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• RNaseq of mantle cell lymphoma patient samples

  This study presents bulk RNA sequencing data from 78 clinical mantle cell lymphoma (MCL) samples. Following rigorous quality control and batch effect correction to account for sample type and redundancy, 62 samples from 59 patients were included in the final analysis. The transcriptomic profiles capture the molecular diversity across both solid and liquid tumor contexts and support investigations into the phenotypic plasticity and metabolic states of drug-tolerant persister (DTP) cells.

  Study EGAS50000001086

• Whole exome sequencing of Zimbabwean patients with suspected Mendelian disorders

  This study presents whole exome sequencing data from Zimbabwean individuals with suspected Mendelian disorders, including sickle cell disease, Fanconi anemia, haemophilia, and muscular dystrophy. The dataset includes both affected individuals and family members to support inheritance-based analyses. Variant calling was performed using the Illumina DRAGEN pipeline, with downstream variant prioritisation and interpretation conducted using the Zi-Mendelian bioinformatics pipeline. This study supports rare disease genomics and precision medicine efforts in African populations.

  Study EGAS50000001708

• Autozygosity pilot - QMUL

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing British-Pakistani cohort samples will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consists of low coverage whole exome sequencing on these samples.

  Dataset EGAD00001001027

• NIH RECOVER: A Multi-Site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection

  The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in decedents who die more than 60 days after initial onset or after hospital discharge, whether in-hospital or out-of-hospital at time of death, and who meet the working definition of PASC as defined by the recent World Health Organization publication given in Section 5.4. The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of decedents who died between15-60 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003768

• Microbiome

  16S-sequencing: All stool samples were processed according to the standards of the Flemish Gut Flora Project (Falony et al., 2016). All samples were processed together and sequenced in as a single batch (dual index run DI23R22) which included positive controls (PC, identical stool sample), negative controls (PCR-mix) and ‘blanks’ or negative controls of the extraction (no sample). In addition, a Runella strain (RS) was included to check for potential cross-contamination, as this strain is not present in human samples. The V4 region of the 16S rRNA gene was amplified with the primer pair 515F and 806R (GTGYCAGCMGCCGCGGTAA and GGACTACNVGGGTWTCTAAT, resp.), modified to contain a barcode sequence between each primer and the Illumina adaptor sequences to produce dual- barcoded libraries (Tito et al., 2019). Sequencing was performed on the Illumina MiSeq. Sequences were processed using the LotuS (Hildebrand et al., 2014) and DADA2 pipeline (Callahan et al., 2016) using RDP 16 as the reference taxonomy.

  Dataset EGAD50000002027

• Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

  The TARGET Study consists of 200 BAM files, for the 100 patients discussed in the publication. Each patient has a normal control BAM file and a ctDNA BAM file.

  Dataset EGAD00001004796

• WGS of cfDNA in PDAC Breast Cancer and Matched Controls

  This dataset contains WGS data derived from plasma cfDNA. The cohort includes PDAC and breast cancer patients alongside matched controls. These data are intended to support research into ctDNA and genomic fragmentation patterns.

  Dataset EGAD50000002323

• Autism Sequencing Consortium (ASC)

  The ARRA Autism Sequencing Collaboration was created in 2010 bringing together expert large-scale sequencing center (at the Baylor College of Medicine, PI Richard Gibbs and the Board Institute of MIT and Harvard, PI Mark J. Daly) and a collaborative network of research labs focused on the genetics of autism (brought together by the Autism Genome Project and the Autism Consortium). These groups worked together to utilize dramatic new advances in DNA sequencing technology to reveal the genetic architecture of autism through comprehensive examination of the exotic sequence of all genes. The Autism Sequencing Consortium (ASC) was founded by Joseph D. Buxbaum and colleagues as an international group of scientists who share autism spectrum disorder (ASD) samples and genetic data. The PIs are Drs. Joseph D. Buxbaum (Icahn School of Medicine at Mount Sinai), Mark J. Daly (Broad Institute of MIT and Harvard), Bernie Devlin (University of Pittsburgh School of Medicine), Kathryn Roeder (Carnegie Mellon University, Matthew State and Stephan Sanders (University of California, San Francisco). The rationale for the ASC is described in Buxbaum et al. 2012, and this paper should be cited when referencing the data set. All shared data and analysis is hosted at a single site, which enables joint analysis of large-scale data from many groups. The ASC was first supported by a cooperative agreement grant to four lead sites funded by the National Institute of Mental Health (U01MH100233, U01MH100209, U01MH100229, U01MH100239), with additional support from the National Human Genome Research Institute. The NIMH recently renewed their support with a second grant (U01MH111661, U01MH111660, U01MH111658 and U01MH111662) to expand the project from 29,000 genomes to more than 50,000 exomes over the next 5 years. NHGRI provides ongoing sequencing support for the ASD through the Broad Center for Common Disease Genomics (UM1HG008895, Mark Daly, PI).

  Study phs000298

• Studies of L1-mediated Pseudogene Formation in Human HeLa Cells

  Alu elements mobilize from one genomic location to another by a "copy-and-paste" mechanism known as retrotransposition, which requires the human Long INterspersed Element-1 (LINE-1 or L1) ORF2-encoded protein (ORF2p); however, little is known about other cellular factors required for Alu retrotransposition. Isolates of HeLa cells differ in their ability to support Alu retrotransposition. Here, we generated Illumina whole genome sequencing data derived from four HeLa isolates: HeLa-H1, HeLa-CCL2, HeLa-HA, and HeLa-JVM.

  Study phs003397

• RNAseq of MCL cell lines

  This study provides bulk RNA sequencing data from Mino and Jeko-1 mantle cell lymphoma (MCL) cell lines treated with CDK9 inhibitors, including the novel compound YX0798. CDK9 is a key regulator of RNA polymerase II–mediated transcription, and its inhibition disrupts transcriptional programs critical for tumor survival. The dataset captures transcriptomic changes associated with CDK9 inhibition, including downregulation of oncogenic drivers such as MYC and MCL-1. These data support mechanistic studies of transcriptional reprogramming and therapeutic vulnerability in aggressive MCL.

  Study EGAS50000001089

• Cell-free DNA and bone marrow samples from myelodysplastic syndromes

  We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA. Sequencing of BM DNA and cfDNA showed a comparable mutational profile and variant allele frequencies (VAF) strongly correlated between both sample types. Our results support the analysis of cfDNA as a promising strategy for performing molecular characterization, detection of chromosomal aberrations and monitoring of MDS patients.

  Study EGAS00001005992

• Autozygosity pilot - British-Pakistani from Birmingham 2

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing British-Pakistani cohort samples from Birmingham will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consists of low coverage whole exome sequencing on these samples.

  Dataset EGAD00001001026

• Autozygosity pilot - British-Pakistani from Birmingham

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 50-80%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing British-Pakistani cohort samples from Birmingham will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consist of low coverage whole exome sequencing on these samples.

  Dataset EGAD00001001025

• ICGC PRAD-CA WGS fastq

  Raw lane level fastq files from Whole genome sequencing in support of ICGC PRAD-CA Variant calls

  Dataset EGAD00001003909

• ICGC PRAD-CA WGS fastq

  Raw lane level fastq files from Whole genome sequencing in support of ICGC PRAD-CA Variant calls

  Dataset EGAD00001003957

• ICGC PRAD-CA WGS fastq

  Raw lane level fastq files from Whole genome sequencing in support of ICGC PRAD-CA Variant calls

  Dataset EGAD00001003975

• Genomic and Phenotypic Profile of Sickle Cell Disease in Human Population in Cameroon

  Sickle cell disease (SCD) is caused by a biallelic single nucleotide substitution in the beta-globin gene (HBB), resulting in an amino acid substitution, Glu7Val, formerly known as Glu6Val. An estimated 300,000 babies with SCD are born worldwide each year, with nearly 75% of these births being in sub-Saharan Africa. In Africa, at least 30-50% of children with untreated SCD die before the age of 5 years. Therefore, accelerating the path for novel therapies for SCD through genomics research on fetal hemoglobin (HbF) is critical. Variants in the currently known HbF‐modulating genes/loci, i.e., BCL11A, HBS1L-MYB, and XmnI-HBG2, explain only 10-20% of the variation of HbF levels in African individuals with SCD, compared with nearly 50% of the variation in HbF levels among Europeans. Expanding genomic research in populations of African ancestry could uncover the missing heritability of HbF-promoting loci. This study used the Human Heredity and Health (H3Africa) consortium SNP genotyping array developed from whole genome enriched for common variants in sub-Saharan Africans to investigate genomic variations associated with HbF levels in individuals with sickle cell anemia of the HbSS genotype from Cameroon. Two of the previously described loci, BCL11A and HBS1L-MYB were replicated, while a novel locus on chromosome 13 mapping to FLT1 was uncovered. The study therefore opens up a novel avenue for exploring SCD gene therapy.

  Study phs003748

• About

  About What's the EGA? The European Genome-phenome Archive (EGA) is a global network for permanent archiving and sharing of personally identifiable genetic, phenotypic, and clinical data generated for the purposes of biomedical research projects or in the context of research-focused healthcare systems. Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, we aim to advance biomedical research and promote personalised medicine worldwide by enabling discovery of and access to human genomic and health research data. The EGA contains data collected from individuals whose consent agreements authorise data release for specific research use to bona fide researchers. We ensure strict security measures to control access to the data and maintain patient confidentiality. With expertise in data management and technical infrastructure, we promote FAIR data reuse and enable researchers to share their data securely. By leveraging public funding and our strategic partnerships, the EGA provides a free service for permanent data storage, data discovery, and secure data access. In addition, we foster a federated network to provide transnational access to human research data in compliance with legal frameworks. For additional information about the EGA, please contact: Helen Parkinson and Mallory Freeberg EMBL European Bioinformatics Institute Arcadi Navarro, Roderic Guigó, and Jordi Rambla Center for Genomic Regulation History The European Genome-phenome Archive was launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. With the signing of a memorandum of understanding in 2013 and a formal agreement in 2016, the EGA became a joint project of EMBL-EBI and the Centre for Genomic Regulation (CRG). The two institutes work together to support the EGA services, including supporting submissions, website, strategic leadership, and data infrastructure developments. In 2022, the Federated EGA was officially launched with the signature of the first five countries: Finland, Germany, Norway, Spain, and Sweden. With more than 20 additional nodes worldwide preparing to join, the Federated EGA aims to become the largest human omics data sharing initiative towards understanding human health and disease. EGA overview If you're a researcher you may need to deposit, manage, or access genomic data in a secure and regulated way. The European Genome-phenome Archive (EGA) is a platform that facilitates these processes, ensuring that sensitive data is stored and shared in accordance with legal and ethical regulations. Submission process To start a submission, you need to become an EGA submitter. For that, you’ll need to sign a Data Processing Agreement (DPA) with us, that defines the terms and conditions under which your data will be processed and shared within the EGA system. The access to each study is controlled by its Data Access Committee (DAC). The DAC is responsible for managing data access requests and ensuring that the release of data is in accordance with the General Data Protection Regulation (GDPR). Please, note that once your data is released, all public metadata related to your study and dataset(s) will be searchable on the EGA website. However, the files are only accessible under controlled access, which means that a DAC has to agree to a previous data access request. Request process It is possible to submit an access request to data stored at the EGA. The DAC assigned to the study will assess the request and, if approved, grant access to the data. Requesters must provide sufficient justification for your request and comply with the intended data usage in order to get access to it. Each dataset is covered by a Data Access Agreement (DAA) that defines the terms and conditions of use for the specified dataset/s. The DAA is created and provided by the DAC, and must be signed by the individual requesting access to the given dataset/s. Download process Once the request for access is approved, the data and metadata can be downloaded. The EGA offers various download options to fit the needs: it is possible to preview files without downloading them, download specific files of interest, or even download terabytes of data. Overall, the EGA provides a secure and regulated environment for depositing, managing, and accessing human data. Regardless of the role - submitter, DAC member, or requester - the EGA provides assistance for each while ensuring that sensitive data is managed in an ethical and responsible manner. More information on how EGA handles data is available in the EGA dataflow.

  Documentation about/ega

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• HGSC lines: ATACseq and RNAseq, pre- vs post-treatment with HKMTi-1-005

  Formation of a DAC to support the deposition of RNAseq and ATACseq data, from pre- vs post-treatment high-grade serous ovarian carcinoma cell lines. The lines include PEO1, PEO4, PEA2, OVCAR5, OVCAR8, and the treatment includes use of a novel epigenetic drug called HKMTi-1-005.

  Dac EGAC50000000034

• Melanoma transcriptomic data from patients undergoing immunotherapy

  This dataset contains raw RNA sequencing data from melanoma patient tumor samples collected before and during immunotherapy. The data support investigation of treatment-related changes in tumor cell populations. Samples were analyzed as part of a study exploring cellular responses to immune-based therapies.

  Dataset EGAD50000001569

• Neuroblastoma_MP-PCR_MultiplexPCR_TargetedSequencing_BAMs

  This dataset contains raw sequencing data (BAM/BAI files) generated from human neuroblastoma patient samples. The data were produced using targeted high-throughput next-generation sequencing and are intended to support genomic analyses of tumor-associated alterations. All files are provided under controlled access in accordance with EGA data protection requirements.

  Dataset EGAD50000002260

• A tumor focused approach to resolving the etiology of DNA mismatch repair deficient tumors classified as suspected Lynch syndrome

  Routine screening of tumors for DNA mismatch repair (MMR) deficiency (dMMR) in colorectal (CRC), endometrial (EC) and sebaceous skin (SST) tumors leads to a significant proportion of unresolved cases classified as suspected Lynch syndrome (SLS). A tumor-focused testing approach reclassified 86.9% of SLS into Lynch syndrome, sporadic dMMR or MMR-proficient cases. These findings support the incorporation of tumor sequencing and alternate MLH1 methylation assays into clinical diagnostics to reduce the number of SLS patients and provide more appropriate surveillance and screening recommendations.

  Study EGAS50000000021

• Genome Wide Association Study of Subjects with Myalgic Encephalomyelitis (ME)/Chronic Fatigue Syndrome (CFS)

  Myalgic encephalomyelitis, also known as chronic fatigue syndrome or ME/CFS, is a complex and heterogeneous disease that severely impacts the health and quality of life of those afflicted. Several lines of evidence support the possibility that ME/CFS development may involve a heritable component. In this pilot study, 42 cases that meet the diagnostic criteria of ME/CFS and 38 healthy controls were consented into this study. The goal of this study was to identify candidate polymorphisms that can be used for a large multi-center screening study.

  Study phs001015

• Genetic Variants Influence on the Placenta Regulatory Landscape

  This study of the regulatory landscape of the placenta relies on the identification of associations between genetic variant and gene expression changes (eQTLs); genetic variant and DNA methylation changes (mQTLs); and, gene expression change and DNA methylation change (eQTMs). It involves the analysis of DNA sequence variation (n=303), DNA methylation (n=303) and mRNA expression data (n=80) from placentas from healthy women. Such studies are crucial to fully apprehend the complexity of the regulatory landscape and to support further analysis focusing and disease driven phenotype.

  Study phs001717

• WES of Mino-VEN-R Mantle Cell Lymphoma Cells

  This project investigates the genetic basis of therapy resistance in mantle cell lymphoma (MCL) using whole exome sequencing (WES) of the Mino_VEN_R cell line, a model of resistance to pirtobrutinib, a non-covalent BTK inhibitor. Our study suggested that drug-tolerant persister (DTP) cells evade therapy through metabolic and phenotypic reprogramming. By analyzing the exome profile of resistant cells, this study aims to identify mutations associated with treatment escape and cellular plasticity. The findings will contribute to a better understanding of resistance mechanisms and support the development of more effective therapeutic strategies.

  Study EGAS50000001088

• Autozygosity pilot - Born in Bradford (2017-05-11)

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing cohort samples from the Born In Bradford study will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consist of low coverage whole exome sequencing on these samples. This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003329

• Whole Genome sequencing of Angolan and Mozambican individuals

  To support the continued discovery and cataloguing of genomic variation in human populations and to further our understanding of the Bantu Expansion, we sequenced the genomes of 291 individuals from Cabinda, a northern exclave of Angola, and 49 individuals from Maputo, the capital of Mozambique. Utilising the power and flexibility of these whole-genome sequencing datasets, we discover rare variation, fine-scale population structure, and perform analyses using haplotype-based inference tools and our own model-based simulation framework to reconstruct complex dispersals of Bantu speak-ing populations across sub-Saharan Africa.

  Study EGAS00001007458

• Count Me In (CMI): The Metastatic Prostate Cancer (MPC) Project (CMI-MPCproject)

  Count Me In - The Metastatic Prostate Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Prostate Cancer Research The Metastatic Prostate Cancer Project (MPCproject; http://mpcproject.org/) is a research study that empowers men with metastatic and advanced prostate cancer to partner directly with researchers by sharing their samples and clinical information, with the ultimate goal of accelerating scientific discoveries that have clinical impact. The MPCproject enables any man with metastatic or advanced prostate cancer in the US and Canada to participate in cutting-edge genomic and molecular research, regardless of where they live. Metastatic or advanced prostate cancer patients visit the project website and complete an online questionnaire of basic information about themselves and their cancer. Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA, and transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided with updates on the study.

  Study phs001939

• Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

  Next generation sequencing (NGS) of circulating tumour DNA (ctDNA) supports blood-based genomic profiling but is not routinely implemented in the clinic. TARGET is a molecular profiling programme with the primary aim to match patients to early phase clinical trials based on analysis of both somatic mutations and copy number alterations (CNA) across a 641 cancer-associated gene panel in a single ctDNA assay. For the first 100 TARGET patients, ctDNA data showed good concordance with matched tumour and results were turned round within a clinically acceptable timeframe for Molecular Tumour Board (MTB) review. When applying a 2.5% Variant Allele Frequency (VAF) threshold actionable mutations were identified in 41/100 patients, with 11 of these patients going onto a matched therapy. These data support the application of ctDNA in an early phase trial setting where broad genomic profiling of contemporaneous tumour material enhances patient stratification to novel therapies and provides a practical template for bringing blood-based analyses to the clinic.

  Study EGAS00001003407

• Whole exome sequencing (WES) of EBV- primary central nervous system lymphoma (PCNSL)

  This dataset contains whole exome sequencing (WES) of 29 HIV- EBV- primary central nervous system lymphoma (PCNSL) tumors and 5 activated B-cell-like PCNSL (ABC-PCNSL) and activated B-cell-like diffuse large B-cell lymphoma (ABC-DLBCL) cell lines (TK, HKBML, OCI-Ly3, HBL-1, TMD-8). Cases with secondary involvement of the CNS were excluded. DNA was extracted with AllPrep DNA/RNA FFPE kit and libraries were prepared using the Agilent SureSelect Human All Exon v6 + UTR kit. Paired end reads were aligned to GRCh37 using bwa mem v.0.7.17, and reads were sorted and duplicated were marked in the final BAM files. Access to this data is controlled. There are a number of steps that a researcher must take to obtain access to this data, including execution of a Data Access Agreement between the institutions. The process is overseen by the Technology Development Office; please contact our general email address TDOadmin@phsa.ca. Please only click the "request data" button on the EGA website after a Data Access Agreement is fully executed.

  Dataset EGAD50000000451

• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk

  Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.

  Dataset EGAD50000000518

• Singapore Gastric Cancer Consortium GeoMx DSP tissue microarray (SGCC TMA) cohort

  Gastric cancer (GC) remains a significant global health challenge due to its high heterogeneity, with intratumoral heterogeneity (ITH) posing a major obstacle to effective patient outcomes. In this study, utilizing GeoMx Digital Spatial Profiler (DSP) technology, we specifically investigated ITH within GC patients by comparing tumor core regions to tumor edge regions. Our findings indicate that tumor edge regions exhibit more advanced tumor activity, akin to the G2-like progressed state, compared to tumor core regions. The findings confirm the spatial locations of G2 RNA-ITH subregions and support the conclusions drawn from the discovery cohort.

  Study EGAS50000000640

• COVID_19_UK_CIC_Spatial

  Understanding the immune response to SARS-CoV-2 is critical to our ability to control the coronavirus pandemic. Spatial transcriptomics will be performed on COVID-19 post-mortem tissues in collaboration with the UK - Coronavirus Immunology Consortium (UK-CIC). UK-CIC encompasses a concerted effort by the UK's world-leading immunology community to deliver a co-ordinated and agile national research programme to increase our understanding of how the immune system interacts with SARS-CoV-2. UK-CIC is led by Professor Paul Moss (University of Birmingham) and brings together 20 UK immunology centres of excellence, with support from the British Society for Immunology.

  Study EGAS00001005817

• Autozygosity pilot - Born in Bradford (2014-11-20)

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing cohort samples from the Born In Bradford study will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consist of low coverage whole exome sequencing on these samples.Data Access is controlled by the Wellcome Trust Sanger Institute DAC and the Born In Bradford Executive Group. This dataset contains all the data available for this study on 2014-11-20.

  Dataset EGAD00001001079

• Genomic characterisation of MGUS

  The hematological malignancy multiple myeloma (MM), also called Kahler's disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Dataset EGAD00001006363

• Whole-genome shotgun metagenomic sequencing of rectal mucus from patients suspected to have colorectal cancer

  This dataset contains whole-genome shotgun metagenomic sequencing data of 408 rectal mucus samples from patients suspected to have colorectal cancer and healthy controls. Sequencing was performed on the Illumina NovaSeq platform, producing paired-end FASTQ files. These data support microbial community profiling and biomarker discovery analyse

  Dataset EGAD50000001867

• Everything you need to know about Federated EGA Affiliates: Q&A

  Addressing common questions about Federated EGA (FEGA) Affiliates and providing answers. FEGA Affiliates have recently been defined as the third tier within the newly approved “Federated EGA Structure and Organisation” document, alongside Central EGA (CEGA) and the FEGA Nodes. In this blog post, we aim to answer the questions that may arise on this topic. For more general information about FEGA Affiliates, you can refer to this blog post. Let's now start with the questions and answers! What is the difference between a FEGA Affiliate and a FEGA Node? FEGA Nodes A FEGA Node is a national-level service that accepts submissions and provides archiving and access services within a single country's jurisdiction. Nodes provide end-to-end services for submitters in that jurisdiction, including submission support, processing, permissions management, and distribution. FEGA Affiliates A FEGA Affiliate is not a national submission service. Instead, it archives data from its own legal entity and/or selected partner institutions (for example, consortium partners). Affiliates are designed for organisations and consortia that need to keep data stewardship and access decisions within their own governance model, while still enabling discovery through the broader FEGA ecosystem. What do Affiliates commit to? Here is a practical checklist of the core expectations for a FEGA Affiliate. FEGA Affiliate checklist Discovery and metadata Submit non-personal metadata to CEGA to obtain EGA accessions and enable discovery (with metadata validation handled by the CEGA Helpdesk). Operations and resilience Maintain a data storage system and a defined backup/recovery approach. Ensure operational capacity (personnel and infrastructure) to deliver Affiliate services. Maintain systems and practices that support local data security and align with EGA best-practices. Access and user support Provide data distribution or access (e.g in a trusted research environment) to authorised users to datasets hosted at the Affiliate. Provide permissions management for datasets archived by the Affiliate (the CEGA DAC (Data Access Committee) Portal is always at your disposal to use). Provide a minimal helpdesk with sufficient capacity to support relevant DACs and approved users. Membership term Commit to a minimum membership term of four years. Governance and participation (lightweight by design) Affiliates integrate into the FEGA network operationally, but without the committee obligations associated with Nodes. When is becoming an Affiliate the right fit? Consider the Affiliate tier if: You host (or plan to host) controlled-access datasets that must be managed under your organisation’s or consortium’s governance, you want studies to be discoverable through EGA, but need access control and/or distribution to remain local, and you are not aiming to operate a national submission service tier.. What if a FEGA Node already exists in my jurisdiction? We encourage any potential Affiliate to reach out to their national FEGA Node to explore collaboration at the national level. Why? Federated models within a country already exist in FEGA, where a national Node operates like a Central EGA for their country. FEGA Nodes can also represent the interests of any Affiliates within their jurisdiction at the FEGA Committees. FEGA Nodes have experience and can support you on your FEGA journey. Ready to join as a FEGA Affiliate? We’re excited to open this formally defined pathway for organisations and consortia to participate in the federation. If you think the FEGA Affiliate tier fits your needs, start by assessing: Your scope (organisation/consortium-held data rather than public external submissions), Your ability to provide the core services (permissions, distribution/access, helpdesk, monitoring), and Your readiness to submit non-personal metadata to CEGA for accessioning and discovery. To express interest, please contact us here, and we'll help you understand the onboarding steps and how Affiliates integrate into the FEGA network.

  Blog fega-affiliates-q&a

• Thirty cutaneous SCC WES tumour samples with matched normal

  Thirty cutaneous SCC WES tumour samples with matched normal include 20 samples from South et al. JID and 10 new samples. These 30 samples has been used to support the findings in the TGFb Nature Communications paper (DOI: 10.1038/ncomms12493). They are also a part of the ongoing study of cSCC genomic landscape of 40 cSCC samples in total.

  Dataset EGAD00001002253

• The dataset of Southeast Borneo individuals (Banjar and Ngaju ethnic groups) was used as comparative data to determine the Asian parental population of the Malagasy. Our study found strong support for an origin of the Asian ancestry of Malagasy among the Banjar.

  Malagasy genetic diversity results from an exceptional proto-globalisation process that took place over a thousand years ago across the Indian Ocean. Previous efforts to locate the Asian origin of Malagasy have highlighted Borneo broadly as a potential source, but so far no firm source populations have been identified. Here, we have generated genome-wide data from two Southeast Borneo populations, the Banjar and the Ngaju, together with published data compiled from populations across the Indian Ocean region. We find strong support for an origin of the Asian ancestry of Malagasy among the Banjar. This group emerged from the long-standing presence of a Malay Empire trading post in Southeast Borneo, which favoured admixture between the Malay and an autochthonous Borneo group, the Ma’anyan. Reconciling genetic, historical and linguistic data, we show that the Banjar, in Malay-led voyages, were the most probable Asian source among the analysed groups in the founding of the Malagasy gene pool.

  Study EGAS00001001841

• CIDR: The Role of Rare Coding Variation in Prostate Cancer in Men of African Ancestry - RESPOND Project 2

  In RESPOND Project 2, we seek to identify rare genetic factors that are associated with prostate cancer (PCa) risk and aggressiveness in men of African ancestry (AA). We will conduct exome sequencing of 15,000 prostate cancer cases and 5,000 controls from the RESPOND cohort and the African Ancestry Prostate Cancer Consortium (AAPC) with cases selected based on risk categories: high-risk (stage T3/T4 or Gleason 8+ or PSA>20 ng/ml), intermediate-risk (stage T2b/T2c or Gleason 7 or PSA 10-20 ng/ml) and low-risk disease (stage T1/T2a and Gleason ≤ 6 and PSA<10 ng/ml). We expect the findings from this Project to significantly advance knowledge of susceptibility to aggressive PCa and racial/ethnic disparities in PCa risk, and to guide the development of future preventive, early detection and prognostic measures for AA men. The first phase of the study will include exome sequence data for approximately 7,500 cases and 5,000 controls from AAPC. The second phase of the study will include exome data for 5,000 cases from RESPOND and AAPC.ACKNOWLEDGMENTS and CONTRIBUTING SITES Multiethnic Cohort (MEC): The MEC and the genotyping in this study were supported by National Institutes of Health (NIH) grants CA63464, CA54281, CA1326792, CA148085, and HG004726. Cancer incidence data for the MEC and Los Angeles Study of Aggressive Prostate Cancer (LAAPC) studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with federal funds from the National Cancer Institute (NCI)/NIH/Department of Health and Human Services (DHHS) under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the Centers for Disease Control and Prevention (CDC). Ghana Prostate Study (GPS): The Ghana Prostate Study was funded by the Intramural Program of the NCI/NIH/DHHS under Contract No. HHSN261200800001E. Men of African Descent and Carcinoma of the Prostate (MADCaP): We thank all MADCaP study participants. This work is a product of the MADCaP network. This work was supported by NCI/NIH grant U01CA184374 to Timothy Rebbeck and National Institute of General Medical Sciences (NIGMS) MIRA grant R35GM133727 to Joseph Lachance. Additional funding includes a seed grant from the Integrated Cancer Research Center at Georgia Institute of Technology. UGANDA: The UGANDA study was supported by NIH grant R01CA165862. Southern Community Cohort (SCCS) is funded by NIH grant CA092447. SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt Ingram Cancer Center (CA68485). Data on SCCS cancer cases were provided by Alabama Statewide Cancer Registry, Kentucky Cancer Registry, Office of Cancer Surveillance at Tennessee Department of Health, Florida Cancer Data System, Central Cancer Registry at North Carolina Division of Public Health, Georgia Comprehensive Cancer Registry, Louisiana Tumor Registry, Mississippi Cancer Registry, South Carolina Central Cancer Registry, Virginia Cancer Registry at Virginia Department of Health, and Cancer Registry at Arkansas Department of Health. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries (NPCR)/Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the NPCR/CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. Karuprostate: The Karuprostate study was supported by the French National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la Prostate. Séverine Ferdinand, Marc Romana. The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. We would also like to acknowledge the UNC BioSpecimen Facility and the LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). Gene-Environment Interaction in Prostate Study (GECAP) was supported by NIH grant ES011126. King County Prostate Cancer Study (KCPCS) was supported by NIH grants CA056678, CA082664, and CA092579, with additional support from the Fred Hutchinson Cancer Research Center. We thank the participants in these studies, and Ms. Suzanne Kolb for help with study management. The Los Angeles Study of Aggressive Prostate Cancer (LAAPC) was funded by grant 99-00524V-10258 from the Cancer Research Fund, under Interagency Agreement #97-12013 (University of California contract #98-00924V) with the Department of Health Services Cancer Research Program. Cancer incidence data for the MEC and LAAPC studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with Federal funds from the NCI/NIH/DHHS under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the CDC. Prostate Cancer Studies at MD Anderson (MDA) was supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388.

  Study phs002637

• NIH RECOVER-Pediatric: Understanding the Long-Term Impact of COVID on Children and Families

  The NIH Researching COVID to Enhance Recovery (RECOVER) initiative comprises a set of three combined retrospective and prospective, longitudinal and observational meta-cohort studies with nested case-control studies designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection (PASC or Post-COVID syndrome) in a diverse study population representative of the general COVID-19 population in the US. Enrolled patients, with and without known SARS-CoV-2 infection, will be observed for clinical signs and symptoms of PASC and will be assessed for risk and resiliency factors and potential mediating factors associated with the severity and progression of PASC. The objective of the RECOVER initiative is to enhance knowledge of recovery from SARS-CoV-2 infections in order to support development of novel diagnostic and therapeutic interventions. Overarching scientific objectives are as follows:Characterize the incidence and prevalence of sequelae of SARS-CoV-2 infection.Characterize the spectrum of clinical symptoms, subclinical organ dysfunction, natural history, and distinct phenotypes identified as sequelae of SARS-CoV-2 infection. Define the biological mechanisms underlying pathogenesis of the sequelae of SARS-CoV-2 infection. The RECOVER observational studies comprise three cohorts across the lifespan (adult, pediatric, and tissue pathology (autopsy)). The data collection and data analysis plans for each cohort have been harmonized to use common data elements where feasible. Brief descriptions of each cohort are provided in the following paragraphs: 1) NIH RECOVER: A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults (see phs003463)The RECOVER adult cohort study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals who will enter the cohort with and without SARS-CoV-2 infection and at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection, and with or without PASC symptoms, will be followed to identify risk factors and occurrence of PASC. This study will be conducted in the United States and subjects will be recruited through inpatient, outpatient, and community-based settings. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptom screen will be reported by subjects or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical examinations and radiologic examinations will be performed at local study sites with cross-site standardization. 2) A Multi-Center Observational Study: The RECOVER Post Acute Sequelae of SARS-CoV-2 (PASC) Pediatric Cohort Study (this study)The RECOVER pediatric study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals ages newborn-25 years who will enter the cohort with and without SARS-CoV-2 infection at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study recruit participants inpatient, outpatient, and community-based settings in the United States. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptoms will be reported by participants or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical and radiologic examinations will be performed at local study sites with cross-site standardization. 3) NIH RECOVER: A Multi-site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in (i) non-hospitalized patients who die 30 days or later from symptom onset of COVID-19, and (ii) hospitalized patients who die 30 days or later after discharge from a hospitalization for COVID-19. The study will include decedents who had previously fully recovered from SARS-CoV-2 infection (i.e., >30 days from onset in non-hospitalized, or >30 days from discharge in hospitalized patients), and decedents who meet clinical criteria of PASC as defined by the recent World Health Organization publication (see Section 5.4 below). The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of patients who died 15-30 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003461

• NIH RECOVER: A Multi-Site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults

  The NIH Researching COVID to Enhance Recovery (RECOVER) initiative comprises a set of three combined retrospective and prospective, longitudinal, observational meta-cohort studies with nested case-control studies designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection (PASC or Post-COVID syndrome) in a diverse study population representative of the general COVID-19 population in the US. Enrolled patients with and without known SARS-CoV-2 infection will be observed for clinical signs and symptoms of PASC and will be assessed for risk and resiliency factors and potential mediating factors associated with the severity and progression of PASC. The objective of the RECOVER initiative is to enhance knowledge of recovery from SARS-CoV-2 infections in order to support development of novel diagnostic and therapeutic interventions. Overarching scientific objectives are as follows: Characterize the incidence and prevalence of sequelae of SARS-CoV-2 infection. Characterize the spectrum of clinical symptoms, subclinical organ dysfunction, natural history, and distinct phenotypes identified as sequelae of SARS-CoV-2 infection.Define the biological mechanisms underlying pathogenesis of the sequelae of SARS-CoV-2 infection. The RECOVER observational studies comprise three cohorts across the lifespan (adult, pediatric, and tissue pathology (autopsy)). The data collection and data analysis plans for each cohort have been harmonized to use common data elements where feasible. Brief descriptions of each cohort are provided in the following paragraphs:1) NIH RECOVER: A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults (this study)The RECOVER adult cohort study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals who will enter the cohort with and without SARS-CoV-2 infection and at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study will be conducted in the United States and subjects will be recruited through inpatient, outpatient, and community-based settings. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptom screen will be reported by subjects or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical examinations and radiologic examinations will be performed at local study sites with cross-site standardization. A summary of information available by request in the RECOVER Adult Cohort (this study) can be reviewed via the "Adult Cohort Dataset Release Notes" and the "REDCap Codebook for the Adult Cohort" documents.2) The RECOVER Post Acute Sequelae of SARS-CoV-2 (PASC) Pediatric Cohort Study: A Multi-Center Observational Study (data not yet released)The RECOVER pediatric study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals ages newborn-25 years who will enter the cohort with and without SARS-CoV-2 infection at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study recruit participants inpatient, outpatient, and community-based settings in the United States. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptoms will be reported by participants or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical and radiologic examinations will be performed at local study sites with cross-site standardization.3) NIH RECOVER: A Multi-site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection (data not yet released)The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in (i) non-hospitalized patients who die 30 days or later from symptom onset of COVID-19, and (ii) hospitalized patients who die 30 days or later after discharge from a hospitalization for COVID-19. The study will include decedents who had previously fully recovered from SARS-CoV-2 infection (i.e., >30 days from onset in non-hospitalized, or >30 days from discharge in hospitalized patients), and decedents who meet clinical criteria of PASC as defined by the recent World Health Organization publication (see Section 5.4 below). The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of patients who died 15-30 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003463

• GEnetics of Nephropathy - an International Effort (GENIE) GWAS of Diabetic Nephropathy in the UK GoKinD and All-Ireland Cohorts

  Diabetic kidney disease, or diabetic nephropathy (DN), is one of the leading causes of end-stage renal disease in the United States and worldwide. DN is a common complication of long-standing type 1 and type 2 diabetes. The clinical course is characterized by development of proteinuria and gradual loss of kidney function. Although existing treatments that decrease proteinuria have been shown to moderately abate progression of diabetic kidney disease, many affected patients, who do not die from cardiovascular disease, go on to develop terminal renal failure, necessitating costly renal replacement therapies, such as dialysis and renal transplantation. Type 1 diabetes (T1D) can have its onset in childhood and affected individuals often develop end-stage renal disease in early adulthood, leading to further loss of quality of life. The genetic basis of the disease is not well understood. The GENIE (GEnetics of Nephropathy an International Effort) consortium was initiated to perform the most comprehensive and well powered DN susceptibility genome wide association study (GWAS) analysis to date, using the largest collection of type 1 diabetics with and without kidney disease across four study cohorts. The UK-ROI samples were genotyped as part of this project. UK-ROI Sample Description The UK-ROI collection consists of samples derived from the Republic of Ireland (Dr. Catherine Godson, PI, at University College, Dublin, Ireland) and the United Kingdom (Warren 3 and Genetics of Kidneys in Diabetes UK, UK GoKinD, Dr. Alexander P. Maxwell, PI, at Queen's University of Belfast, UK). All study subjects met the inclusion criteria: white individuals with T1D, diagnosed before 31 years of age, whose parents and grandparents were born in the British Isles.

  Study phs000389

• Clinical evaluation of long read sequencing-based episignature detection in developmental disorders

  Some developmental disorders (DD) are marked by specific genome-wide methylation changes, known as episignatures, which can support diagnosis and reveal underlying mechanisms. Current methods rely on indirect methylation profiling. Here, we assessed whether long-read whole genome sequencing with nanopore technology could directly detect both episignatures and genetic variants. We sequenced forty controls and twenty DD patients, using clustering and dimensional reduction to compare methylome patterns with microarray-based signatures. Our classifiers accurately identified episignatures in 17 of 19 patients with pathogenic variants, matching microarray results. This study shows nanopore sequencing enables comprehensive, haplotype-aware genomic and epigenomic analysis for DD diagnostics.

  Study EGAS50000000719

• Human Epilepsy Genetics: Mosaic Mutations in Focal Epilepsy

  This study investigates the role of somatic mosaic mutations in human focal epilepsies, including focal cortical dysplasia (FCD) and mesial temporal lobe epilepsy (mTLE). It leverages genomic and single-cell transcriptomic data from surgically resected brain tissue to identify pathogenic variants and characterize their effects on specific cell types and molecular pathways. The study employs methods such as deep whole-exome and targeted sequencing, single-nucleus RNA sequencing (snRNA-seq), and integrated genotype-transcriptome profiling (e.g., GO-TEN) to define the cellular architecture and functional consequences of mosaic mutations. Data generated under this project aim to elucidate mechanisms of epileptogenesis and support discovery of potential therapeutic targets.

  Study phs004124

• How are we funded?

  How are we funded? The EGA is provided infrastructure, administrative support, advisory input, and other relevant and necessary aspects by: CRG The EGA at the CRG is funded and supported by “La Caixa Foundation”, The Generalitat de Catalunya (Catalan Government), the Spanish Ministerio de Asuntos Económicos y Transformación Digital (Spanish Government) and the Instituto de Salud Carlos III. The Generalitat de Catalunya contributes with funding to the CRG and to the Barcelona Supercomputing Centre (BSC). The Barcelona Supercomputing Center is decisively contributing to EGA by providing the required compute, storage and networking resources, as well as key personnel for shared operations of EGA infrastructure. EMBL-EBI As part of the European Molecular Biology Laboratory (EMBL), the EGA at EMBL’s European Bioinformatics Institute receives funding from the governments of EMBL’s member states. The UK government, via UK Research and Innovation, also continues to support EMBL-EBI technical infrastructure, with EMBL supporting operational costs. A major source of funding for the EGA both at CRG and EMBL-EBI are competitive projects.The EGA resource continues to be funded through strategic engagement in collaborative partnerships and projects. Please see our projects page for more information. Other funders include the European Commission, the US National Institutes of Health, the Wellcome Trust, UK Research Councils, and our Industry Programme partners. Last updated on October, 2024.

  Documentation about/projects-and-funders/funders

• Molecular response of AML blasts to Aza-treatment.

  Azacytidine (Aza) treatment is effective in some patients with acute myeloid leukemia (AML). Clinical observations suggest that DNMT3A-mutant patients represent a subgroup of AML patients that responds particularly well to Aza-treatment. Data coming from a mouse model support this finding and we have already generated molecular data suggesting a molecular pathway involved in Aza-response in DNMT3A-mutant AML patients. We now aim to validate these findings in primary AML-blasts. To this end, we have FACS-sorted blasts from patients with AML prior to and under Aza-treatment and plan to correlate pre-treatment as well as on-treatment methylomes to clinical Aza-response.

  Study EGAS00001004825

• Methylation-based classification of human mesenchymal chondrosarcoma

  We applied methylome and copy number profiling to a set of 45 well characterized MCS cases to evaluate their potential diagnostic value. Notably, the findings were reproducible also when analysing the round cell and cartilaginous component separately. Furthermore, four outliers were identified by methylome profiling for which the diagnosis had to be revised. Methylome profiling represents a sensitive, specific and reliable tool to support the diagnosis of MCS, particularly if only the round cell component is obtained in a biopsy and the diagnosis is not suspected. It can furthermore aid in confirming the diagnosis in case RNA sequencing for the HEY1::NCOA2 fusion transcript is not available.

  Study EGAS00001007042

• 33 patients with Monoclonal Gammopathy of Undetermined Significance (MGUS) had whole exome sequencing performed. Cells were sorted by FACSAria using CD138, CD19 and CD56 to obtain a pure abnormal plasma cell population. Generated somatic variants were compared to a previous study of 463 multiple myeloma patients.

  Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant precursor of multiple myeloma (MM) with a 1% risk of progression per year. Although targeted analyses have shown the presence of specific genetic abnormalities such as IGH translocations, RB1 deletion, 1q gain, hyperdiploidy or RAS genes mutations, little is known about molecular mechanism of malignant transformation. We have performed whole exome sequencing together with SNP array analysis in 33 flow-cytometry separated abnormal PC samples of MGUS patients to describe somatic gene mutations and chromosome changes at the genome-wide level. Non-synonymous mutations (NS-SNVs) and copy number alterations (CNAs) were present in 97.0% and in 63.6% of cases, respectively. Importantly, the number of somatic mutations was significantly lower in MGUS compared to MM (p<10-4) and we have identified 6 myeloma significantly mutated genes which are KRAS, NRAS, DIS3, HIST1H1E, EGR1 and LTB in the MGUS dataset. We also found a positive correlation with increasing chromosome changes and somatic mutations. IGH translocations were present in 27.3% of cases comprising t(4;14), t(11;14), t(14;16) or t(14;20) and were in a similar frequency to MM, which corresponded with primary lesion hypothesis. Data from this study showed MGUS is a genetically comprehensive disease, however overall genetic instability is significantly lower compared to MM.

  Study EGAS00001001658

• 10x Visium Spatial Transcriptomics of 61 Human Hepatocellular Carcinoma Samples

  This dataset contains spatial transcriptomics sequencing data from 61 hepatocellular carcinoma (HCC) tissue samples profiled using the 10x Genomics Visium platform. The cohort includes 38 resected tumors and 23 tumors from patients treated with atezolizumab plus bevacizumab. Sequencing data are provided as paired-end FASTQ files. These data support the analysis of intra-tumoral heterogeneity and its association with clinical outcomes.

  Dataset EGAD50000002122

• WGS Fastq files from the CPC-Gene project in support of PRAD-CA, DCC Release 26

  This dataset contains fastq files with Whole genome sequencing data for the CPC-Gene Project. Data from each sample was generated using multiple whole genome libraries and sequenced across multiple runs

  Dataset EGAD00001003761

• WGS Fastq files from the CPC-Gene project in support of PRAD-CA, DCC Release 26

  PRAD-CA, DCC Release 26 : This dataset contains fastq files with Whole genome sequencing data for the CPC-Gene Project. Data from each sample was generated using multiple whole genome libraries and sequenced across multiple runs

  Dataset EGAD00001003706

• Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS)

  Advances in antiretroviral therapies (ART) and patient management have improved survival of people living with HIV (PLWH). However, with exposure to ART and associated side effects and toxicities as well as to the virus itself, PLWH are at an increased risk of several chronic diseases. The Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS) research network integrates longitudinal clinical data and treatment management of PLWH and provides research infrastructure to support HIV-associated clinical, social, and behavioral outcomes and comparative effectiveness research using data collected from 8 Centers for AIDS Research clinical sites across United States. For detailed study description, see Kitahata et al. (2008, PMID:18263650).

  Study phs001788

• The Genomics of Pilocytic Astrocytoma Formation in Neurofibromatosis Type 1

  Neurofibromatosis type 1 (NF1) inherited cancer predisposition syndrome is one of the most common autosomal dominant tumor predisposition syndromes in which affected individuals develop brain tumors. These low-grade glial neoplasms (pilocytic astrocytomas) typically arise in children younger than 7 years of age and are hypothesized to result from a combination of germline and acquired somatic NF1 tumor suppressor gene mutations. In this study, whole genome sequence analysis was performed on three NF1-associated pilocytic astrocytoma tumors (NF1-PA) and matched normal blood samples to establish the genomic landscape of NF1-PA. These data support the existence of multiple distinct mechanisms (mutation, LOH, and methylation) underlying somatic NF1 inactivation in NF1-PA tumors.

  Study phs000563

• Sweden-Schizophrenia Population-Based Case-Control Exome Sequencing

  Current findings of the genetic risk of schizophrenia and bipolar disorder emerging from genome wide association studies (GWAS) support a highly polygenic model displaying the full spectrum of causal alleles that includes the extremes of rare, penetrant alleles as well as common alleles of small effect. Lower frequency polymorphism, rare variants and private mutations have eluded measurement by GWAS studies and thus association with disease. In order to create a comprehensive catalogue of low frequency or rare coding variation in individuals with psychiatric disease and to build a foundation for future genetic studies of schizophrenia and bipolar disorder, we have obtained whole exome DNA sequence from a population-based schizophrenia and bipolar disorder Swedish case-control cohort.

  Study phs000473

• Resilience and Susceptibility Patterns in the Viral Immune Response Using RNA-Seq (ReSP VIRUS Study)

  This is a cross sectional study to investigate the relationship between nasal mucosa gene expression and clinical outcomes in infants with critical Respiratory Syncytial Virus (RSV) infection. We collected nasal mucosa samples from infants admitted to the pediatric intensive care unit with polymerase chain reaction confirmed RSV bronchiolitis. Samples were obtained by mucosal scrape biopsy of the inferior turbinate using a sterile plastic curette and bulk RNA-sequencing of mRNA was performed. Clinical data was extracted from the electronic health record including: demographics, medical history, duration of symptoms, time from admission to sample collection, hospital and intensive care unit length of stay, and type and duration of respiratory support.

  Study phs003053

• Tumor Profiler Melanoma Study

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. Technologies used are digital pathology, targeted NGS, single-cell RNA, single-cell DNA, bulk RNA, bulk proteotyping, single-cell CyTOF, imaging mass cytometry, pharmacoscopy, 4i Drug Response Profiling, and cell-free DNA. These technologies were applied to 240 tumor samples collected over 3 years across three cancer indications: metastatic melanoma, metastatic epithelial ovarian cancer, and acute myeloid leukemia (AML). Here, we publish the scRNA, scDNA, and bkRNA data of the melanoma cohort.

  Study EGAS50000000599

• Tumor Profiler Ovarian Study

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. Technologies used are digital pathology, targeted NGS, single-cell RNA, single-cell DNA, bulk RNA, bulk proteotyping, single-cell CyTOF, imaging mass cytometry, pharmacoscopy, 4i Drug Response Profiling, and cell-free DNA. These technologies were applied to 240 tumor samples collected over 3 years across three cancer indications: metastatic melanoma, metastatic epithelial ovarian cancer, and acute myeloid leukemia (AML). Here, we publish the scRNA and scDNA data of the ovarian cancer cohort.

  Study EGAS50000000885

• CINECA synthetic data.Please note: This study contains synthetic data (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results.

  Please note: This study contains synthetic data (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk

  Study EGAS00001002472

• Extracorporeal Life Support Survival in a Pediatric Hematopoietic Cellular Transplant Recipient with Presumed Graft Versus Host Disease-Related Fulminant Myocarditis

  We report the case of a 15-year-old female with hypodiploid pre-B acute lymphoblastic leukemia status post allogeneic hematopoietic stem cell transplantation (HCT) from a matched unrelated male donor who presented on transplant day +75 with cardiac arrest due to ventricular fibrillation associated with fulminant myocarditis. Using conventional diagnostics, an exhaustive search for microbial pathogens in the heart biopsy as well as nasopharynx, blood, urine, and endotracheal aspirate was performed but did not uncover a candidate pathogen. The family consented to a research study for the use of unbiased next-generation genomic sequencing for pathogen identification in the myocardial biopsy. DNA sequencing was performed on 1.5 x 108 sequencing pairs and no microbial pathogens were identified. Interestingly, a significant component of Y-chromosomal human DNA was identified, suggesting infiltration of at least 10 donor leukocytes per host cell. This finding is grossly consistent with the lymphocyte:myocyte ratio in the biopsy according to visual inspection at 40x magnification. This case merits discussion due to (1) her survival after 17 days of veno-arterial extracorporeal life support (ECLS) and (2) the possibility of cardiotropic graft versus host disease (GVHD).

  Study phs001336

• Aberrant Activation of Wound Healing Programs within the Metastatic Niche Facilitates Lung Colonization by Osteosarcoma Cells

  Lung metastasis is responsible for nearly all deaths caused by osteosarcoma, the most common pediatric bone tumor. How malignant bone cells coerce the lung microenvironment to support metastatic growth is unclear. This study delineates how osteosarcoma cells educate the lung microenvironment during metastatic progression.Using single-cell transcriptomics (scRNA-seq), we characterized genome– and tissue-wide molecular changes induced within lung tissues by disseminated osteosarcoma cells in both immunocompetent murine models of metastasis and patient samples. We confirmed transcriptomic findings at the protein level and determined spatial relationships with multi-parameter immunofluorescence. We evaluated the ability of nintedanib to impair metastatic colonization and prevent osteosarcoma-induced education of the lung microenvironment in both immunocompetent murine osteosarcoma and immunodeficient human xenograft models.Osteosarcoma cells induced acute alveolar epithelial injury upon lung dissemination. scRNA-seq demonstrated that the surrounding lung stroma adopts a chronic, non-resolving wound-healing phenotype similar to that seen in other models of lung injury. Accordingly, metastasis-associated lung demonstrated marked fibrosis, likely due to the accumulation of pathogenic, pro-fibrotic, partially-differentiated epithelial intermediates. Inhibition of fibrotic pathways with nintedanib prevented metastatic progression in multiple murine and human xenograft models. Our work demonstrates that osteosarcoma cells co-opt fibrosis to promote metastatic outgrowth. When harmonized with data from adult epithelial cancers, our results support a generalized model wherein aberrant mesenchymal-epithelial interactions are critical for promoting lung metastasis. Adult epithelial carcinomas induce fibrotic pathways in normal lung fibroblasts, whereas osteosarcoma, a pediatric mesenchymal tumor, exhibits fibrotic reprogramming in response to the aberrant wound-healing behaviors of an otherwise normal lung epithelium, which are induced by tumor cell interactions.

  Study phs003569

• Melanoma post mortem analysis

  Despite multiple large-scale sequencing studies offering substantial insight into the genomic landscape of cutaneous melanoma, the molecular events surrounding disease progression and the resulting molecular heterogeneity between metastases have not been fully elucidated. We have been applying whole genome and transcriptome sequencing across metastases collected during post mortem. Herein we show the findings for the first such patient. This is a targeted pulldown validation in support of the whole-genome sequencing analysis of the metastatic tumours and targeted pulldown of the primary tumour.

  Dataset EGAD00001005073

• Ither NB in Organoids WGS dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids WGS dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010282

• 33 patients with Monoclonal Gammopathy of Undetermined Significance (MGUS)

  Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant precursor of multiple myeloma (MM) with a 1% risk of progression per year. Although targeted analyses have shown the presence of specific genetic abnormalities such as IGH translocations, RB1 deletion, 1q gain, hyperdiploidy or RAS genes mutations, little is known about molecular mechanism of malignant transformation. We have performed whole exome sequencing together with SNP array analysis in 33 flow-cytometry separated abnormal PC samples of MGUS patients to describe somatic gene mutations and chromosome changes at the genome-wide level. Non-synonymous mutations (NS-SNVs) and copy number alterations (CNAs) were present in 97.0% and in 63.6% of cases, respectively. Importantly, the number of somatic mutations was significantly lower in MGUS compared to MM (p<10-4) and we have identified 6 myeloma significantly mutated genes which are KRAS, NRAS, DIS3, HIST1H1E, EGR1 and LTB in the MGUS dataset. We also found a positive correlation with increasing chromosome changes and somatic mutations. IGH translocations were present in 27.3% of cases comprising t(4;14), t(11;14), t(14;16) or t(14;20) and were in a similar frequency to MM, which corresponded with primary lesion hypothesis. Data from this study showed MGUS is a genetically comprehensive disease, however overall genetic instability is significantly lower compared to MM.

  Dataset EGAD00001001901

• Therapeutic Targeting of ATR Yields Durable Regressions in High Replication Stress Tumors

  Patients with relapsed or recurrent small cell lung cancer or extra-pulmonary small cell cancers were enrolled on an investigator-initiated, single-arm, phase 2 trial (NCT02487095) combining an ATR inhibitor M6620 (VX-970, berzosertib) administered at 210 mg/m2 intravenously over 60 minutes on day 2 and day 5, and topotecan 1.25 mg/m2 intravenously over 30 minutes every 23 hours on days 1 through 5, with a support of pegfilgrastim 6mg subcutaneously on day 6 in 21-day cycles. Tumor samples were collected either just before starting the treatment or before starting treatment prior to be enrolled in the trial. Whole exome and RNA were sequenced to evaluate genomic and transcriptomic characteristics associated with the response to the combination treatment.

  Study phs002327

• Germline variants in UHRF1 are associated with multi-locus imprinting disturbance in humans and mice

  Genomic imprinting provides is an epigenetic process crucial for normal development and is disrupted in congenital imprinting disorders(CIDs). There is great interest in the clinical consequences and aetiology of multilocus imprinting disturbance(MLID) which occurs in some individuals with CID, though the cause of MLID is unknown in most cases. We investigated a kindred with a CID and MLID and identified a rare genetic variant in the UHRF1 gene which has a critical role in the establishment and maintenance of DNA methylation. We generated a mouse model and found that the equivalent Uhrf1 variant was associated with prenatal lethality and disruption of normal imprinting mechanisms. These findings support UHRF1 as a novel candidate gene for CIDs with MLID.

  Study EGAS50000001179

• Assessing the suitability of formalin-fixed paraffin-embedded (FFPE) tissue for genome-wide association studies (GWAS)

  This study evaluates the feasibility of conducting genome-wide association studies (GWAS) using DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue. Genotyping results from paired FFPE and blood samples were compared using both microarray technology and low-coverage whole-genome sequencing (lcWGS). The analysis demonstrated high concordance between FFPE- and blood-derived genotypes. Although both platforms performed well, microarrays achieved significantly higher recall and precision and currently offer greater cost-effectiveness and computational efficiency. These findings support the suitability of FFPE-derived DNA for GWAS, with microarrays representing the preferred approach at present. However, the broader variant detection enabled by lcWGS may represent an additional advantage to be explored in future studies, particularly in diverse populations.

  Study EGAS00001008103

• Enzymatic methylation sequencing of rectal mucus from patients suspected to have colorectal cancer

  This dataset contains comprises enzymatic methylation sequencing (EM-Seq) data generated from 208 rectal mucus samples from patients suspected to have colorectal cancer and healthy controls. Targeted CpG sites were enriched using a panel of genes implicated in colorectal cancer, and libraries were prepared with NEBNext EM-Seq prior to Illumina sequencing. Sequencing was performed on the Illumina NovaSeq6000 platform, producing paired-end FASTQ files. These data support analyses of DNA methylation patterns in CRC detection and progression

  Dataset EGAD50000001871

• Error-corrected targeted sequencing of rectal mucus from patients suspected to have colorectal cancer

  This dataset contains error-corrected next-generation sequencing (ecNGS) data generated from 161 rectal mucus samples. These samples belong to colorectal cancer, adenoma, and control participants. Genomic DNA was extracted and processed using a hybrid-capture panel targeting 50 colorectal cancer–associated genes, incorporating unique molecular identifiers (UMIs) for duplex consensus error correction. Libraries were sequenced on an Illumina NovaSeq 6000 (paired-end 150 bp) producing paired-end FASTQ files. These data support analyses of DNA mutations in CRC detection and progression.

  Dataset EGAD50000002032

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015718

• Whole-genome sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumoroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015707

• Single-cell RNA-sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumouroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015708

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015709

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015714

• Ither NB in Organoids WXS dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids WXS dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010281

• Aspirin and Inflammation: Mutations, Genes, Pathways and Prevention in Barrett's Esophagus

  Background: Use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been shown to protect against tetraploidy, aneuploidy, and chromosomal alterations in the metaplastic condition Barrett's esophagus (BE) and to lower the incidence and mortality of esophageal adenocarcinoma (EA). The esophagus is exposed to both intrinsic and extrinsic mutagens resulting from gastric reflux, chronic inflammation and exposure to environmental carcinogens such as those found in cigarettes. Here we test the hypothesis that NSAID use inhibits accumulation of point mutations/indels during somatic genomic evolution in BE. Methods: Whole exome sequences were generated from 82 purified epithelial biopsies and paired blood samples from a cross-sectional study of 41 NSAID users and 41 nonusers matched by sex, age, smoking, and continuous time using or not using NSAIDs. Results: NSAID use reduced overall frequency of point mutations across the spectrum of mutation types, lowered the frequency of mutations even when adjusted for both TP53 mutation and smoking status, and decreased the prevalence of clones with high variant allele frequency. Never smokers who consistently used NSAIDs had fewer point mutations in signature 17, which is commonly found in EA. NSAID users had on average a 50% reduction in functional gene mutations in nine cancer-associated pathways and also had less diversity in pathway mutational burden compared to nonusers. Conclusions: These results indicate NSAID use functions to limit overall mutations on which selection can act and supports a model in which specific mutant cell populations survive or expand better in the absence of NSAIDs. Galipeau PC, et al. Genome Med. 2018 Feb 27;10(1):17. PMID: 29486792.

  Study phs001654

• Circulating cell-free DNA analysis in Small Cell Lung Cancer

  Small cell lung cancer (SCLC) accounts for ~250,000 deaths worldwide each year. Acquisition of adequate tumour biopsies is challenging and liquid biopsies present the best option for patient stratification and response monitoring. We present genome-wide and targeted plasma DNA sequencing data that identifies tumour related changes in 91% of limited (LS-SCLC) and 100% of extensive stage (ES-SCLC) patients. Parallel analysis of circulating tumour cells (CTCs, by CellSearch) based on ≥ 1 CTC/7.5ml blood increased tumour detection frequencies to 98% patients (95% for LS-SCLC) where CTC count and plasma DNA readouts correlated with disease stage and overall survival (OS). Targeted plasma DNA sequencing identified potential therapeutic targets in >50% of patients. This approach will support trials of targeted therapies where improved patients outcomes are urgently required.

  Study EGAS00001003110

• Upper respiratory microbiome of COVID-19 patients

  Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 microbiome studies by analyzing the upper respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We found that time in the intensive care unit and the type of oxygen support explained the most variation within the upper respiratory tract microbiome, dwarfing (non-significant) effects from viral load, disease severity, and immune status. Specifically, mechanical ventilation was linked to altered community structure, lower species- and higher strain-level diversity, and significant shifts in oral taxa previously associated with COVID-19.

  Study EGAS00001004951

• Genome-wide associations of human gut microbiota variation and implications for causal inference analyses

  Here we use appropriate taxon-specific models along with support from independent cohorts to show association between human host genotype and gut microbiome variation. Using fecal derived 16S rRNA gene sequences and host genotype data from the Flemish Gut Flora Project (FGFP) we identify genetic associations involving multiple microbial traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease, however in the absence of clear microbiome driven effects, caution is needed in interpretation. This work marks a growing catalog of genetic associations which will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.

  Study EGAS00001004420

• McGill Epigenomics Mapping Centre

  The McGill Epigenomics Mapping Centre (EMC) and Data Coordination Centre (EDCC) were established in 2012 at the McGill University and Genome Quebec Innovation Centre (Montreal, Canada) to support large-scale human epigenome mapping for a broad spectrum of cell types and diseases. Previous epigenetic studies have provided profiles of specific chromatin marks in relation to basic biological processes, and future studies of molecular mechanisms must build upon these proofs-of-concept by integrating sequence-based variation with multiple levels of epigenetic and transcriptional regulation across the genome of human tissues and animal disease models. This project leverages the high-throughput sequencing infrastructure and expertise in genomics and transcriptomics at the McGill Innovation Centre to carry out this research. Controlled access to the data by collaborators and the greater scientific community is gained via a portal, which takes advantage of Compute Canada high-performance computing cluster resources to manage the large volume of data associated from the generation of reference epigenome maps. McGill University is one of two Canadian mapping and data coordination centres, the other based at the Michael Smith Genome Sciences Centre in Vancouver, British Columbia. The generation of comprehensive epigenome maps at McGill University is part of a larger international effort that is coordinated by the International Human Epigenome Consortium (IHEC), whose overall long-term objective is to determine the extent to which the epigenome shapes human populations over generations and in response to the environment. This project is funded under the Canadian Epigenetics, Environment, and Health Research Consortium (CEEHRC) by the Canadian Institutes of Health Research and by Genome Quebec, with additional support from Genome Canada. The computing and networking infrastructure, and part of the software development, are provided by Compute Canada and CANARIE.

  Study EGAS00001000995

• De novo detection of somatic variants

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

  Dataset EGAD50000001292

• Whole-genome sequencing data of poorly differentiated thyroid carcinomas and matched blood from six patients

  This dataset contains raw sequencing reads in FASTQ format from 12 samples, comprising paired tumour and matched blood DNA from six patients diagnosed with poorly differentiated thyroid carcinoma (PDTC). Genomic DNA was extracted from fresh-frozen tumour tissue and peripheral blood using standard protocols. Whole-genome sequencing was performed on the Illumina HiSeq X Ten platform, generating paired-end reads at an average depth of approximately 20X. These data support investigations into the somatic mutational landscape and genomic alterations associated with PDTC.

  Dataset EGAD50000001628

• Emirati Haploid Single-Sample-Assemblies (30 Individuals, 60 Assemblies)

  This dataset provides 27 phased diploid genome assemblies for Emirati trios, delivered in FASTA format. Assemblies were built with hifiasm (trio mode) from PacBio HiFi reads at ≥25× coverage for each parent and offspring, then scaffolded with NTLink and reference-guided merging using RagTag against CHM13v2. As part of the same program, a complementary set of single-sample diploid assemblies for 30 individuals (yielding 60 haplotypes) is being generated from deep PacBio HiFi data to expand a population-matched pangenome reference. Together, these resources capture Emirati genomic diversity and support downstream variant discovery and annotation.

  Dataset EGAD50000001753

• Development and Validation of a Prognostic and Predictive 32-Gene Signature for Gastric Cancer

  We applied this signature to a 567-patient GC cohort to establish genomic-based molecular subtypes and then used a support vector machine to build a molecular subtype-based risk-scoring model. Both source code and supplementary datasets for risk score prediction are available at https://github.com/hwanglab/Yonsei_gastric_cancer_32genes.

  Dataset EGAD00001008091

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Ither NB in Organoids RNA-Seq dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids RNA-Seq dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010283

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715

• PAGE: Global Reference Panel

  Stanford contributed samples to the PAGE study that can act as a population reference dataset across the globe. Therefore this dataset includes reference individuals, without phenotypes, chosen to help infer ancestry that will help us understand the diverse samples available in PAGE. The complete dataset comprises individuals of European, African, Asian, Oceanian, and Native American descent, from a total of over 50 populations. A subset of these individuals from Puno, Peru and Easter Island (Rapa Nui), Chile, are included in the PAGE samples that were whole genome sequenced in 2015. Additional details are available in the Study Acknowledgments. The Global Reference Panel comprises 6 sample sets: A population sample of Andean individuals primarily of Quechuan/Aymaran ancestry from Puno, Peru A population sample of Easter Island (Rapa Nui), Chile Individuals of indigenous origin from Oaxaca, Mexico Individuals of indigenous origin from Honduras Individuals of indigenous origin from Colombia Individuals of indigenous origin from the Nama and Khomani KhoeSan populations of the Northern Cape, South Africa In addition, we genotyped publicly available samples that will be hosted on the Bustamante lab website (https://bustamantelab.stanford.edu/). These comprise large public datasets to provide an open reference dataset for the world: The additional related individuals from the Americas in the Human Genome Diversity Panel (H952) plus all additional samples from the Americas A subset of the unrelated individuals from the Maasai in Kinyawa, Kenya (MKK) dataset from the International Hapmap Project hosted at Coriell Additional samples will be available for restricted use with a data access agreement with the Bustamante Lab. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356).

  Study phs001033

• Genotyping NIGMS CEPH Samples from the United States, Venezuela, and France

  The Human Genetic Cell Repository (HGCR) is sponsored by the National Institute of General Medical Sciences (NIGMS) with the mission of supplying scientists with the materials for accelerating disease gene discovery and functional studies. The resources available include highly-characterized, contaminant-free fibroblast cell lines, transformed lymphoblastoid cell lines (LCLs), and DNA samples derived from these cultures. While the Repository has a major emphasis on inherited diseases, it also contains large collections of cell lines gathered from populations around the world that are intended for use in facilitating the understanding of human variation. Prominent among these resources is the CEPH Reference Family collection contributed by the Centre d'Etude du Polymorphisme Humain (CEPH), Foundation Jean Dausset, Paris, France. The CEPH collection includes families collected by R. White (Utah), J. Dausset (French), J. Gusella (Venezuelan), and J. Egeland (Amish). There are a total of 809 individuals accounting for 832 pedigree positions in the reference families. Family relationships for the 61 reference families were verified at Coriell and approved by CEPH. In an effort to enhance the value of this cell culture resource available from the Repository, the Coriell Genotyping and Microarray Center used the Affymetrix Genome-Wide Human SNP Array 6.0 platform to genotype 181 samples from the NIGMS HGCR CEPH collection. Included are thirteen families from the United States (Amish Pedigree 884 and Utah Pedigrees 1331, 1356, 1400, 1416, 1424, 1427, 1477, and 1582), France (Pedigrees 35 and 66), and Venezuela (Pedigrees 102 and 104). Twelve of the families consist of 3 generations and one family consists of 2 generations. Pedigree charts and sample descriptions are available on the Repository catalog website (see below).

  Study phs000268

• Women's Interagency HIV Study (WIHS)

  The Women's Interagency HIV Study (WIHS), a multicenter, prospective study, was established in August 1993 to carry out comprehensive investigations of the impact of HIV infection and its clinical, laboratory, and psychosocial effects in women. The purpose of this study is to collect and evaluate these data from HIV infected and at-risk women to better understand and provide support for women whom are currently HIV infected or who are at risk for HIV infection. Participants will have study visits every 6 months. Questionnaires regarding sexual behavior, health care utilization, medical and obstetric/gynecological history, psychosocial factors, and sociodemographics will be completed by participants. Physical, gynecological, and lipodystrophy examinations will also be conducted at each visit, and current medication regimen will be noted. Blood and other bodily fluid samples will be collected and registered in both local and national repositories of the WIHS in conjunction with NIAID.

  Study phs001503

• MYC Inhibition By Omomyc Causes DNA Damage And Overcomes PARPi Resistance In Breast Cancer.

  This study investigates the role of MYC dysregulation in DNA damage response (DDR) and PARP inhibitor (PARPi) resistance in breast cancer. Using Omomyc, a direct MYC inhibitor, we demonstrate that MYC inhibition shuts down DDR genes in triple-negative breast cancer (TNBC), causing DNA repair defects and inducing DNA damage that synergizes with PARPi treatment. Through patient-derived models and clinical samples from metastatic HR-altered breast cancer patients treated with PARPi, we identify MYC transcriptional activity as a predictive biomarker of PARPi resistance. Digital spatial profiling (DSP) analysis of pre-treatment tumor biopsies reveals that patients with progressive disease have significantly elevated MYC signatures compared to responders. These findings support the therapeutic strategy of combining MYC inhibition with PARPi in PARPi-resistant breast cancers where high MYC activity predicts poor response to therapy.

  Study EGAS50000001347

• Identification of four new susceptibility loci for testicular germ cell tumour, including variants near GAB2, GSPT1 and ZFPM1

  Genome wide association studies (GWAS) have identified multiple risk loci for testicular germ cell tumour (TGCT), revealing a polygenic model of disease susceptibility strongly influenced by common variation. To identify further SNPs associated with TGCT we conducted a multistage GWAS with a combined dataset of >25,000 individuals (6,059 cases and 19,094 controls). We identified new risk loci for TGCT at 3q23 (rs11705932, TFDP2, P = 1.5 x 10-9), 11q14.1 (rs7107174, GAB2, P = 9.7 x 10-11), 16p13.13 (rs4561483, GSPT1, P = 1.6 x 10-8) and 16q24.2 (rs55637647, ZFPM1, P = 3.4 x 10-9). We additionally present detailed functional analysis of these loci, identifying a statistically significant relationship between rs4561483 risk genotype and increased GSPT1 expression in TGCT patient samples. These findings provide additional support for a polygenic model of TGCT risk and further insight into the biological basis of disease development.

  Study EGAS00001001302

• Vento_Placental_Cell_Atlas

  The Human Cell Atlas initiative is an ambitious global research effort which aims to describe every cell in the human body across all developmental stages to generate a reference map to accelerate progress in science and medicine particularly relating to human development and disease. The initiative is led by investigators based at the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard and funding support from the Wellcome and NIH. This specific project will assess human development. We aim to interrogate the cellular composition and molecular regulators underpinning development and maturation through single cell RNA-sequencing/spatial transcriptomics and computational algorithms to predict cellular developmental trajectories and cell-cell interactions. We will subsequent validate these findings in situ using allied imaging technologies e.g. immunohistochemistry and RNAscope and in vitro culture of human intestinal organoids (HIOs).

  Study EGAS00001004187

• Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare and lethal tumor in adolescent and young adult patients. Currently, there is no standard-of-care treatment for these patients. Reliable models that represent this disease and can be used for translational research are scarce. To model SCCOHTs, we have established eight patient-derived tumoroid lines from tumor lesions of three patients with SCCOHT. The tumoroids recapitulate genomic and transcriptomic characteristics of the corresponding patient tumors and capture intrapatient tumor heterogeneity. Organoid drug profiling using a library of 153 clinical compounds identified methotrexate as an effective and selective drug against SCCOHTs with a clinically relevant IC50 of 35 nmol/L. RNA sequencing demonstrated that methotrexate induced TP53 pathway activation and apoptosis. These data underscore that organoid technology can support the design of therapeutic strategies for rare cancers.

  Study EGAS00001007911