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• The University of Hong Kong Intestinal Metaplasia Organoids Study scCNV 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 EGAD00001015423

• Genetic architecture of male infertility in India

  The dataset consists of whole exome and genome sequencing data from infertile males and his parent(s) and/or sibling(s)

  Dataset EGAD00001015606

• single-cell DNA and RNA from HGSOC samples using DNTR-seq.

  single-cell DNA and RNA from the same cells, for HGSOC samples using DNTR-seq technolgy.

  Study EGAS50000001643

• National Cancer Institute (NCI) Genome Wide Association Study (GWAS) of Lung Cancer in Never Smokers

  A genomewide study of lung cancer in never smokers Abstract and specific aims In the United States, lung cancer incidence and mortality rates have been steadily declining over the past decade, following decline in the prevalence of tobacco smoking. However, lung cancer remains the leading cause of cancer death, killing more patients than breast, colon, and prostate cancers combined. Although tobacco smoke is the predominant risk factor for development of lung cancer, some patients develop the disease without a history of tobacco smoking. About 10 - 15% of all lung cancers occur in lilfetime never smokers. This figure will increase as the proportion of never smokers increases in the population. Even at present rates, lung cancer in never smokers, if considered a separate disease, is 6th to 8th top cause of cancer death. The growing number of never smokers in the USA and other countries emphasizes the importance of understanding the epidemiology and biology underlying lung cancer in this group. Genetic polymorphisms associated with the risk of lung cancer in never smokers are expected to overlap with those associated with the risk of lung cancer in ever smokers only partially. Epidemiological, molecular and clinical data suggest that molecular mechanisms of LC may differ in smokers and non-smokers, implying that lung cancer in never smokers is a different disease compared to the lung cancer in smokers. One can expect that there should be stronger genetic component in the control lung cancer in never smokers because effects of the genetic factors in never smokers are unmasked by the lack of tobacco smoke exposure. The genetic epidemiology of lung cancer in never smokers has not been well explored, largely because of difficulties in accruing the needed sample size for association studies. We propose a multicenter (total 14 sites from the US and Europe) genomewide association study of lung cancer in never smokers with the following specific aims: Aim 1: To identify candidate SNPs influencing risk for lung cancer in never smokers using Discovery sample. In the Discovery phase we will genotype 1256 Caucasian cases and 1365 age- and gender-matched never smoker controls using the Illumina Human660W-Quad platform. In addition, we will include in the analysis 284 cases and 175 matched controls already genotyped on the 610Quad platform. In this phase we will only include the study sites that have collected blood specimens (MDACC, Mayo Clinic, Karmanos Cancer Institute, The University of Liverpool Cancer research Centre, Institute of Cancer Research in Sutton, and Lunenfeld Research Institute in Toronto, Canada). All the samples will be sent to the independent lab for genotyping, to reduce site-specific technical artifacts. The final sample will consist of 1540 cases and 1540 controls matched by study site. Aim 2: To perform the second phase (validation) analysis of significant SNPs identified in aim 1 using an independent set of cases and controls. SNPs associated with risk at the significance level of 0.01 or below in the discovery set will be included in the replication phase. The proposed threshold guarantees an adequate power to retain SNPs with the typical effect size of 1.3. We plan to carry 6000-7000 SNPs for validation. The independent replication set will include 800 cases and 800 controls, mostly from sites that collected tissue (Mayo Clinic, Karmanos Cancer Institute, UT Southwestern) or buccal specimens (UCLA), but also blood samples (Imperial College London, University of Pennsylvana, German Cancer Research Center, Heidelberg, National Research Center for Environment and Health, Neuherberg, Carmel Medical Center, Haifa). We will then perform a joint analysis to test the significance of the SNPs identified in the first stage using a stringent critical p-value of 10-7. There will be 2340 cases and 2340 controls in the joint set. Based on our experience with GWAS in smokers and assuming that genetic component in lung cancer risk in never smokers can be higher than genetic component in smokers, we expect to identify about 5-10 candidate regions associated with lung cancer risk in never smokers. Aim 3: To identify and explore pathways associated with the risk of lung cancer in never smokers. Results of the number of studies on the molecular mechanisms and drug response suggest that lung cancer in never smokers is a different disease and different pathways will be associated with lung cancer risk in non-smokers and smokers. To identify pathways and molecular functions associated with lung cancer risk in never smokers we will apply Ingenuity and DAVID bioinformatics tools. We will use at least 300 top candidate genes identified in joint and discovery analysis. The reason why we select rather large number of candidate genes for functional annotation is two-fold: 1. Both algorithms are looking for enrichment of pathways and function by most significant genes and they produce statistically robust results only when number of genes is relatively high. 2. Despite the fact that this study will be largest possible for never smokers we still are underpowered to detect SNPs with relatively small effect size. But though those SNPs will not reach genome wide level of significance they will tend to be on the top of the list. In other words genes from the gray zone (significant on individual level and non-significant for genome wide level) are expected to be enriched by true discoveries. True discoveries are likely to be associated with limited number of pathways / functions while false positives are expected to be uniformly distributed across functions and pathways. Therefore significant clustering of the gene to a given function will suggest that that those genes are true discoveries. This is the first GWAS aiming at identifying the genetic control of susceptibility to lung cancer in Caucasian never smokers. We will combine the available resources from the multiple sites to achieve the sample size sufficient for this study. The study will identify genetic architecture of the predisposition to the lung cancer in never smokers.

  Study phs000634

• Uncovering RNA Signatures of C9orf72-Linked ALS and Related Disorders

  Substantial clinical and pathological variability has been reported in patients carrying an expanded repeat in C9orf72, who are generally diagnosed with amyotrophic lateral sclerosis (ALS) and/or frontotemporal dementia (FTD). Emerging evidence suggests that C9orf72 expression, RNA foci, and dipeptide-repeat proteins contribute to C9orf72-related diseases; however, the majority of the clinicopathological variability remains unexplained. We hypothesize that RNA sequencing (RNA-Seq) might reveal individual genes or groups of highly correlated genes (modules) that could account for this variability, which may help to identify much-needed druggable targets and/or biomarkers. Our preliminary studies performed in the frontal cortex, where we compared C9orf72 expansion carriers to (disease) controls, demonstrated that the top differentially expressed gene was C9orf72 itself. We also noticed that differentially expressed genes were enriched for the endocytosis pathway, which is consistent with the reported function of the C9orf72 protein in vesicle trafficking. Furthermore, we detected a module enriched for vesicular pathways, and additionally, we discovered an association with survival after onset for several promising candidates involved in vesicular transport. To find new therapeutic targets and biomarkers, here we have completed RNA-Seq on an increased number of samples to examine another relevant region: the cerebellum. As such, we performed RNA-Seq on a well-characterized cohort of C9orf72 expansion carriers, patients without this expansion, and control subjects without neurological diseases. We used multivariable linear regression models for gene-level analysis, weighted correlation network analysis for module-level analysis, and leafcutter for splicing analysis. Using the cerebellar RNA-Seq data, we found a large number (>6,000) of differentially expressed genes, with a notable increase in expression of homeobox genes in C9orf72 expansion carriers, as well as many gene modules that were associated with C9orf72 expansion status. Additionally, using leafcutter, we detected over 1,000 differential splicing events and an increase in the number of cryptic splicing events in C9orf72 expansion carriers.

  Study phs003065

• National Institute of Neurological Disorders and Stroke (NINDS), Family Study of Essential Tremor (FASET), Identification of Susceptibility Genes for Essential Tremor

  The Familial Study of Essential Tremor (FASET) was designed to identify susceptibility genes for Essential Tremor. ET is among the most common neurological diseases with a prevalence (age > 40 years) estimated to be 4.0% and prevalence in advanced age (> 90 years) exceeding 20%. ET, often referred to as "familial tremor", is generally regarded as a highly genetic disorder with families, with affected members over multiple generations, and twin studies show high concordance among monozygotic twins. Probands (affected with ET) and relatives were enrolled in a family study of ET at Columbia University, New York between 2011 - 2014. The study was approved by the Institutional Review Board at Columbia University and written informed consent was obtained from all enrollees. The criteria for enrollment were: 1) the proband had early-onset ET with age at onset < 50 years, 2) the proband had a diagnosis of definite or probable ET, 3) in addition to the proband, there were at least two affected relatives in the family, 4) additional affected and unaffected family members were willing to participate in the study, and 5) the families contained more than two affected individuals in different generations. Blood samples were also collected for genetic research. For the genetic analyses, we excluded enrollees that we or others had diagnosed with Parkinson's disease (PD) or dystonia. The final sample includes 52 families (52 probands [affected with ET]) and 155 relatives). The number of affected individuals enrolled per family ranged from 3 - 7 (mean = 4.1). Genetic samples from FASET were analyzed with whole genome SNP genotyping (for linkage analyses) and whole exome sequencing. It is hoped that this resource will better help researchers to understand the genetic causes of ET and underlying disease pathogenesis.

  Study phs000966

• Heart Failure Network - Effectiveness of Ultrafiltration in Treating People with Acute Decompensated Heart Failure and Cardiorenal Syndrome (HFN CARRESS - BioLINCC)

  ObjectiveThe CARRESS trial examined the effectiveness of ultrafiltration compared with a strategy of diuretic-based stepped pharmacologic therapy on renal function and weight loss in patients with heart failure who have worsening renal function and persistent congestion.BackgroundAcute cardiorenal syndrome is defined as worsening renal function in patients with acute decompensated heart failure. It occurs in 25 to 33% of patients and is associated with poor outcomes. Current heart failure treatments focus on removing excess fluid buildup, however administration of intravenous diuretics may contribute to worsening renal function. Venovenous ultrafiltration is one alternative therapy that may be effective in patients with acute decompensated heart failure complicated by acute cardiorenal syndrome and persistent congestionSubjectsA total of 188 patients were randomized.DesignHospitalized subjects were randomly assigned to receive either ultrafiltration therapy or pharmacologic therapy. Ultrafiltration was performed at a fluid-removal rate of 200 ml per hour and loop diuretics were discontinued for the duration of the intervention. The addition of intravenous vasodilators or positive inotropic agents was prohibited, unless they were deemed to be necessary as rescue therapy. Patients assigned to stepped pharmacologic therapy received intravenous diuretics to manage congestion and maintain a urine output of 3 to 5 liters per day. In both groups, the assigned treatment strategy was to be continued until the signs and symptoms of congestion in the patient were reduced as much as possible. The primary end points were baseline changes in serum creatinine and weight as assessed at 96 hours after treatment assignment.ConclusionsThe use of a stepped pharmacologic-therapy algorithm was superior to a strategy of ultrafiltration for the preservation of renal function, and there was a similar amount of weight loss between the two groups. Ultrafiltration was associated with a higher rate of adverse events (Bart, et al., 2012, PMID: 23131078).

  Study phs003510

• Best Practices for DACs

  Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security.

  Documentation access/data-access-committee/best-practices

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• Sequencing of Cervical Cancer

  Precision mapping of genetic alterations in cancer can enable better selection of therapies and improved outcomes when combined with new sequencing diagnostics. We describe whole-exome sequences from cervical adenocarcinomas and paired normal samples in Hong Kong Chinese women. These data uncover a heterogeneous genomic landscape but identify commonly aberrant loci including FAT1, ARID1A, ERBB2 and PIK3CA that may provide a focus for the development of individualized targeted therapies for Chinese women with cervical adenocarcinoma.

  Study phs000723

• Autosomal recessive

  To define a genetic syndrome of combined immunodeficiency, severe autoimmunity, and developmental delay, 4 patients from two families who had similar syndromic features were studied. To identify disease-causing mutations, we performed whole exome sequencing for one patient and her healthy parent from Family 1 and also for one patient from Family 2. Disease segregated with novel autosomal recessive mutations in a single gene, tripeptidyl-peptidase II (TPP2) gene. The result defines a new human metabolic immunodeficiency.

  Study phs000848

• Gene Expression of Small Cell Carcinoma of the Ovary-Hypercalcemic Type (SCCOHT)

  Small cell carcinoma of the ovary-hypercalcemic type (SCCOHT) is a rare and aggressive form of ovarian cancer afflicting young women at a median age of 24 years. SCCOHTs are characterized by loss of protein expression of SWI/SNF chromatin remodeling ATPases SMARCA4 and SMARCA2 through mutation and epigenetic silencing, respectively. This study aims to establish gene expression profiles of this cancer through RNA-Seq of fourteen pathologically confirmed cases of SCCOHT tumors.

  Study phs001528

• The Immunogenetics of Measles Immunity - Measles (MMR) vaccination (NIAID/NIH)

  To examine the role of gene polymorphisms (including functional studies of SNPs) on variations in vaccine-induced immune responses, in approximately 3,000 healthy school-age children, adolescents and young adults/adults, who were vaccinated with measles-containing vaccine (MMR). To achieve greatest power to detect SNPs associated with measles-specific immune response phenotypes, we pooled our data across three genotyping platforms and three cohorts (US cohort, San Diego cohort and Rochester cohort).

  Study phs001630

• Myocardial Infarction Genetics Exome Sequencing Consortium: U. of Leicester

  MI cases were ascertained from two studies: (i) the British Heart Foundation Family Heart Study and (ii) the BRICCS Study. Control subjects were ascertained from the control subjects being recruited as part of the UK Aneurysm Growth Study (UKAGS). All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs001000

• Ataxia Gene Identification by Integrated Genomic Analysis

  Ataxias are a group of diseases that result in a lack of coordinated muscle movement. Hereditary ataxias are genetically heterogeneous and it is reported that 40% of suspected genetic ataxias currently have an unknown cause. We used exome sequencing to detect mutations responsible for ataxia. We sequenced, when available, multiple individuals per family to identify family specific mutations and further confirmed segregation of variants using samples from available affected and unaffected family members.

  Study phs000757

• Neoadjuvant Pazopanib in Renal Cell Carcinoma

  This study examined the tissue of patients who received oral pazopanib prior to nephrectomy. Patients were consented and underwent a pre-treatment biopsy. Pretreatment samples for analysis were preserved as available. Subjects underwent a proscribed course of treatment with pazopanib. At the completion of treatment, subjects underwent a planned nephrectomy, and samples were collected from the nephrectomy specimen. We recorded response to treatment, adverse events, and 2 year follow up for recurrence.

  Study phs002053

• FusionSeq: a modular framework for finding gene fusions by analyzing Paired-End RNA-Sequencing data

  We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts such as misalignments or random pairing of transcript fragments and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including 8 cancers with and without known rearrangements.

  Study phs000311

• NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study

  Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE).Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000287.

  Study phs001368

• Single-cell RNA sequencing of human IL-18R supported CAR T cells targeting oncofetal Tenascin C

  C.TNC-CAR.Zip18R CAR-T cells are from 2 donors and multiplexed 10x Genomics scRNA-seq were performed with a hashtag to label each sample. For tumor and CAR-T cell cocluture samples, CAR-T cells were extracted from 3 time points. The raw data are fastq format for total 20 samples considering sequencing lanes. The multiplexing information, CAR and Zip18R sequences are deposited in analyses.

  Study EGAS50000000772

• Measurement of the Male Germline Mutation Rate Using Sequential Sperm Samples

  We recalled 23 sperm donors with prior banked samples to provide a new sperm sample. The old and new sequential sperm samples were then profiled by high-fidelity duplex sequencing to measure individual-specific mutation rates and patterns. We also performed deep whole-genome sequencing of sequential sperm samples from two individuals followed by targeted validation, which measured remarkably stable mosaicism of clonal mutations that likely arose during embryonic and germline development.

  Study phs003716

• Comparison Across Multiple Types of Sleep Deprivation

  This study is designed to assess neurobehavioral performance, as well as molecular and physiological changes associated with variations in timing and quantity of sleep. Gene expression changes associated with neurobehavioral (cognitive) performance were assessed in a time-series among individuals randomly assigned to four separate sleep conditions during a 10-day inpatient study: a well-rested control, sleep restriction with nighttime sleep, sleep restriction with daytime sleep to roughly simulate shiftwork schedules, and total (acute) sleep deprivation.

  Study phs003924

• Bulk RNAseq from in vitro generated macrophages and T cells, and mUM tumour biopsies

  Monocyte derived macrophages were polarised into M1 or M2 using IFNg+ ILP or IL-4 respectively (n =4) . Pan T cells were cultured with or without IL-2 for 4 days (n=4 - 6). Pan T cells were co-cultured with THP1 tumour cells for 20 hours in the presence or absence of ImmTAC molecules and in the presence or absence of M2 macrophages. Sorted T cells and macrophage populations prior and post co-culture were analysed by bulk RNA sequencing (60 million reads per sample) using the Illumina NovaSeq system. Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system

  Dac EGAC50000000518

• The Heterogeneity Study of HeLa S3 Cells Based on Full-Length Single-Cell RNA-Seq

  In this study, we produced full-length RNA-seq data of 45 single HeLa S3 cells, 8 replicates of 10 pg total RNA and one 5 ng total RNA from HeLa S3 cell population. Using this data, we investigated the heterogeneity of HeLa S3 cells in gene expression, alternative splicing, fusion and HPV-host fusion and expression. This study provides comprehensive transcriptomic characters of HeLa S3 cells at the single cell level.

  Study phs001029

• Genetic analyses in patients with T or NK cells-associated disorders

  We conduct somatic gene mutation analysis in various diseases involving T cells or NK cells and clarify the gene mutation profile. By comparing clinical information and the results of mutation analysis, we will identify gene groups that influence the onset and refractoriness of the disease. As the analysis continues, the results of mutation analysis may become part of diagnostic criteria in the future, or provide basic data for the development of new therapeutic agents.

  Study JGAS000658

• Genetic analyses in patients with T or NK cells-associated disorders

  We conduct somatic gene mutation analysis in various diseases involving T cells or NK cells and clarify the gene mutation profile. By comparing clinical information and the results of mutation analysis, we will identify gene groups that influence the onset and refractoriness of the disease. As the analysis continues, the results of mutation analysis may become part of diagnostic criteria in the future, or provide basic data for the development of new therapeutic agents.

  Study JGAS000709