Exome sequencing of a Novel Primary T Cell Immunodeficiency Kindred (2019-08-19)

Primary T cell immunodeficiency disorders have a heterogeneous genetic basis. This study will focus on one case characterised by severe T cell lymphopenia in the index case. We aim to sequence the complete exomes of this individual, her three unaffected siblings and parents in an effort to identify the causative genetic mutation responsible for this disorder. We will perform exome capture using Agilent SureSelect system, followed by sequencing on the HiSeq platform. Our study has the potential to uncover genes important for T cell development and novel therapeutic strategies to treat T cell immunodeficiencies. . This dataset contains all the data available for this study on 2019-08-19.

Dataset EGAD00001005263

Benchmarking dataset for ProSolo, a probabilistic single nucleotide caller for single cell DNA sequencing data

This is the dataset used in the benchmarking of ProSolo, a new probabilistic single nucleotide variant caller for single cell DNA sequencing data that provides control over the false discovery rate of different single cell events at genomic sites (e.g. alternative allele presence or allele dropout). It provides the whole exome sequencing data used in assessing ProSolo's performance that is not available elsewhere, namely bulk whole exome sequencing data of a patient with a constitutional mismatch repair defect (MSH6-) and their parents and siblings, a bulk whole exome sample of granulocytes from that patient and 5 single granulocytes whole exome sequenced after whole genome amplification.

Dataset EGAD00001005929

MYOSEQ

The MYOSEQ project focuses on the application of next generation sequencing, in particular whole exome sequencing (WES), in a large cohort of patients with unexplained limb‐girdle weakness (LGW). Focusing on undiagnosed patients with a clearly defined clinical phenotype enables increased diagnostic rates for known genes (in particular Pompe disease, GNE related pathologies and other known LGMD subtypes) in this cohort, while the use of WES provides scope both for new gene discovery and for additional research into disease modifiers and genotype‐phenotype correlation with substantial cost effectiveness. The LGW patient cohort was collated by Newcastle University in collaboration with clinical centers across Europe. The sequencing was performed at the Broad Institute and jointly analyzed with Newcastle University.

Dataset EGAD00001006158

Whole exome and genome sequencing for normal endometrial glands

The raw fastq files for 30 whole exome and 30 whole genome sequencing for normal endometrial glands. The paired-end sequencing data sets (R1 and R2) are deposited.

Dataset EGAD00001008377

Developing somatic copy number and mutation calling tools for a bespoke sequencing platform

We previously developed a linked-read sequencing platform (DigiPico) for analysing whole cancer genomes from picogram quantities of tumour DNA. The aim of this study was to develop and evaluate the specialised computational approaches required to obtain clinically useful results from the raw data. To this end, we performed matched DigiPico, bulk tumour and germline WGS on samples from four patients.

Study EGAS00001007195

Detection of cancer cell transcriptomes

Single cell transcriptomes, generated using chromium 10X 3' sequencing, for two tumour types (AT/RT, and Ewing's sarcoma). For each individual, tumour and normal whole genome sequencing was also obtained using Illumina short read sequencing to an average depth of 30X. These data were used to validate the accuracy of a method for identifying cancer cell transcriptomes based on the allelic shift produced by copy number changes.

Dataset EGAD00001009005

Whole Genome Scan for Pancreatic Cancer Risk in the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium (PanScan)

Within the framework of the NCI-sponsored Cohort Consortium, investigators from 12 prospective epidemiologic cohorts formed the Pancreatic Cancer Cohort Consortium in 2006. This study, also known as "PanScan", is funded by the National Cancer Institute (NCI) and involves conducting a genome-wide association study (GWAS) of common genetic variants to identify markers of susceptibility to pancreatic cancer. In 2007, the study was expanded to include 8 case-control studies. The study team includes scientists from the cohorts comprising the Consortium, the NCI and the Pancreatic Cancer Case Control Consortium (PanC4). PanScan I and II were conducted in 12 cohort studies and 8 case-control studies, leading to the discovery of four novel regions in the genome associated with risk for pancreatic adenocarcinoma. The third phase of PanScan (PanScan III) was conducted using recently identified incident pancreatic cancer cases drawn from fourteen cohorts from the cohort consortium, including nine prospective cohorts who participated in PanScan I, and five newly joined cohorts. The nine cohort studies that participated in PanScan I and had new genotyping of cases in PanScan III include ATBC, CPS-II, EPIC, HPFS, NHS, PHS, PLCO, SMWHS, and WHI; the five newly joined cohort studies include the Agricultural Health Study (AHS), the Multiethnic Cohort Study (MEC), the Melbourne Collaborative Cohort Study (MCCS), the Vitamins and Lifestyle Study (VITAL), and Selenium and Vitamin E Cancer Prevention Trial (SELECT). In addition to the cases from cohorts, we also included cases from the Gastrointestinal Cancer Clinic of Dana-Farber Cancer Institute Study (DFCI-GCC); from the University Hospital in Heidelberg, Germany, which is part of a larger European clinical case-control study (PANDoRA); and from clinic-based cases from eastern Spain (PANKRAS-II). The dbGaP datasets available include all subjects previously made available from PanScan I and II, plus 1,582 new incident pancreatic cancer cases of European descent from prospective cohorts, case-control studies or case series (genotyped as part of PanScan III). Also included are 61 pancreatic cancer cases and 67 control subjects from PanScan I as well as 173 pancreatic cancer cases from PanScan III of Asian ancestry from the Shanghai Men's and Women's Health Study (Supplemental Table 10, Wolpin et al. (Nat Genet, 2014)). The control population used in the analysis for the Wolpin et al. manuscript included cancer-free individuals from the prospective cohorts that contributed pancreatic cancer cases to PanScan III and controls from the Spanish Bladder Cancer SBC/EPICURO study that were previously genotyped using the OmniExpress, Omni 1M or Omni 2.5M SNP arrays. The data from these control subjects were posted to dbGaP under the GWAS in which they were initially genotyped and will not be made available in duplicate under this dbGaP study.The summary statistics for PanScan I-III were generated as detailed in Wolpin BM. et al., Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer, Nature Genetics 2014; 46(9):994-1000 (https://www.nature.com/articles/ng.3052), and Klein, A. et al., Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer, Nature Communications, 2018;9(1):556 (https://www.nature.com/articles/s41467-018-02942-5). The dataset includes results from an association study of 5,117 individuals diagnosed with pancreatic ductal adenocarcinoma (PDAC) and 8,845 control individuals, or a total of 13,962 subjects of European ancestry (as compared to the genotype and phenotype information under this project that includes 9,437 individuals (PanScan I and II PDAC case and control individuals and PanScan III PDAC cases only). This is due to the fact that PanScan III “borrowed” GWAS data from control individuals genotyped separately from the PanScan GWAS project and are therefore not included as raw genotypes in phs000206.v5.p3. Association analysis was performed separately for PanScan I-II and PanScan III, followed by a meta-analysis of the two datasets. Results were filtered based on a minor allele frequency (MAF) < 0.01, an imputation INFO score < 0.3 and a heterogeneity P-value < 1x10-10 leaving a total of 9,758,390 variants. Columns in the summary statistics dataset are as follows: ID: variant rsIDChr: chromosome numberPosition: position in the chromosome, genome build GRCh37/hg19MarkerName: variant identifierAllele1: reference alleleAllele2: alternative alleleFreq1: allele frequency for allele2FreqSE: standard error of the allele frequencyMinFreq: the minimal allele frequency across studiesMaxFreq: the max allele frequency across studiesEffect: effect size for allele2StdErr: standard errorP-value: meta-analysis p-valueDirection: summary of effect direction for each studyHetISq: I^2 statistic which measures heterogeneity on scale of 0-100%HetChiSq: chi-squared statistic in simple test of heterogeneityHetDf: degrees of freedom for heterogeneity statisticHetPVal: P-value for heterogeneity statistic

Study phs000206

Center for Common Disease Genomics [CCDG] - Inflammatory Bowel Disease (IBD) - Global Microbiome Conservancy Host Exomes

The human body is a complex ecosystem, hosting tens of billions of bacteria, primarily in the gut. This community, known as the 'gut microbiome', is vital to human health, affecting functions ranging from metabolism, immunity, and development, to behavior. Conversely, reduced microbiome diversity and other imbalances of the gut community (dysbiosis) are associated with many diseases of the industrialized world, such as metabolic syndrome, asthma, and inflammatory bowel diseases among others. Microbiome-based interventions thus hold the potential to revolutionize our understanding of, and therapeutic approaches to, many aspects of human health and disease. Despite many advances, current understanding of the human microbiome is largely limited to majority ethnic groups in industrialized nations, and does not reflect the full diversity of human commensal microbiota. In addition to the scientific ramifications of minority underrepresentation, there are significant translational and ethical implications as well: First, failing to capture the full diversity of healthy human microbiota may limit our ability to understand and generate effective therapeutics for many microbiome-associated diseases. Second, underrepresented groups are less likely to benefit from microbiome-based medical advances tailored to well-studied populations, propagating healthcare inequities. The window of opportunity to characterize human microbiome diversity is closing rapidly. Human gut microbial diversity is diminishing around the globe, due to the spread of Westernized diets and lifestyles, which are associated with reduced microbiome biodiversity. The Global Microbiome Conservancy (GMbC) is a non-profit collaboration between scientists and communities around the world that aims to 1) preserve the full biodiversity of the human gut microbiome, 2) characterize its evolution across populations and host lifestyles and 3) investigate its interactions with the human host. We are collecting gut microbiome and human DNA samples from diverse populations around the world, from isolated groups to urbanized populations, to culture and study this essential biodiversity and to preserve it in a living "seed bank" as a long-term safeguard against future extinctions. The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of: Undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases. Understanding how best to design rare variant studies for common disease. Developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. Both exome and genotyping information of GMbC participants will help understanding how recruited human populations are structured and genetically related. This human genetic structure will be analyzed in light of gut microbiome compositional and genomic differences to illuminate associations between specific microbiome traits and human groups and the evolutionary processes involved in the co-evolution of human hosts and their gut microbiome. It will also provide variant information for critical genes shaping the composition of microbiomes, such as genes involved in innate and adaptive immunity (e.g. antimicrobial peptides) or in the regulation of the immune response (e.g. Nod2). Association studies between specific variants in these genes and microbiome features will be performed, which will then be validated with in vitro and in vivo experiments. Human data from GMbC cohorts will also increase the genetic diversity of human populations, providing additional variant information for many susceptible loci that were found to be associated with Crohn's disease and ulcerative colitis. The whole genome sequencing data generated is comprised of samples from diverse and indigenous populations. Raw sequencing data, metadata, vcf and phenotype data at the individual level for a subset of the cohort's samples are available at https://anvilproject.org/data. For questions about availability, contact help@lists.anvilproject.org. Microbiome data for the samples sequenced in this study can be found in phs002235 Global Microbiome Conservancy Sequence Data.

Study phs002205

Trial of Late Surfactant for Prevention of Bronchopulmonary Dysplasia: A Study in Ventilated Preterm Infants Receiving Inhaled Nitric Oxide (TOLSURF-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 assess whether late surfactant treatment in extremely low gestational age newborn (ELGAN, ≤28 week gestation) infants requiring ventilation at 7-14 days safely improves survival without bronchopulmonary dysplasia.Background: Bronchopulmonary dysplasia (BPD) is the most common form of chronic lung disease in children with an estimated 15,000 new cases annually in the United States. BPD affects infants born prematurely, is a major contributor to the cost of prematurity each year, and is associated with long-term pulmonary disability, neurodevelopmental abnormalities and death.Increases in the survival of ELGAN infants have resulted in another form of BPD, which is characterized by impaired alveolar and microvascular development with excess tone and reactivity of airway smooth muscle. Despite treatments to enhance lung maturation, premature infants often need prolonged intubation and mechanical ventilation and/or oxygen support. When mechanical ventilation is required longer than 7 days, BPD results in 70% of surviving ELGAN infants. Most of these infants experience clinical episodes of increased requirement for ventilatory support that are associated with dysfunctional surfactant, which is primarily due to low surfactant protein B (SP-B). In pilot studies of late surfactant treatment in premature infants, there was short-term improvement in SP-B content. These prior studies provided the rationale for a larger clinical trial for later doses of surfactant treatment to prevent episodes of respiratory decompensation and BPD. Participants: 511 infants were eligible for randomization of the 2693 infants screened. Of the 511 infants eligible for randomization, there were 252 infants allocated to the treatment arm and 259 infants allocated to the placebo arm.Design: The study was designed to assess the effect of late doses of surfactant on survival without BPD at 36 weeks post menstrual age (PMA) in ELGAN infants who required intubation and mechanical ventilation between 7 and 14 days of age and were receiving Inhaled nitric oxide (iNO). Infants were stratified within clinical centers and gestational age groups and randomized to treatment with calfactant, a natural surfactant extracted from bovine lung lavage fluid, or a sham procedure.All infants received iNO according to the protocol used in the Nitric Oxide Chronic Lung Disease (NOCLD) trial. A masked syringe containing either a standard dose of calfactant for the treatment group, or air for the placebo group, was administered to the infant behind a screen by staff not involved in providing the infant's clinical care. Monitor and ventilator alarms were turned off during dosing to avoid unblinding of clinical staff. To accommodate research staff availability and infant instability, the dosing interval was not strictly set but could be repeated every 24 – 72 hours up to 5 doses if the infant still required intubation. Dosing could be discontinued by physician request or parental withdrawal from the study. Due to parental preference, the first infant in a multiple birth was randomized according to the randomization schedule and subsequent infants were assigned to the same treatment group. Follow-up to assess pulmonary and neurologic development continued until 2 years of age, with treatment group blinding maintained. The primary outcome was survival without BPD at 36 weeks PMA. Secondary outcomes included BPD at 40 weeks PMA, pulmonary outcome at 12–24 months of age, and neurodevelopmental outcome at 2 years of age. Conclusions: There were no significant differences observed between the treatment group and the control group for survival without BPD at 36 weeks or 40 weeks.

Study phs003899

A Pilot Study Using Next Generation Sequencing in Advanced Cancers: Feasibility and Challenges

In this study, we used NGS to identify somatic events in advanced stage cancer patients to demonstrate the feasibility for using this approach to improve patient treatment.

Study phs000657

Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype"

Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype" with Name: Menghong Yin Email address: menghong.yin@dkfz-heidelberg.de Associated affiliation: Translational Skin Cancer Research Lab (DKFZ)

Dac EGAC50000000168

DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy"

DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy" with Florian Janke (f.janke@dkfz-heidelberg.de) and Holger Sültmann (h.sueltmann@dkfz-heidelberg.de)

Dac EGAC50000000308

Amplicon sequencing of duodenal adenoma

The aim of this study is to analyze the methylation and mutation status of non-ampullary duodenal lesions in order to detect the genetic changes for predicting the progression to adenocarcinomas.

Study JGAS000352

Cancer Affected Patients - Data Access Committee

Access to the cancer cohort is made available by completing the data access agreement for review by the data access committee and will be granted to qualified investigators for appropriate use. Individuals requesting access to the data need to comply with the terms of a Data Access Agreement (DAA) and are requested to use the data only in approved and ethical ways.

Dac EGAC50000000037

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