Search Results - EGA European Genome-Phenome Archive

Whole genome sequencing in prime-edited human organoids

We performed whole genome sequencing to detect possible off-target mutations induced by prime editing. Liver organoids, derived from a healthy control, were transfected with either control (GFP) plasmids or prime editing plasmids (GFP+PE2+pegRNA+nickRNA) to induce a 6-bp deletion in CTNNB1. One control and two prime-edited organoid lines were clonally expanded from single cells. High-throughput sequencing was performed on the complete genomic DNA isolated from these clonal lines, as well as the starting culture (bulk). After correction for germline mutations in the starting culture, new mutations in the control and prime-edited lines were compared. The same approach was followed in small intestinal organoids, derived from a patient with disease-causing 3-bp deletion in DGAT1. In these small intestinal organoids, prime editing was used to insert the 3 missing nucleotides. Two corrected clones were compared to one control clone.

Dataset EGAD00001006352

Chromoanasynthesis as a Cause of Jacobsen Syndrome

Jacobsen syndrome (OMIM #147791) is a rare multisystem genomic disorder involving craniofacial abnormalities, intellectual disability, other neurodevelopmental defects and terminal truncation of chromosome 11q, typically deleting ~170 to >340 genes. We describe the first case of Jacobsen syndrome caused by congenital chromoanasynthesis, an extreme form of complex chromosomal rearrangement. Six duplications and five deletions occurred on one copy of chromosome 11q with microhomology signatures in the breakpoint junctions, indicating an all-at-once replication-based rearrangement mechanism in a gametocyte or early post-zygotic cell. Eighteen genes were deleted from the Jacobsen region, including KIRREL3, which is associated with intellectual disability. Patients of any age with abnormal immune function who have recurrent or unusual infections, whose blood tests show evidence of immune dysfunction, or who have GVHD, XSCID, CGD or LAD may be eligible for this study. Patients' parents, siblings, grandparents, children, aunts, uncles and first cousins of any age also may be included. Healthy normal volunteers between 18 and 85 years of age are recruited as controls.

Study phs002036

Investigating Genetics in Suspected Congenital Syndromes

We employed forward and reverse genetics to identify individuals with heterozygous JAK1 variants associated with autoimmune and inflammatory diseases. We first recruited six unrelated probands and seven affected family members presenting with a range of autoimmune and inflammatory conditions. Whole exome sequencing revealed 4 different variants spanning all domains of the JAK1 protein: FERM domain (chr1: 64873438-G>A; c.415C>T; p.E139K), SH2 domain (chr1: 64855641-G>A; c.1516C>T; p.R506C), pseudokinase domain (chr1: 64845529-C>T; c.2099G>A; p.S700N, and kinase domain (chr1: 64838479-C>T; c.2953G>A; p.V985I). We then performed a systematic review of electronic health records of the BioME BioBank database and identified 43 additional individuals with at least one of these JAK1 variants. Comparing variant-positive and variant-negative individuals, our study revealed increased occurrences of autoimmunity, atopy, colitis, and dermatitis in patients harboring these JAK1 gain-of-function variants. We have deposited in dbGaP the whole exome sequencing files of the 43 patients identified in the BioME biobank, as well as their phenotype information.

Study phs003453

HiDEF-seq Single-Molecule Sequencing of Single-Strand Mismatches and Damage

Our study sought to resolve, with single-molecule resolution, the mismatches and damage events that precede DNA mutations. Using a novel single-molecule, long-read sequencing method (HiDEF-seq) we detected base substitutions when present in either one or both DNA strands. We compared the fidelity for dsDNA mutations to that of the same samples profiled by NanoSeq duplex sequencing. We also detected cytosine deamination, a common type of DNA damage, with single-molecule resolution. We profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes. These samples revealed single-strand mismatch and damage signatures. Since double-strand DNA mutations are only the endpoint of the mutation process, our approach enables new studies of how mutations arise in a variety of contexts, especially in cancer and aging.The data available via dbGaP includes raw HiDEF-seq sequencing files (Pacific Biosciences subreads in BAM format), raw NanoSeq sequencing files (Illumina FASTQ format), and raw germline sequencing files (Illumina FASTQ format).The HiDEF-seq main publication contains a supplementary table with a list of accession IDs for each sample's files.

Study phs003604

Upper cortical layer-driven network impairment in schizophrenia

Schizophrenia is one of the most wide-spread and complex mental disorders. To characterize the impact of schizophrenia, we performed single nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. Additionally, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most dramatic - in upper layer GABAergic neurons, including downregulation in energy metabolism and upregulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Finally, Visium spatial transcriptomics further corroborated upper layer neuron vulnerability in schizophrenia. Overall, our results point towards general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology. Study is available on bioRxiv (https://doi.org/10.1101/2020.11.17.386458) and in upcoming publication.

Study EGAS00001006495

MATCH-molecular driver

Patients were biopsied at progression on molecular targeted agents and WES and/or WTS were performed to identify resistance mechanisms. 271 underwent one or sequential tissue biopsies.

Dataset EGAD50000000697

Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee

Four iPSC line data were sequenced by WGS. One of them has gene MYBPC3 modified.

Dataset EGAD00001005066

Matched FF and FFPE WGS from a metastatic prostate tumor

This dataset contains three bam files. One normal blood sample and two matched FF and FFPE samples from the same metastatic prostate tumor.

Dataset EGAD00001006180

Whole exome and whole genome sequencing of pancreatic cancer

These are seven sequencing files form whole exome and whole genome of five tissue samples collected from one pancreatic cancer patient

Dataset EGAD00001003261

RNA-seq of multi-regional CRC samples

BAM files of RNA sequencing (RNA-seq) experiment on multi-regional colorectal cancer (CRC) samples. 58 samples corresponding to 16 patients were sequenced and there is one BAM file for each sample.

Dataset EGAD00001006164

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

Clinical data

Clinical data for IMpower150 (one patient per line): anonymized_patient_id, train_test_split, ctDNA_status, ARM1, OS_months, OS_event, PFS_months, PFS_event, TTEOS_rebaseline_BL, TTEPFS_rebaseline_BL, TTEOS_rebaseline_C2D1, TTEPFS_rebaseline_C2D1, TTEOS_rebaseline_C3D1, TTEPFS_rebaseline_C3D1, TTEOS_rebaseline_C4D1, TTEPFS_rebaseline_C4D1, TTEOS_rebaseline_C8D1, TTEPFS_rebaseline_C8D1, pdl1_high, number_metastatic_sites, baseline_ECOG, age, sex_female, history_of_tobacco_use, sld_baseline, sld_wk6, sld_percent_change_bl_to_wk6, sld_difference_bl_to_wk6, AGEGRP, tumor_assessment_week_6, tumor_assessment_week_12, tumor_assessment_week_18, tumor_assessment_week_24, PFS_days, days_between_randomization_c3

Dataset EGAD00001009726

71 Whole-exome sequencing of Esophageal Squamous Cell Carcinoma on Chinese Patients

Esophageal Squamous Cell Carcinoma (ESCC) is one of the deadliest cancers worldwide. We performed 71 Whole-exome sequencing of Esophageal Squamous Cell Carcinoma on Chinese Patients.

Dataset EGAD00001001926

Illumina genome sequencing data for HICF2 craniosynostosis families (Genome Medicine)

BAM files for two families recruited to the HICF2 genome sequencing project due to craniosynostosis. One family is a singleton and the other is an affected mother-daughter duo.

Dataset EGAD00001011373

Whole Exome Data of RFWD3 Fanconi anemia patient

Dataset contains one sample derived from gDNA of human fibroblasts. Files are in FASTQ format and were generated using the Agilent SureSelect Human All Exon 50Mb Kit and followed by Next Generation Sequencing on a HighSeq2000 instrument (Illumina).

Dataset EGAD00001003311

SLC9A3R1 variant associated with age-related hearing loss

The dataset contains one BAM file that includes a SLC9A3R1 variant identified in two Italian patients affected by age-related hearing loss. Data have been produced by targeted re-sequencing, using Ion Torrent PGM platform.

Dataset EGAD00001004171

paired-EXOME (WES) sequencing with SureSelect-V5+UTRs of B-cell lymphoma

Tumors and control of nodal B-cell lymphoma of one patient. WES sequencing on Illumina HiSeq 4000 with Agilent SureSelect V5+UTRs. Bam files were aligned with bwa mem to hg19.

Dataset EGAD00001006059

MOMA Data Access Committee

Dac EGAC00001000145

Data Access Committee for Deciphering Developmental Disorders (DDD) Project

Dac EGAC00001000282

B-lineage cells in coeliac disease Data Access Committee

The DAC will be made up of: Ida Lindeman ida.lindeman@medisin.uio.no (admin) Ludvig M. Sollid l.m.sollid@medisin.uio.no Rasmus Iversen rasmus.iversen@medisin.uio.no

Dac EGAC50000000162

Roifman DAC

This Data Access Committee will oversee all requests for data submitted by Dr. Chaim Roifman at the Hospital for Sick Children in Toronto, Canada. Requests should be directed by email to chaim.roifman@sickkids.ca.

Dac EGAC50000000396

Whole-Genome Sequencing in Multiplex Epilepsy Families

Epilepsy is one of the most common neurologic disorders, affecting approximately 4% of individuals at some time in their lives. More than 30% of people with epilepsy continue to have seizures despite treatment, and improved approaches to treatment and prevention are sorely needed. In the search for new strategies to reduce the burden of disease, the discovery of specific genes that influence risk offers a novel opportunity to clarify pathogenic mechanisms, identify susceptible individuals prior to seizure onset, and treat and prevent seizures in people at risk. Despite clear evidence of the importance of genetics in susceptibility to epilepsy, only limited progress has been made in identifying the specific genes that influence risk. One of the greatest challenges for genetic research on this disorder is its extreme clinical and genetic heterogeneity. Although epilepsy is broadly defined by recurrent unprovoked seizures, it is so variable in its clinical manifestations, natural history, and treatment response that most epileptologists view it as a collection of different syndromes ("epilepsies") with distinct etiologies. The genetic effects on susceptibility are also likely to be extremely variable, ranging from rare variants with high penetrance (some of which produce Mendelian patterns of inheritance) to common variants with low penetrance. Recent findings strongly suggest that rare gene variants play a major role in the genetic architecture of the epilepsies. The purpose of this study was to discover new genetic risk factors for epilepsy. The primary approach was to use whole-genome sequencing to interrogate classes of genetic variants, including very rare variants, in multiplex families. Our main hypothesis was that, in at least some proportion of these families, a single variant would explain all instances of epilepsy. Variants identified within the families could then be tested for cosegregation within the family and also validated by seeing enrichment in sporadic epilepsy cases. Furthermore, understanding the impact of rare variation in epilepsy also has the potential to provide insight into the genetic architecture of other complex human diseases. Our analysis focused on families containing multiple individuals with non-acquired (idiopathic or unknown cause) epilepsy under the hypothesis that these would be enriched for genetic control. The families studied had been previously collected and phenotyped in detail, and contain an average of 3.8 individuals per family with a range of different types of epilepsy. We selected one or two affected individuals from each family for sequencing. This work has generated NGS data on 60 samples from 29 multiplex epilepsy families. We have established that, under a monogenic model of inheritance, sequencing pairs of distantly related relatives is an effective method for reducing the number of candidate variants. Critically, we have found that no single variant can explain a large proportion of these epilepsy families. This work emphasizes that identifying causal variants among the many genetic candidates found in this work will require very large sample sizes and gene-based analyses.

Study phs000690

NHLBI TOPMed: Genomic Summary Results for the Trans-Omics for Precision Medicine Program

The NHLBI Trans-Omics for Precision Medicine (TOPMed) program aims to identify the genetic basis of variation in biomedical phenotypes, with emphasis on those related to heart, lung, blood and sleep disorders, as part of a broader Precision Medicine Initiative. The TOPMed program has provided whole genome sequencing (WGS) to over 80 different studies that had previously recruited participants and collected extensive phenotype data. Many TOPMed investigators affiliated with these studies have organized their activities into phenotype-focused Working Groups and have developed genotype-phenotype association projects. These analyses have resulted in valuable cross-study Genomic Summary Results (GSR) that include whole genome association test results of both common and rare variants. Most of the analyses include data from multiple studies, some of which are based on sensitive populations, precluding public sharing of GSR. This dbGaP accession provides a mechanism for sharing sensitive GSR, using the controlled-access mechanisms of dbGaP to provide protections for sensitive populations.

Study phs001974

Characterizing the Neurobehavioral Phenotype(s) in MPS III (Pilot Study)

Mucopolysaccharidosis III (MPSIII) syndrome is characterized by a severe cognitive decline ending in dementia and death. MPSIII is also associated with a range of abnormal and disruptive behaviors that can include, but go well beyond, childhood noncompliance and oppositionality. The purpose of this study is to conduct a cross-sectional investigation to identify the behavioral phenotype and its neural basis in MPSIII. An overall goal of this research is to develop easily administered, sensitive and specific neurobehavioral markers to characterize the behavioral phenotype(s) of MPSIII, track their progression, and to delineate their possible neural substrates. The study looks to develop develop a sensitive and specific behavioral rating of disease progression in MPS III which can be used for clinical outcome studies. The research objectives are: Develop a measure for the use of health professionals to use in tracking MPSIII phenotypes and disease progression. Test our model of MPSIII with objectively recorded behaviors in a well-defined experimental setting. Elucidate the neural bases of MPSIII by correlating behavioral profiles with changes in brain structures through quantitative neuroimaging. Determine the relationship between the loss of cognitive functions and development of behavioral abnormalities in MPSIII. This is an observational pilot study that will enroll 45 individuals with MPS III Type A or B. Those participating in the study will be evaluated during a one-day assessment and chart review.

Study phs001330

(Epi)genetic Risk Architectures of Opioid-Dependent Brain

With nearly 20,000 overdose deaths in 2014 alone, opioid addiction (OA) has emerged as one of the most pressing public health crises in recent US history. One-fifth of individuals who try heroin develop an addiction to opioids. Genetics is a major contributor to OA with an estimated 60% heritability, only somewhat less than schizophrenia (80%) which has recently seen substantial gains in identified underlying genetics. Yet, studies to date have failed to uncover most of the genes that predispose individuals to OA, leaving the overwhelming fraction of OA heritability unexplained. The proposed study takes a novel, integrated "omics-based" strategy to investigate the molecular basis of OA and uncover both genetic and epigenetic factors associated with opioid addiction. The premise for our approach is founded on studies from our labs, and others, implicating regulatory variation in common traits and diseases, including those associated with complex brain phenotypes like addiction. We have collected the largest known cohort of postmortem brains from addicts who overdosed on opioids, along with matched control brains from non-users. From both cases and control specimens, we will isolate cells from 2 regions of the brain closely implicated in the addiction phenotype: the Prefrontal Cortex (PFC) and the Nucleus Accumbens (NAc). In Aim 1, we propose ChIP-seq studies to identify regulatory elements that distinguish cases from controls and define the opioid addiction phenotype. The regulatory differences will be connected to their gene targets through high resolution in situ Hi-C. In Aim 2, we propose QTL-based approaches to identify genetic variants that underlie the regulatory differences (hmQTLs). We also propose eQTL analyses to identify genetic variants that underlie differences in transcript levels between cases and controls. Aim 3 leverages the largest heroin addiction GWAS meta-analysis to date to test the hypothesis that SNPs in regions associated with chromatin and expression differences between cases and controls define novel loci for predisposition to OA. Each Aim has the potential for discovery independent of the others (differential HM, RNAexp, QTLs, and variant-phenotype associations) but their synergy is the most powerful component of the proposed study: identifying regulatory pathways that generate, not only phenotype associations, but hypothesized mechanisms for those associations which can be the focus of new opioid addiction prevention and treatment development.

Study phs002724

Data generated by the Drier Lab at HUJI

This Data Access Committee is responsible to all data generated by and deposited by the Drier Lab at the Faculty of Medicine of the Hebrew University of Jerusalem (http://yotamdrier.ekmd.huji.ac.il/)

Dac EGAC50000000060

Policy to access RNAseq Patient Derived Sézary syndrome cells

This is the policy for accessing the RNAseq raw data associated to the project 'Diverse transcriptomic and mutational patterns but limited functional pathway alterations in patient-derived SS cells'

Dac EGAC50000000693

McGill Reproductive Genetics Data Access Committee

Committee at RI-MUHC (Slim Lab) that reviews requests for controlled human genetic/phenotypic data generated in reproductive genetics/infertility studies. Ensures requests comply with participant consent, ethics approvals, and institutional policies.

Dac EGAC50000000775

RNA profiles of human placentas

This DAC addresses the control of the access to the RNA-seq of the human placentas. It covers the project "Decoding human placental cellular and molecular responses to maternal obesity and fetal growth"

Dac EGAC50000000505

National Sleep Research Resource (NSRR): Cleveland Family Study (CFS)

The Cleveland Family Study (CFS) is a family-based study of sleep apnea, consisting of 2,284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study began in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. National Institutes of Health (NIH) renewals provided expansion of the original cohort, including increased minority recruitment, and longitudinal follow-up, with the last exam occurring in February 2006. The CFS was designed to provide fundamental epidemiological data on risk factors for sleep disordered breathing (SDB). The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first-degree relatives, spouses and available second-degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first-degree relatives. Each exam, occurring at approximately 4-year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. Currently, data of 710 individuals are available for use through BioData Catalyst (with genotype data available through dbGaP).The National Sleep Research Resource (NSRR) is a NIH-supported sleep data repository that offers free access to large collections of de-identified physiological signals and related clinical data from a large range of cohort studies, clinical trials and other data sources from children and adults, including healthy individuals from the community and individuals with known sleep or other health disorders. The goals of NSRR are to facilitate rigorous research that requires access to large or more diverse data sets, including raw physiological signals, to promote a better understanding of risk factors for sleep and circadian disorders and/or the impact of sleep disturbances on health-related outcomes. Data from over 15 data sources and more than 40,000 individual sleep studies, many linked to dozens if not hundreds of clinical data elements, are available (as of Feb. 2022). Query tools are available to identify variables of interest, and their meta-data and provenance.

Study phs002715

Exceptional Responders Initiative

The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is < 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

Study phs001145

EGA metadata schema

EGA Schemas In this page, you will find information on how the European Genome-phenome Archive (EGA) manages its metadata standards using both XML Schema Definition (XSD) and JavaScript Object Notation (JSON) formats. If you are not sure what this means, you may want to explore our brief metadata introduction. This information may be of your interest if you are planning to learn more about how the EGA is built and how to wrap around it for other processes. Nevertheless, if you are a common user (e.g. submitter or requester), you would not have to worry about these schemas nor their format, since they are implemented in user-friendly ways for you. Metadata standards are rules that define how to format and structure data of metadata objects (i.e. entities), like EGA's samples or experiments in a consistent manner. These objects are the nodes of the metadata model of the EGA (Figure 1). Figure 1. Diagram of EGA's metadata model. The model's building blocks are objects (e.g. sample), which can reference each other (e.g. an experiment referencing the used samples). Once your files are uploaded, they can also be referenced by Runs and Analyses. The submission object is an object itself that compiles many others. At EGA, we inherit our metadata schemas from the European Nucleotide Archive (ENA), and we have expanded them to include bespoke objects such as "Policy", "Dataset", and "DAC" (Data Access Committee) for our specific use-case: handling sensitive human data. See below a list of all our metadata objects and some context for each. Metadata Object EGA accession Description Examples of metadata fields Study EGAS… Information about the study Study type, study title, study abstract… Sample EGAN… Information about the used samples in the experiment or analysis Taxon ID, scientific name, biological sex, phenotype… Experiment EGAX… Information about the performed experiment Used libraries, sequencing platform, reference to the used samples… Analysis EGAZ… Contains information about the analysis Type of analysis, used assembly, reference sequence… Run EGAR… The run holds information about the files containing the raw reads generated in a run of sequencing Platform, spot descriptor, raw file references… DAC EGAC… Contains information about the Data Access Committee (DAC) DAC contacts, contact emails… Policy EGAP… Contains the Data Access Agreement (DAA) and policy which its usage complies with Policy text, data use ontologies (DUO) codes… Dataset EGAD… Contains the collection of runs/analysis to be subject to controlled access Dataset type, compilation of Run's and Analysis' IDs There are two different sets of schemas, based on their formats, in which the EGA accepts metadata: XSDs (for XML files) and JSON Schemas (for JSON files). EGA's XML Schema Definition . When programmatic submissions are pushed through the European Bioinformatics Institute (EBI) system, XML format is used. The schemas that are applied for this format are defined in XML Schema Definition (XSD) files, which can be found at ENA's GitHub repository. You can find more information on how to validate and submit your data programmatically in our programmatic submission documentation. Furthermore, see at our GitHub repository some XML examples with either made-up values (similar to what you would submit) or descriptive values for each field (just for documentation). EGA's JSON Metadata Schemas . When programmatic submissions are pushed through the Centre for Genomic Regulation (CRG) system, JSON format specifications are used instead. See the full JSON specifications for further details. In conclusion, the EGA metadata schemas are crucial for maintaining the quality and consistency of submitted data. By understanding and following the rules outlined in these schemas, you can ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource. Sample checklists Besides the standards in our schemas, we have another layer called Sample checklists. These are another system that the EGA inherits from ENA, and specifies what attributes are required or allowed for a sample object. The EGA uses these checklists to enforce that, for example, a sample object has the three mandatory attributes: subject ID, sex and phenotype of the individual the sample was taken from. When you submit to EGA, our checklist is automatically selected by default.

Documentation submission/metadata/ega-schema

ICGC Data Access Compliance Office

To access Controlled Access ICGC data at the EGA you must first apply for access on the DACO form. Instructions on this process is available from this web site: http://docs.icgc.org/portal/access/

Dac EGAC00001000010

The EGA at the International Congress of Human Genetics

Today is the start of the International Congress of Human Genetics (ICHG). This event, hosted by the African Society of Human Genetics (AfSHG) and the Southern African Society for Human Genetics (SASHG), will reunite international experts to highlight how genomic technologies are being managed to address challenges generated by the current status of Human Health and Genomics. The European Genome-phenome Archive (EGA) will be at the Congress participating in workshops, meetings and talks where topics such as data access and discovery as well as the Federated EGA will be present. Data access and discovery In the context of the “Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. Data access and discovery In the context of the “ Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. During the last four years, CINECA has been identifying gaps in data sharing between Africa, Canada and Europe in order to build a federated solution for data access. Thomas Keane will present the project within the sessions happening the 24ᵗʰ. The Federated EGA at the ICHG A Federated EGA poster will be shown during the Poster Session 1 that will take place the 23ʳᵈ. The objective is to bring awareness of the European Genome-phenome Archive as a resource for permanent archive and secure data sharing. In this context, the network generated by the Federated EGA is key for cases where research data cannot be shared outside local jurisdictions. The Federated EGA was officially launched on 2022 with research institutes from five countries becoming the first nodes of this network. Nowadays, with more than 20 nodes preparing to join, it aims to become the largest human omics data sharing initiative towards understanding human health and disease. The H3Africa Initiative and the African research represented in the EGA 1.1% of the EGA studies include samples from African populations. Countries such as South Africa, Kenya, Uganda or Egypt, among others, are present in the 72.577 samples from African individuals archived at the EGA. 23 EGA datasets are managed by the Human Heredity and Health in Africa Initiative (H3Africa). This Initiative will celebrate its Consortium Meeting the 27ᵗʰ and 28ᵗʰ, back-to-back with the ICHG. H3ABioNet, the Pan African Bioinformatics Network for the H3Africa consortium, will also take this context to celebrate its 10-Year Symposium during the Congress. Members of the EGA team will attend both of them, as the H3ABioNet works in conjunction with H3Africa projects, to submit data to the European Genome-Phenome Archive.

Blog the-ega-at-the-international-congress-of-human-genetics

Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants and parents), NIDDK

Genetics of Kidneys in Diabetes (GoKinD) study is an initiative aimed at identifying susceptibility genes for diabetic nephropathy in type 1 diabetes. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents were also enrolled to form family trios. Altogether, GoKinD includes 3043 participants comprising 931 cases, 944 singletons, 268 pairs of parents of cases, and 316 pairs of parents of control. Accessible as a GAIN database are 905 of the cases, 890 of the controls, 10 pairs of parents of cases and 10 pairs of parents of controls (dbGaP phs000018 Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants), GAIN). The other parents and the remaining cases and controls are available by a separate application process through NIDDK. Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form available at http://www.niddkrepository.org or by contacting the Juvenile Diabetes Research Foundation.

Study phs000088

Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants), GAIN

Genetics of Kidneys in Diabetes (GoKinD) study is an initiative aimed at identifying susceptibility genes for diabetic nephropathy in type 1 diabetes. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents were also enrolled to form family trios. Altogether, GoKinD includes 3043 participants comprising 931 cases, 944 singletons, 268 pairs of parents of cases, and 316 pairs of parents of control. Accessible as a GAIN database are 905 of the cases, 890 of the controls, 10 pairs of parents of cases and 10 pairs of parents of controls. The other parents and the remaining cases and controls are available by a separate application process through NIDDK (dbGaP phs000088 Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants and parents), NIDDK). Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form available at Juvenile Diabetes Research Foundation. Consent groups and participant set Diabetic complications only (DCO): 1825 (904 cases, 881 controls, 40 others)

Study phs000018

NHLBI TOPMed: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE)

Started in 2007, the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) is one of the largest asthma cohort studies in the United States. Its overarching goal is to elucidate the genetic underpinnings of asthma and asthma medication treatment response. The cohort was recruited from a large health care system serving southeast Michigan and the Detroit metropolitan area, and the participants broadly represent the demographic and socioeconomic diversity of the region. Control participants (i.e., patients without a diagnosis with asthma) were recruited from the same health system and geographic region. By virtue of their health system enrollment, both asthma case and control patients have longitudinal clinical information which was routinely collected as part of their care. Both case and control patients underwent at detailed evaluation at the time of enrollment which included lung function testing and bronchodilator response. The SAPPHIRE cohort is a member of the Asthma Translational Genomics Collaborative (ATGC). The latter was selected for whole genome sequencing in Phase 3 of the National Heart Lung and Blood Institute's TOPMed Program. The SAPPHIRE sample selected for sequencing includes African American and/or Latino individuals with and without asthma.

Study phs001467

Japan PBC-GWAS Haplotype Study

Primary biliary cholangitis (PBC) susceptibility loci have largely been discovered through single SNP association testing. In this study, we report genic haplotype patterns associated with PBC risk genome-wide in two Japanese cohorts. Among the 74 genic PBC risk haplotype candidates we detected with a novel methodological approach in a discovery cohort of 1,937 Japanese, nearly two-thirds were replicated (49 haplotypes, Bonferroni-corrected P<6.8x10-4) in an independent Japanese cohort (N=949). Along with corroborating known PBC-associated loci (TNFSF15, HLA-DRA), risk haplotypes may potentially model cis-interactions that regulate gene expression. For example, one replicated haplotype association (9q32-9q33.1, OR=1.7, P=3.0x10-21) consists of intergenic SNPs outside of the human leukocyte antigen (HLA) region that overlap regulatory histone mark peaks in liver and blood cells, and are significantly associated with TNFSF8 expression in whole blood. We also replicated a novel haplotype association involving non-HLA SNPs mapped to UMAD1 (7p21.3; OR=15.2, P=3.9x10-9) that overlap enhancer peaks in liver and memory Th cells. Our analysis demonstrates the utility of haplotype association analyses in discovering and characterizing PBC susceptibility loci.

Study EGAS00001002915

Atherosclerosis Risk in Communities Study (ARIC-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. At present, the ARIC sIRB has determined that ARIC data cannot be shared with for-profit entities.Related Studies Other ARIC data available include: Imaging studies (ARIC-Imaging), Genetics and genomics (ARIC, phs000280.v8.p2), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): ARIC (phs002988.v1.p1), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637.v1.p1). Available Data Data available for request include ARIC v1-v8 examination cycles, collated annual follow-up communication data for contact years 2-32, and follow-up for mortality, heart disease, and stroke events through 2019. Also included are data from ancillary studies. Objectives The objectives of ARIC are to: 1) investigate associations of factors, including those not previously measured in cohort studies, with prevalence of atherosclerosis and incidence of CHD, clinical stroke and other cardiovascular diseases; and 2) measure cardiovascular disease occurrence and trends and relate these to community levels of, and changes in, risk factors, medical care and atherosclerosis. Background At the time of project initiation, the NHLBI had long recognized the need for longitudinal studies to identify the biochemical and physiological markers and specific environmental factors which place individuals at high risk for the major atherosclerosis diseases. The development of reliable ultrasound examination of peripheral arteries enhanced the expected benefit of such studies. Community surveillance planning began for ARIC in response to recommendations of the 1978 NHLBI Workshop on the Decline in CHD Mortality and has been extended in its purpose to evaluate the large geographic differences in U.S. mortality. Participants Black and white men and women, age 45-64 at entry; sample size: 15,792. Design ARIC is a large-scale, long-term prospective study that measures associations of established and suspected coronary heart disease risk factors with both atherosclerosis and new CHD events in men and women from four geographically diverse communities. The project has two components: community surveillance of morbidity and mortality; and repeated examinations of a representative cohort of men and women in each community. The community surveillance involves abstracting hospital records and death certificates and investigating out-of-hospital deaths. The representative cohorts include approximately 4,000 persons from each community. Community surveillance data includes detailed hospital record abstraction, ECG tracings, and event adjudication. Data from out-of-hospital events in the community include physician, informant, and coroner questionnaires as well as death certificate data and event adjudication. Community surveillance ended in 2014.Cohort participants were examined four times at three year intervals between 1987 and 1998, and have been continuously contacted annually to update their medical histories. Atherosclerosis was measured by carotid ultrasonography. Risk factors studied include: blood lipids, lipoprotein cholesterols, and apolipoproteins; plasma hemostatic factors; blood chemistries and hematology; sitting, supine and standing blood pressures; anthropometry; fasting blood glucose and insulin levels; ECG findings; cigarette and alcohol use; physical activity levels; dietary aspects; and family history. Clinic visits were restarted in 2011 with ARIC visit 5.

Study phs003738

Raw ONT R10 data: Rapid brain tumor classification from sparse epigenomic data

This dataset contains 207 samples sequenced using rapid-multiplexed barcoded library preparation on Nanopore PromethION R10 flow cells on P2 Solo and P24 systems. One unaligned BAM file per sample is provided.

Dataset EGAD50000000791

COVID-19 scRNA-seq, TCR-seq and BCR-seq

COVID-19 scRNA-seq, TCR-seq and BCR-seq for 291 samples collected from 109 patients. Among 291 samples, 249 of them have two libraries (sequencing runs) for each assay, while 42 have only one library.

Dataset EGAD00001007995

Variants from a subset of genes from WES of adult AML patient samples

Dataset comprises one vcf file containing variants from a list of genes (DNA repair and metabolism associated genes) subset from WES of an adult AML cohort. The cohort contains 145 patient samples. WES was performed using Illumina platform.

Dataset EGAD00001008700

BLUEPRINT: WGBS-seq of multiple myeloma and plasma cells

Whole-genome Bisulfite sequencing of two multiple myeloma samples and one pooled sample of plasma cells.

Dataset EGAD00001000672

whole genome sequencing data of genomic heterogeneity of multiple synchronous lung cancer.

Fastq data of genomics heterogeneity of multiple synchronous lung cancer. Whole-genome sequencing (WGS) were performed in 3 tumour samples, one regional lymph node metastasis sample and peripheral blood sample from the same patient with MSLCs.

Dataset EGAD00001003458

Ovarian cancer/normal cell lines

We performed whole genome sequencing of nine OC patient-derived cell lines and one normal cell line (HOSEpiC) to analyze if the cell lines harbor OC-typical genomic aberrations absent in normal cells and to relate genomic features to drug sensitivities.

Dataset EGAD00001003146

Transposome Bisulfite Sequencing

DNA belonging to 16 tumour/normal samples were treated with bisulfite, then up to 5 different bisulfite PCRs were performed in each one of the samples. Amplicons form the same sample were pooled and submitted to sequencing on a MiSeq platform.

Dataset EGAD00001001028

Medulloblastoma whole and focused exome sequencing (n=13 patients, n=37 samples)

Whole exome sequencing: 24 samples matched tumor-normal and one matched CSF. Focused exome sequencing: 17 samples matched tumor-normal-2 time point CSF.

Dataset EGAD00001006387

Whole_genome_sequencing_of_100_DDD_trios_with_suspected_noncoding_causal_mutations

We would like to whole-genome sequence 100 trios (300 individuals) from the DDD project in which we suspect the proband has a pathogenic noncoding mutation, to 30X coverage. These have been carefully selected to maximise the chances of finding pathogenic noncoding mutations. Specifically, we have selected probands who have no likely causal mutation within the coding region but who have a heterozygous loss-of-function mutation inherited from one parent in a known recessive developmental disorder gene, and whose phenotype is a good match for the typical phenotype caused by recessive variants in that gene. We suspect that these probands may have a heterozygous noncoding mutation on the other allele which reduces expression of the gene so that, together, these two mutations are effectively equivalent to a homozygous loss-of-function mutation. About a quarter of the probands have affected siblings and, if those siblings have been exome sequenced, we have checked that they are identical-by-descent in the region of the gene. We propose to search in the promoter region, intronic and annotated regulatory regions around these genes of interest for rare variants inherited from the other parent (i.e. not the one who transmitted the loss-of-function variant), or de novo variants. If we find such variants, and demonstrate an enrichment of this compound heterozygous LoF noncoding mechanism above that expected by chance, we intend to follow up specific candidates by RNAseq and potentially CRISPR/Cas9 experiments. 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 please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002452

Genetics of Neuropsychiatric and Neurodevelopmental Disorders

Although schizophrenia is a highly heritable disease, relatively little progress had been made in securely identifying the genetic causes of this disorder, and most instances of schizophrenia in the general population remain unexplained. One avenue of explanation for the genetic basis of schizophrenia, however, has been effectively closed by recent research. Genome-wide association studies (GWAS) have now shown that common variation makes at most a modest contribution to the risk of schizophrenia. At the same time that the role of common variation has been circumscribed by GWAS, however, the analysis of copy number variants that are detectable on a genome-wide scale has revealed and replicated a number of very rare variants that associate with schizophrenia. These rare copy number variants that have been implicated in schizophrenia, however, have one striking feature in common: they are all risk factors for other brain related disorders beyond schizophrenia such as mental retardation, autism and epilepsy. These findings argue that genetic risk factors may confer a highly penetrant vulnerability to neuropsychiatric disorder, which is then further modified by interacting genetic or environmental factors to determine the ultimate manifestation. Most schizophrenia collections that are being studied today, however, have been selected precisely for their homogeneity: including only schizophrenia patients with no comorbidities, or schizophrenia patients with relatives who have schizophrenia but no other neuropsychiatric conditions. These selection criteria are inconsistent with what we now know about the bulk of the genetic differences that have been associated with disease. The central hypothesis of this project is that there are rare genetic variants that strongly elevate the risk of various neuropsychiatric diseases, and that these risk factors can be identified most readily in families segregating multiple neuropsychiatric conditions.

Study phs000682

Cell-Free DNA Genomic and Fragmentomic Features for Early Outcome Prediction in Diffuse Large B-Cell Lymphoma

Purpose: Diffuse large B-cell lymphoma (DLBCL) patients need an accurate and early risk stratification strategy as prompt therapy escalation may improve outcome. Patients and methods: We evaluated cell free DNA (cfDNA) genomic and fragmentomic features in 190 patients with large B-cell lymphoma from more than 40 hospitals in the Benelux using Whole Genome Sequencing (WGS). We defined a new metric called ACT score (Aberrations, Contribution of short fragments, Terminal motif analyses) by combining four cfDNA signals and evaluated its performance to predict end-of-treatment (EOT) response and survival. Results: Individual cfDNA features and ACT score were altered per EOT response after one cycle of treatment (T1). The ACT score at T1 outperformed all individual cfDNA features in predicting EOT response (AUC = 0.74). Patients with a positive ACT score had an inferior outcome compared to ACT score negative patients [progression-free survival (PFS): HR 5.0 (95% CI 3.1-8.2), log-rank test, p < 0.0001) and overall survival (OS): HR 6.5 (95% CI 3.5-12.2), log-rank test, p < 0.0001]. The 2-year PFS in ACT score positive and negative patients were 29.8% and 78.1%, respectively. The prognostic value of the ACT score is independent of the International Prognostic Index and interim imaging. Conclusions: ACT score computed from a single plasma sample collected after one cycle of treatment can predict clinical outcome. This low-cost and easy-to-interpret test does not require tissue biopsies or a priori knowledge of mutations and has the potential to aid patient selection in interventional clinical trials and risk-adapted treatment strategies.

Study EGAS50000000412

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