Search Results - EGA European Genome-Phenome Archive

Patient-Derived Breast Cancer Organoid Study

This study uses normal and tumor tissues from breast cancer patients to derive 3D cell culture models called organoids. Organoid technology is an innovative platform that can be used to study a patient's tumor in a dish ex-vivo. As part of this study we have comprehensively characterized these models using next-generation sequencing for: 1) pathogenic SNVs in a targeted gene panel 2) copy number alterations 3) transcriptome analysis using RNA sequencing and 4) single-cell RNA sequencing

Study phs002722

MutWP5__CRUK_Mutographs_of_CancerBreastCancer_Mastectomy__Exome_

Sequencing of LCM-derived microbiopsies from 30 women who underwent mastectomies due to a breast cancer diagnosis. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations.

Study EGAS00001003319

Investigating_the_genetics_of_immunity_against_Salmonella_in_humans

This study entails whole genome sequencing of an interleukin (IL)-12 b-1 receptor-deficient individual who presented with a chronic systemic Salmonella Enteritidis infection that did not resolve with standard IFNg and antibiotic treatment. Whole genome sequencing of the patient’s parents are also included.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001001664

Genomic Signatures Reveal DNA Damage Response Deficiency in Brain Metastases of Colorectal Cancer

Brain metastasis (BM) of colorectal cancer (CRC) is rare but lethal, and lacks effective therapies or a good understanding of its genomic landscapes. We conduct an analysis of whole-exome sequencing (WES) and whole-genome sequencing (WGS) data on 19 trios of patient-matched BMs, primary CRC tumors, and adjacent normal tissue to (1) document genomic signatures during the evolution of CRC BM; (2) identify clinically actionable targets for the BM treatment; and (3) identify potential drivers in CRC BM.

Study EGAS00001003659

TRIGR collaboration between University of Helsinkin and Children's Mercy Research Institute

DAC for collaborations between by the University of Helsinki and Children's Mercy Hospital, such as the Trial to Reduce IDDM in the Genetically at Risk (TRIGR), used to study the evolving epigenomics of immune cells in type 1 diabetes at single nuclei resolution

Dac EGAC50000000543

RRBS - MBD4-deficient AML

Reduced Representation Bisulfite Sequencing for WEHI-AML-1 and WEHI-AML-2. RRBS libraries were made with the NuGEN Ovation RRBS Methyl-Seq System. Bisulfite conversion was performed with the Qiagen Epitect kit. Sequencing was performed on an Illumina HiSeq2500.

Dataset EGAD00001003567

H3Africa TrypanoGEN Main WGS

This dataset is for TrypanoGEN Phase 1: Variant discovery, and includes 233 samples sequenced to approximately 10X coverage. Samples are from Guinea, Cote D’Ivoire, DRC and Uganda using Illumina HiSeq 2500.

Dataset EGAD00001005076

Martin_Ravenscroft-AUS1

Whole genome sequencing data on D19-0702 (AUS1), presented in Martin et al. 2020 (AUS1). WGS (Illumina HiSeq) was performed at Kinghorn Centre for Clinical Genetics, Garvan Institute of Medical Research. Data was analyzed using the Seave bioinformatic analysis pipeline (https://www.seave.bio).

Dataset EGAD00001006276

Fecal whole metagenomic shotgun sequencing data.

Human fecal WMS data from patients treated with combined anti-CTLA-4 and anti-PD-1 immunotherapy for advanced melanoma.

Dataset EGAD00001006734

HV31 - MGI standard short-read sequencing

MGI standard short-read sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~57×.

Dataset EGAD00001007044

HV31 - MGI CoolMPS short-read sequencing

MGI CoolMPS short-read sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~57×.

Dataset EGAD00001007048

Treatment arm information and sample sheet

Table of treatment arm information for the 418 RNAseq evaluable population.

Dataset EGAD00001009502

Genomic and transcriptomic determinants of host susceptibility, protection, and viral mutation in experimental SARS CoV-2 infection: RNA (2025-08-11)

Single-cell profiling of healthy adult volunteers that were inoculated with SARS-CoV-2. . This dataset contains all the data available for this study on 2025-08-11.

Dataset EGAD00001015679

A study of the immune system in patients with peripheral inflammatory neuropathy (CIDP): RNA adult (2025-10-02)

Leveraging single-cell sequencing technologies to shed light on the immune aetiology of chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) . This dataset contains all the data available for this study on 2025-10-02.

Dataset EGAD00001015725

Transcriptomic profiling of the Enteric Nervous System in Hirschsprung Disease (2025-07-31)

This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease. . This dataset contains all the data available for this study on 2025-07-31.

Dataset EGAD00001015667

MASS_Pilot: Muscle and Ageing Science Study - Collaboration with Wellcome Sanger Institute to characterise skeletal muscle ageing using Human Cell Atlas approaches (2025-07-31)

Transcriptomic analysis of skeletal muscle, to understand the mechanisms of muscle ageing. . This dataset contains all the data available for this study on 2025-07-31.

Dataset EGAD00001015670

Additional RNAseq data of metastatic breast cancer samples

Paired-end RNA sequencing data from 33 metastatic breast cancer samples. Sequencing was performed on the Illumina NovSeq 6000 using NEBNext Single Cell and Low Input RNA Library Prep Kit for Illumina.

Dataset EGAD00001015678

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-010

Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

Dataset EGAD00001006026

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-009

Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

Dataset EGAD00001006027

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-025

Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

Dataset EGAD00001006029

Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution

Ischemia reperfusion is an unavoidable step of organ transplantation. Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from six human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single cell RNA sequencing. Donor and recipient origin of cells from the reperfusion timepoint were deconvolved. Gene expression profiles were (1) compared between each donor cell type between timepoints and (2) compared between donor and recipient cells. Inflammatory responses from donor lung macrophages were found after reperfusion with upregulation of multiple cytokines and chemokines, especially IL-1 and IL-1. Significant inflammatory responses were found in alveolar epithelial cells (featured by CXCL8) and lung endothelial cells (featured by IL-6 upregulation). Different inflammatory responses were noted between donor and recipient monocytes and CD8+ T cells. The inflammatory signals and differences between donor and recipient cells observed provide insight into the cellular and molecular mechanisms of ischemia reperfusion induced lung injury. Further investigations may lead to the development of novel targeted therapeutics.

Study EGAS50000000490

Single-cell RNA sequencing of pediatric Hodgkin Lymphoma to study the inhibition of T cell subtypes

Here, we applied single-cell RNA-sequencing (scRNA-seq) on isolated HRS cells and the immune cells from the same cHL tumors. This allowed us to identify genes of cell surface proteins that are consistently overexpressed in HRS cells and can potentially be used as targets for antibody-drug conjugates or CAR T cells. Finally, we identify potential interactions by which HRS cells inhibit T cells, among which the Galectin-1/CD69 and HLA-DRA/LAG3 interactions. However, high levels of inter-patient heterogeneity of the interaction strength were observed. In conclusion, this study identifies new potential therapeutic targets for cHL and highlights the importance of studying heterogeneity when identifying therapy targets.

Study EGAS50000000432

Lebanon_HighCov_seq

We propose to investigate the genomics of a Lebanese sample. we plan (1) genotyping (2.5M) of 120 Lebanese individuals, choosing this platform to allow comparison with the 1000 Genomes and African Genome Variation project populations, (2) 8x sequencing of 100 individuals to provide unbiased population-level sequence information including allele frequencies, and (3) 30x sequencing of four individuals to allow inferences such as from PSMC/MSMC to be obtained. The current form is for the high-coverage sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002085

Lebanon_LowCov_seq

we propose to investigate the genomics of a Lebanese sample. we plan (1) genotyping (2.5M) of 120 Lebanese individuals, choosing this platform to allow comparison with the 1000 Genomes and African Genome Variation project populations, (2) 8x sequencing of 100 individuals to provide unbiased population-level sequence information including allele frequencies, and (3) 30x sequencing of four individuals to allow inferences such as from PSMC/MSMC to be obtained. The current form is for the low-coverage sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002084

ChIP-seq for 10 samples

This dataset contains ChIP-seq data generated from two patient-derived xenograft (PDX) models. For each model, sequencing data are provided from input control (n=1), IgG control (n=2), and FOXF1 immunoprecipitation (n=2). All the 10 samples are in bam file type.

Dataset EGAD50000001786

Sequencing data for oesophageal and related samples - Alex Frankell et al (RNA)

Data supporting: "The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic." Frankell et al. RNAseq (BAM files) 116 tumours

Dataset EGAD00001004423

Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets

Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/.

Dataset EGAD00001006331

DETECT-A NGS Data Batch 1

This batch is a subset of the full DETECT-A dataset, containing 43963 fastq files generated from 3024 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

Dataset EGAD00001008415

iPSC and iNeuron RNAseq, chip-seq and single cell CRISPR activation

Dataset includes 1) RNAseq for Bob_Ngn2 cell differentiation from iPSC to iNeuron stage (time point 0, 24, 48 and 96 hours). 2) Bob_Ngn2 cell line chip-seq (H3K4me3, H3K4me1, H3K27me3, H3K9me3, H3K27ac, H3K36me3) for both iPSC and iNeuron stage with 3 replicates at each time point. 3) Single cell CRISPR activation experiment with 96 endogenous genes.

Dataset EGAD00001010050

Sequencing data for oesophageal / related samples - Kazachenka et al (DNA)

Data supporting: "The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes" WGS for 452 samples

Dataset EGAD00001011095

DETECT-A NGS Data Batch 6

This batch is a subset of the full DETECT-A dataset, containing 9 fastq files generated from 8 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

Dataset EGAD00001015458

DETECT-A NGS Data Batch 4

This batch is a subset of the full DETECT-A dataset, containing 25210 fastq files generated from 3040 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

Dataset EGAD00001015360

DETECT-A NGS Data Batch 5

This batch is a subset of the full DETECT-A dataset, containing 12740 fastq files generated from 3211 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

Dataset EGAD00001015426

WXS dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

Dataset EGAD00001015638

RNA-seq dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

Dataset EGAD00001015639

Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Versions 1 and 2 (ROC-Cardiac Epistry 1 and 2-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data: The ROC Cardiac Epistry versions 1 and 2 include all cardiac arrest cases entered into the ROC database from December 1, 2005 to April 1, 2011. ROC Cardiac Epistry 3 includes cardiac arrest cases captured between 2011 and 2015, and introduced significant changes in how and which data were collected.For ROC traumatic injury Epistry data, please see: ROC-Trauma Epistry Objectives: To build a prospective population-based registry of participants with out-of-hospital cardiac arrest responded to by Emergency Medical Services (EMS). Specific aims: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of participants that experience cardiac arrest;to more fully establish the burden of cardiac arrest; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes.Background: Cardiac arrest is a common, serious, debilitating and costly public health problem. Although there has been a steady decline in morbidity and mortality from most cardiovascular diseases, high mortality rates for out-of-hospital cardiac arrests continue to pose a challenge for healthcare providers and a significant public health burden. The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Participant and care characteristics can predict favorable outcomes in cardiac arrests, but there is still a wide variation in outcomes that is not well understood. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region. Variations in geographic, socioeconomic and periodic factors may also be associated with differences in outcomes.Prior to ROC Cardiac Epistry, there were no North American population-based registries for out-of-hospital cardiac arrests. Therefore there was a need for standardized data collection of out-of-hospital cardiac arrests in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants: The registry included 109,326 cardiac arrest events from 264 EMS agencies transporting to 287 acute care hospitals from the following regional centers: Birmingham, Alabama; Dallas, Texas; Iowa City, Iowa; Milwaukee, Wisconsin; Pittsburgh, Pennsylvania; Portland, Oregon; San Diego, California; Seattle/King County, Washington; Ottawa, Ontario; Toronto, Ontario; and Vancouver, British Columbia.Design: ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital cardiac arrests in the ROC regions. Each ROC site had to ensure capture of all eligible cases within the EMS service areas. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Alternative methods included linkage to death registries and obituaries if the death occurred within 30 days. Sites submitted data using a web-based interface or batch uploads. Participants were not contacted directly.

Study phs003803

FEGA and European GDI: working together to improve human health

The Federated EGA is a global resource for discovery of and access to sensitive human omics and associated data consented for secondary use, through a network of human data repositories to accelerate biomedical research and improve human health. The Federated EGA network was launched in September 2022 with five inaugural nodes, and since 2023 seven operational nodes can share data across national borders in adherence to European and national laws. A few weeks after FEGA's official launch, in November 2022, the European Genomic Data Infrastructure (GDI) project was kicked-off . This European Commission co-funded project, coordinated by ELIXIR, is aimed to deliver federated, sustainable and secure data infrastructure to access genomic and related phenotypic and clinical data across Europe. This project supports the aim of the 1+MG initiative (25 EU countries, Norway and UK) to enable personalised medicine and health through a shared framework and infrastructure for securely accessing and integrating high quality genomic data and other health data across borders.1+MG will be an integral component of the European Health Data Space (EHDS) for secondary use (Healthdata@EU) as an authorised participant. How are Federated EGA and GDI similar? Given their shared visions, the Federated EGA and European GDI networks have a lot in common. To begin, they share the same overall goal of establishing networks of “nodes” that host sensitive human data within a jurisdiction and connecting these nodes in a global network to support data discovery and promote human genome data access for research and healthcare. FEGA and GDI are both initially focused on enabling access to human genomic data, while FEGA ambition is to expand the scope to clinical research data and other omics data in the future. FEGA and GDI are both built on open and interoperable software solutions, a subset of which are based on the LocalEGA components. FEGA and GDI implementation solutions are based on international community standards, for example those developed by the Global Alliance for Genomics and Health, which contributes to making them interoperable. Both FEGA and GDI allow for the nodes to make use of any solution that is fully compatible. As illustrated in Figure 1, a final key point is the significant overlap of institutions involved in envisioning and operating FEGA and GDI nodes, with the clear wish to keep them interoperable in the future. What distinguishes Federated EGA from GDI? Despite being largely similar, there are some differences between the FEGA and GDI networks, which we aim to clarify in this post. The first difference is the governance model that the nodes will operate to comply with national laws and GDPR. In the FEGA network, nodes have taken inspiration from the EGA data access model, where the infrastructure is a data processor of the hosted data and data controllership remains with the originating Data Access Committees (i.e. Data controllers) for each dataset. On the other hand, in the GDI network the controllership of datasets will be transferred to a 1+MG European Digital Infrastructure Consortium (EDIC) legal entity created by the Member States (MS), who will make data access decisions, with data holders having veto powers for their datasets. Importantly, FEGA nodes have the flexibility to choose another model to fit with their data protection framework, including becoming data controllers for their datasets. The second difference is the inclusion criteria for data. While FEGA nodes are designed to accept almost any type of omics data in need of control access (e.g. genomics, transcriptomics, genotyping, single cells sequencing, patient-tracked metagenomics), GDI nodes are initially, but not only, focused on accepting whole genome and exome sequencing data and affiliated data from sources such as (i) the Genome of Europe use case of the 1+MG initiative which specifically aims to fulfil the mission of building “a European network of national genomic reference cohorts of at least 500,000 citizens”) (ii) data collection of other types of genomic data identified by countries through the 1+MG dashboard and (iii) genomic data coming from data holders which would need to fulfil EHDS requirements. The third difference is the maturity of the software stacks. The FEGA network provides a set of software for data and metadata submission, storage, permissions management, and file distribution (the LocalEGA package). GDI is building a complete set of open source reference for the five functionalities covering the full data life cycle (a few more compared to the LocalEGA) including federated processing (analytics, AI/ML), which is still under active development. Notably, one of the GDI functionalities - storage and interfaces - can be satisfied by using the LocalEGA storage solution, highlighting the ability of FEGA and GDI to be interoperable. In both FEGA and GDI, nodes are allowed to use alternative solutions as long as they are fully interoperable with the networks. Figure 1 provides a simple overview of these described commonalities and differences. Figure1: schematic overview of the main commonalities and difference among a FEGA and a GDI node Can the same institute run a FEGA and a GDI node at the same time? The answer is Yes! We believe this is entirely possible and encouraged. As long as 1+MG requirements are continuously fulfilled in the implementation. The same trained personnel could operate the infrastructure and leverage the same national funding to run a FEGA and a GDI node. Several European nodes, especially GDI vanguard nodes like Norway, Sweden, Finland and Spain are following this model. The idea is that a lot of the work can be reused, given the overlapping scope and the interoperable technology. Thus, the hosted datasets can be discovered via the two catalogues, perhaps accessible under the same or different governance models. From a FEGA node perspective, the GDI datasets could simply be a subset of the datasets hosted in the FEGA node, which have their specific governance as any other. What's next? So, the amazing teams of people building the Federated EGA network and the European GDI network are working together to create infrastructures able to provide secure access to human genomic and associated data around Europe. Because we all know how much human genomics can improve healthcare and precision medicine. And we all want to collaborate to make it happen. This article has been reviewed collectively by members of the EGA and the GDI coordination team.

Blog fega-and-gdi

Resident memory CD8 T cells persist for years in human small intestine

Resident memory CD8 T cells (Trm) have been shown to provide effective protective responses in the small intestine (SI) in mice. A better understanding of the generation and persistence of SI CD8 Trm cells in humans may have implications for intestinal immune-mediated diseases and vaccine development. Analyzing normal and transplanted human SI we demonstrated that the majority of SI CD8 T cells were bona fide CD8 Trm cells that survived for over 1 year in the graft. Intraepithelial and lamina propria CD8 Trm cells showed a high clonal overlap and a repertoire dominated by expanded clones, conserved both spatially in the intestine and over time. Functionally, lamina propria CD8 Trm cells were potent cytokine-producers, exhibiting a polyfunctional (IFN-γ+ IL-2+ TNF-α+) profile, and efficiently expressed cytotoxic mediators after stimulation. These results suggest that SI CD8 Trm cells could be relevant targets for future oral vaccines and therapeutic strategies for gut disorders.

Study EGAS00001003676

Comprehensive Genomic Characterization of Translocation Renal Cell Carcinoma

Xp11 translocation renal cell carcinoma (tRCC) is a rare, female-predominant cancer driven by a fusion between the TFE3 gene on chromosome Xp11.2 and a partner gene on either chrX or an autosome. It remains unknown what types of rearrangements underlie TFE3 fusions, whether fusions can arise from both the active (chrXa) and inactive X (chrXi) chromosomes, and whether TFE3 fusions from chrXi translocations account for the female predominance of tRCC. To address these questions, we performed haplotype-specific analyses of chrX rearrangements in tRCC whole genomes. We show that TFE3 fusions universally arise as reciprocal translocations and that oncogenic TFE3 fusions can arise from chrXi:autosomal translocations. Female-specific chrXi:autosomal translocations result in a 2:1 female-to-male ratio of TFE3 fusions involving autosomal partner genes and account for the female predominance of tRCC. Our results highlight how X chromosome genetics uniquely constrains somatic chrX alterations and underlies cancer sex differences.This version of the dbGaP study provides a comprehensive set of whole genome data and tables with clinical information collected for the 16 patients (15 pateints as tRCC and 1 patient as ccRCC) in the study cohort. The data also contains 12 RNA-seq samples used in the study and analyses. We anticipate that this data will considerably advance our molecular and genetic understanding of oncogenic translocations in TFE3-tRCC involving inactive chromosome X and its role in cancer sex bias.

Study phs003008

Field studies of Cryptosporidiosis and Enteropathogens in Bangladesh

Cryptosporidiosis causes severe diarrhea in infants in the developing world. There is no vaccine to prevent it, and little in the way of treatment. This study on Bangladeshi urban slum children aims to support the design of a vaccine, both by determining how the immune system protects from infection and by identifying the genotypes of the parasite that should be included in a vaccine, as well as aid in development of therapies by identifying human genes that control infection. The primary objective of the study was to determine the incidence and contribution to disease of the different species and genotypes of cryptosporidia. Secondary objectives were designed to determine acquired immune response to cryptosporidiosis and identify human genes that influence susceptibility to cryptosporidiosis. This is an observational study. Children were recruited from Mirpur Dhaka slum (Cohort 1) and rural Mirzapur (Cohort 2) and followed for cryptosporidium infection longitudinally from birth through age 4 years in Cohort 1 and birth through age 2 years in Cohort 2. Biweekly household visits for diarrheal surveillance were made in addition to anthropometric measurements of mother and child, blood samples collected two times each year from the child, a work-up of diarrheal stools and non-diarrheal surveillance stools for cryptosporidium and other enteropathogens, and blood and breast milk samples from the mother. A detailed description of the study design and procedures can be obtained from publication: Kevin L Steiner, et al., 2018, PMID: 29897482.

Study phs001665

Human genomic and phenotypic synthetic data for the study of rare diseases

The purpose of this dataset is to facilitate development of technical implementations for rare disease data integration, analysis, discovery, and federated access. This synthetic dataset includes clinical and genomic data from 6 rare disease cases. It consists of 18 whole genomes (6 index cases with their parents) which have genetic background based on public human data sequenced in the context of the Illumina Platinum initiative (Eberle, MA et al. (2017)) and made available by the HapMap project (https://www.genome.gov/10001688/international-hapmap-project). In each of the cases, real causative variants correlating with the phenotypic data provided were spiked-in. The cases included in this synthetic dataset correspond to the following type of disorders: CASE 1- Congenital myasthenic syndrome (Autosomal Dominant -de novo variant) CASE 2- Macular dystrophy (Autosomal Dominant) CASE 3- Muscular dystrophy (Autosomal Recessive-compound heterozygous variants) CASE 4- Mitochondrial disorder (Autosomal Recessive-consanguineous case - homozygous variant) CASE 5- Breast cancer (Autosomal Dominant) CASE 6- Similar as case 1 for patient matchmaking tests: Congenital myasthenic syndrome (Autosomal Dominant-de novo variant) For each case you will be able to download the following data: clinical information (phenopackets per individual and pedigree per family), raw genomic data (FASTQ and BAMs) and processed genomic data (vcfs). When using the data, the following should be acknowledged: the RD-Connect GPAP (https://platform.rd-connect.eu/), EC H2020 project EJP-RD (grant # 825575), EC H2020 project B1MG (grant # 951724) and Generalitat de Catalunya VEIS project (grant # 001-P-001647).

Study EGAS00001005702

BCR Signaling in human BM PC

The functions of bone marrow plasma cells (BMPC) beyond antibody production are not fully elucidated and distinct subsets of BMPC suggest potential different functions. Phenotypic differences were identified for human BMPC depending on CD19 expression. Since CD19 is a co-stimulatory molecule of the B-cell-receptor (BCR), and IgA+ and IgM+ BMPC express the BCR on their surface, we here studied whether CD19 expression affects cellular responses, such as BCR signaling and the expression of checkpoint molecules. We analyzed 132 BM samples from individuals undergoing routine total hip arthroplasty. We found that both CD19+ and CD19- BMPC expressed BCR signaling molecules. Notably, the BCR-associated kinase spleen tyrosine kinase (SYK) including pSYK was higher expressed in CD19+BMPC compared to CD19- BMPC. BCR stimulation also resulted in increased kinase phosphorylation downstream of the BCR while expression of CD19 remained stable afterwards. Interestingly, the BCR response was restricted to IgA+ BMPC independently of CD19 expression. With regard to the expression of checkpoint molecules, CD19- BMPC expressed higher levels of co-inhibitory molecule programmed cell death protein-1 (PD-1) than CD19+ BMPC. IgA+ BMPC characteristically upregulated PD-1 upon BCR stimulation in contrast to other PC subsets and inhibition of the kinase SYK abrogated PD-1 upregulation. In contrast, expression of PD-1 ligand, B and T lymphocyte attenuator (BTLA) and CD28 did not change upon BCR activation of IgA+ BMPC. Here, we identify a distinct functiotype of IgA+ BMPC that is independent of the phenotypic heterogeneity of the subsets according to their CD19 expression. The data suggest that IgA+ BMPC underlie different regulatory principles and/or exert distinct regulatory functions.

Study EGAS00001004948

Human breast transcriptome analysis

Obesity is a risk factor for the development of post-menopausal breast cancer and is associated with a worse breast cancer prognosis. Here we carried out transcriptome profiling on nontumorous breast tissue to define the molecular changes that occur related to excess body fat and adipose inflammation. A second goal was to determine if blood biomarkers reflect molecular changes in the breast. Increases in a variety of pathways linked to tumor development and progression were found. Moreover, increased expression of several drug targets including aromatase, the rate-limiting enzyme for estrogen biosynthesis, and PD-1 was observed. Various blood biomarkers that are associated with either elevated risk of breast cancer or worse prognosis were altered and correlated with molecular changes in the breast. Collectively, this study helps to explain both the link between obesity and breast cancer and the utility of blood biomarkers for determining risk and prognosis.

Study EGAS00001004665

RNA-Seq Brest Patient-derived Tumor Organoids

This dataset includes 14 RNASeq samples from 8 patients. For some patients, organoids at different passages have been profiled. They can be identified by their alias, composed of the following structure: <subjectId>_O<organoid_number>_<passage>_RNA. For example, ICSBCS002_O1_1_RNA indicates the earlier passage of organoid 1 for subject ICSBCS002, and ICSBCS002_O1_2_RNA indicates the later passage. Additionally, WCM2137_O1_RNA and WCM2137_O2_RNA indicate two organoids (O1 and O2) derived from different tissues. More information about the passages and tissues can be found in the sample information table.

Dataset EGAD50000000960

Common origin and somatic mutation patterns of composite lymphomas and leukemias

The dataset contains six composite lymphomas and leukemias cases (four composite B-cell lymphomas (case 1-4), and two combinations of B-cell and T-cell lymphoma (case 5+6)). Two tumor and one non-tumor (NTC) sample were sequenced from each case after library prep with NEBNext Ultra DNA Library Prep Kit, Exome capturing was done with NimbleGen SeqCap EZ Choice kit, and sequenced on a Illumina HiSeq 2000 HO and given as fastq files. WGA (Qiagen REPLI-g kit) was used for case 2 and 3. Case 1-4 were microdisected, case 5+6 were flow-sorted.

Dataset EGAD50000001486

RNASeq from PC12 cell lines (derived from PPGL) cultivated under 21% (normoxia) and 1% (hypoxia) oxygen conditions.

RNASeq fastq files from PC12 cells (derived from rat PPGL) were cultivated in normoxia conditions (37˚C, 5% CO2 and 21% O2 balanced with N2) or in hypoxia conditions in a hypoxic incubator (37˚C, 5% CO2 and 1% O2 balanced with N2), for short time (12h, 24h, and 48h) or prolonged time (36 days). Samples at each timepoint were cultured in triplicate (total 24 paired end fastq files). Sequencing was performed with the Illumina NovaSeq6000.

Dataset EGAD50000001200

Multi-region RNA-Seq data of 10 neuroblastoma cases

To investigate intratumour heterogeneity and to better understand tumour evolution in neuroblastoma, we have performed a multi-region RNA sequencing on a total of 51 spatially separated tumor samples from 9 primary neuroblastomas (2 low-risk, 1 intermediate-risk and 6 high-risk) and 1 relapsed neuroblastoma. We also assessed the impact of chemotherapy on the clonal expansion by sequencing tumour regions from one medium risk and one high-risk tumour for which we had matched samples obtained at diagnosis and after chemotherapy.

Dataset EGAD00001008133

eMERGE Network Phase III Clinical Sequencing: eMERGEseq Panel

The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in September 2007 and began its third phase in September 2015. eMERGE III consists of nine study sites, two central sequencing and genotyping facilities, and a coordinating center. eMERGE Phase III aims to: 1) sequence and assess the phenotypic implication of rare variants in a custom designed eMERGEseq panel consisting of 109 genes (including 56 ACMG actionable finding list genes and the top 6 genes from each site relevant to their specific aims), as well as approximately 1400 SNPs; 2) assess the phenotypic implications of these variants by developing, validating and implementing new phenotype algorithms, 3) integrate genetic variants into EMRs to inform clinical care; and 4) create community resources. Included in this study are: ~24,000 eMERGE participants from 10 eMERGE III study sites. Corresponding demographics, body mass index measurements. Top PheWAS codes generated from a collated list of ICD codes from all study sites. Study sites and participants include: Cincinnati Children's Hospital Medical Center (CCHMC): Cincinnati Children's Hospital Medical Center (CCHMC) is a not-for-profit hospital and research center pioneering breakthrough treatments, providing outstanding family-centered patient care and training healthcare professionals for the future, and dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. We bring a comprehensive electronic health record (EPIC), a deidentified i2b2 data warehouse of 680K patient records, a biobank with >261,000 consents that allow return of results to >84,000 patients and guardians who have provided DNA samples, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research. CCHMC will help the eMERGE III Steering Committee identify genes for the eMERGE III targeted sequencing panel, provide 3,000 DNA samples from CCHMC patients to be sequenced, review targeted gene panels from clinical care at CCHMC for somatic mosaicism and reinterpretation, and further develop and disseminate a software workflow suite for sequence analysis. We will also extend our work generating phenotype algorithms using heuristic and machine learning methods to many new childhood diseases. We will develop tools to evaluate adolescent return of results preferences, examine the ethical and legal obligations and potential to reanalyze results, and develop clinical decision support for phenotyping, test ordering, and returning sequencing results. Children's Hospital of Philadelphia (CHOP): The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP), and one of the world's largest genetics research programs, with to state-of-the-art high-throughput sequencing and genotyping technology. Our primary goal is to translate basic research findings to medical innovations. We aim to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders, including asthma, autism, epilepsy, pediatric cancer, learning disabilities, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. Participants were recruited from the CAG biorepository (n>450,000), specifically from >100,000 CHOP pediatric patients and family members, which is enriched for rare-diseases (n>12,000). Center for Applied Genomics, The Children's Hospital of Philadelphia We gratefully thank all the children and their families who enrolled in this study, and all individuals who donated blood samples for research purposes. Genotyping for this project was performed at the Center for Applied Genomics and supported by an Institutional Development Award from The Children's Hospital of Philadelphia. Sequencing was supported by the National Institutes of Health through an award from the National Human Genome Research Institute's Electronic Medical Records and Genomics (eMERGE) program (U01HG008684). Columbia University: The goal of the Columbia eMERGE III project is to develop methods for integrating genomic data in EHRs and to study the impact of such genomic informatics interventions on the health of a diverse, underserved urban adult English- and Spanish-speaking patient population in Northern Manhattan served by Columbia University Medical Center/New York-Presbyterian Hospital system. The study group is 2500 patients recruited from diverse clinics and community outreach centers of self-reported White (~61%), Asian (~11%), African-American (~11%), American Indian/Alaska Native (<1%) racial and Hispanic (~33%) ethnic backgrounds. There are two subgroups in the study cohort - a retrospective group (N=1052) that includes patients from oncology and nephrology clinics, and a prospective one (N=1448) that includes healthy individuals as well as participants with diverse medical conditions. Confirmed pathogenic variants in 70 selected genes will be returned to participants and their healthcare providers through the EHR integration. Participants are able to choose the results they receive and will have the freedom to meet with a genetic counselor and a geneticist to review results. The impact of genetic testing on clinical care is determined by periodic monitoring of EHRs. Geisinger: Samples and phenotype data in this study were provided by the Geisinger MyCode® Community Health Initiative. Participants are recruited across the Geisinger System via online consents or in-person consents at a hospital or clinic visit. Enrollment is ongoing with over 100,000 individuals currently consented. Partners Healthcare (Harvard University): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people's health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women's Hospital), the Biobank provides: Banked samples (plasma, serum, and DNA) collected from consented patients Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women's Hospital and Massachusetts General Hospital Pathology Departments Sample handling and preparation services Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart Data access through our research portal. To date, over 70,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 130 million dollars in NIH research. Kaiser Permanente Washington/ (KPWA) / University of Washington (UW): KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N=2,500.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes N=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (N=1,255), in order to allow us to enrich germline pathogenic variants. Mayo Clinic: The Return of Actionable Variants Empirical (RAVE) Study was approved by the Mayo Clinic IRB. We recruited 2537 participants from Mayo Clinic biobanks in Rochester, MN, who had hypercholesterolemia or colon polyps, thereby enriching for Familial hypercholesterolemia (FH) and monogenic causes of colorectal cancer (CRC). Additional eligibility criteria were: 1) residents of Southeast MN who were alive and aged 18-70 years; 2) LDL-C level >155 or >120 mg/dl while on lipid-lowering therapy; 3) no known cause of secondary hyperlipidemia; and 4) no cognitive impairment or dementia that would compromise their ability to give written informed consent. Based on these criteria, we identified 5270 eligible patients and obtained informed consent from 3030 participants. Recruitment was conducted in waves and utilized mailed recruitment packets consisting of a study brochure, a written informed consent form, a baseline psychosocial questionnaire, and a return postage-paid envelope. DNA of 2537 participants was sent for CLIA-certified targeted sequencing of 109 genes including genes associated with FH and CRC. Targeted sequencing and genotyping was performed in a Central Laboratory Improvement Amendment (CLIA)-certified laboratory. Northwestern University: Samples and data used in this study were obtained from patients from Northwestern Medicine, an integrated healthcare system, formed through a partnership of Northwestern Memorial HealthCare and Northwestern University Feinberg School of Medicine. Participants include a retrospective cohort from the Northwestern Pharmacogenomics Study, funded through the eMERGE II project, NHGRI (3U01HG006388-02S1) and a prospective cohort from the Genetic Testing and Your Health Study, funded through the eMERGE III project, NHGRI (U01HG008673). Patients were eligible to participate if they were18 years or older and see a physician at Northwestern Medicine. Patients consented to genetic testing and to allow their results to be placed in their electronic medical record. Vanderbilt University Medical Center: Vanderbilt University Medical Center (VUMC) participants were enrolled in the eMERGE Network through the Vanderbilt Genome-Electronic Records (VGER) project. Patients were provided the appropriate consent to receive clinically relevant genetic results (N=2,700). Participants were eligible if aged 21 or over, had a healthcare provider at VUMC, and visited the provider at least 3 times in the past 3 years. Meharry Medical College: Inclusion of ethnic groups in genomic research is critical to identify possible reasons for health disparities. African-Americans are being enrolled in various outpatient clinics of Nashville General Hospital at Meharry, an inner city hospital primary serving a poorer patient group. A total of 500 African Americans with four cancer types demonstrating health disparities in this population - prostate, colon, breast, lung are identified and approached by clinical research coordinators. The purpose of the study is to determine if any genetic information can be identified from these patients who have or are at high risk of one of these disparate cancers. All participants provide written informed consent and HIPAA authorization to provide blood samples for broad research use and permission to access data in their hospital electronic medical record for research now and in the future. An extensive demographic profile is obtained and entered into a REDCap database. Blood samples are obtained for a panel of alleles from extracted DNA at Baylor. In addition, de-identified coded samples are processed and stored in a central biorepository for further DNA, RNA and proteomic analyses. The survey and phlebotomy are performed at the time of the initial contact and agreement to participate. Nearly all patients approached willingly agree to participate for potential benefit to themselves, family members, or humankind. Little concern is voiced of providing samples for genetic analysis. Study investigators will share results with the participants and providers if testing does not indicate high risk. Results indicating increased risk or actionable alleles for the patient and/or family will be returned by a genetic counselor. Monitoring of the patients' health in this cohort will continue to be followed in the EMR to identify any future associations that might explain health disparities in African Americans. Proposals will be reviewed from investigators to study the genetic or proteomic samples as well as the clinical and demographic information in the repository. Please note that this version of the dataset has a handful of mismatches between genotyped and provided sex. Data with the following IDs should be removed prior to analysis: 420252874213744142412243424569384245694642672223

Study phs001616

Molecular Characterization of Prostate Cancer Specimens by Bulk and Single Cell Analysis

Version 1: We performed single-cell RNA-sequencing (scRNA-seq) of fresh biopsies from metastatic castration resistant prostate cancer. Additionally, where available, we performed matched bulk whole exome sequencing (WXS; tumor and normal paired) and whole transcriptome sequencing for the same individuals. We also performed bulk whole exome (WXS) and RNA-sequencing (RNA-Seq) from FFPE pre-treatment biopsies from patients with clinically localized high-risk prostate cancer.Version 2: We added data from a randomized phase 2 trial of radium-223 with or without pembrolizumab in patients with Metastatic Castration-Resistant Prostate Cancer (mCRPC) to bone. After enrollment, study participants underwent bone biopsy and were randomized 2:1 to receive radium-223 at 55 kBq/kg every 4 weeks + pembrolizumab at 200 mg every 3 weeks (Arm A, R223+P) or radium-223 at 55 kBq/kg every 4 weeks alone (Arm B, R223). Stratification factors were alkaline phosphatase ≥220 vs. Data generated includes bulk whole exome sequencing (WXS), ultra-low pass whole genome sequencing (WGS) at 0.1X coverage, and targeted-capture sequencing. The ultra-low pass sequencing was used as part of the selection criteria for the target capture sequencing. Note: Two subjects in this study are linked to phs001577 and phs000915 respectively.

Study phs001988

Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types (RNAseq)

Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

Study EGAS00001007428

Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types

Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

Study EGAS00001007412

WGS of 11 MPNSTs, 7 ANNUBPs and 7 blood and normal tissue controls

Whole-genome sequencing (WGS) of 11 MPNSTs, 7 ANNUBPs and 7 controls (6 blood and 1 normal tissue) sequenced for Magallon-Lorenz, 2026. Sequenced at BGI with DNBseq technology (2x150bp) following standard protocols. Raw fastq files provided.

Dataset EGAD50000002492

H3Africa ACEGID Array Phenotype

Phenotype data for Lassa Fever cases and population controls from Nigeria and Sierra Leone associated with genotype data generated using Illumina H3Africa array version 1.

Dataset EGAD00001010923

CancerSEEK ctDNA FASTQ files

Sequencing data from 1,005 cancer patients and 812 healthy controls. All samples prepared using Safe-SeqS technology and sequenced on an Illumina MiSeq and/or HiSeq instrument. Paired FASTQ files for correspond to read 1 and the index read present (R and I respectively).

Dataset EGAD00001003931

SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

SNV calls generated using the SomaticSniper-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

Dataset EGAD00001004431

SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

SNV calls generated using the SomaticSniper-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

Dataset EGAD00001004432

SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

SNV calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

Dataset EGAD00001004433

SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

SNV calls generated using the MuTect-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

Dataset EGAD00001004434

CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

CNA calls generated using the SomaticSniper-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

Dataset EGAD00001004440

CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

CNA calls generated using the SomaticSniper-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

Dataset EGAD00001004441

CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

CNA calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

Dataset EGAD00001004442

CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

CNA calls generated using the MuTect-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

Dataset EGAD00001004443

Kidney tumour_DNA (2018-09-19)

This is a bulk DNA and RNA sequencing study of human renal tumours . This dataset contains all the data available for this study on 2018-09-19.

Dataset EGAD00001004346

Transcription factor binding in human monocyte differentiation

This dataset consists of ChIP-seq data data from human monocytes, monocyte-derived dendritic cells as well as monocyte-derived cells that were subjected to mRNA transfection for PU.1, IRF4, and EGR2. In total, it the data set includes 18 samples.

Dataset EGAD00001006602

Fecal 16S rRNA gene sequencing

Human fecal 16S rRNA gene sequencing data from patients treated with combined anti-CTLA-4 and anti-PD-1 immunotherapy for advanced melanoma.

Dataset EGAD00001006735

CBD-RAW-SC-ATAC: 10X Single-Cell ATAC

Raw Illumina sequencing data from single-cell ATACSeq experiments. For further information regarding this dataset, please contact Julian Knight and Tatjana Sauka-Spengler at contact@combat.ox.ac.uk.

Dataset EGAD00001007963

CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) of CLL_24

To explore intratumor-heterogeneity of CLL_24 using single-cell multi-omics approach, we generated single-cell CITE-seq data for CLL_24, coupling scRNA-seq and protein surface marker measurements with oligo-tagged antibodies.

Dataset EGAD00001009174

Raw count matrix for 418 baseline samples

Count matrix from 418 pre-treatment (Ven-Obi or Clb-Obi) CD19+ B cells

Dataset EGAD00001009501

cell-free methylated DNA immunoprecipitation and high-throughput sequencing data for samples from liver transplant recpients with graft pathologies

Bam and indexed bam files after removal of duplicates and trimming of the unique molecular identifiers. Sequencing was performed on NovaSeq 6000 platform.

Dataset EGAD00001010305

WXS dataset of Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

Creation of living organoid biobank for ewing and ewing-like sarcomas

Dataset EGAD00001015417

Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line. REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIP’d and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified using Qiagen RNeasy. Knock down of CEBPE was validated by qRT. RNA integrity >7.7 for all samples. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

Dataset EGAD00001004084

Characterizing Individual Cells Obtained from Bone Marrow Biopsies of MPN Patients

We profiled the transcriptomes of individual cells obtained from bone marrow aspirates of 7 treatment-naïve newly diagnosed JAK2-mutant myeloproliferative neoplasm (MPN) patients (3 polycythemia vera and 4 essential thrombocythemia patients), and 2 healthy controls. The submitted data corresponds to sequencing reads mapped to the human reference genome GhRC38 build using CellRanger for a total of 9 samples (one per patient). In addition, to reconstruct the lineage histories of single cells in MPN patients, we performed whole-genome sequencing of single-cell-derived colonies of hematopoietic stem and progenitor cells from 2 essential thrombocythemia (ET) patients: 22 JAK2-mutant colonies and 20 WT colonies for patient ET 1; and 13 JAK2-mutant colonies and 21 WT colonies for patient ET 2. The submitted data consists of sequencing reads aligned to the human reference genome GhRC38 build using bwa-mem. Each file corresponds to the whole-genome sequencing data for one colony.

Study phs002308

ALLELE Consortium Glioblastoma Project

Glioblastoma patient samples were sequenced for this project. The purposes of this project are: (1) to establish an umbrella protocol as a mechanism for identifying patients (in the USA and international sites) who agree to the collection, storage, and broad usage of their specimens and ongoing collection, and review of their medical information for the purposes of minimal-risk research and use of such data in clinical trials on which the patient may enroll; (2) to develop operations that facilitate investigator access to the data and/or tissue to conduct research, while minimizing risks to participants and promoting responsible conduct; and (3) to provide the infrastructure for the sharing of de-identified, coded samples, clinical data, and genomic data between participating investigators and institutions. Eligible patients include patients with known or suspected nervous system tumors or other neurologic diseases. Whole exome sequencing from the stated project will be released under this submission.

Study phs003000

INCLUDE: Down Syndrome Early Post-Natal Brain Multiome

Neurodevelopmental deficiencies and neuronal dysfunction contribute to cognitive impairment in individuals with Down syndrome, but what molecular pathways underlie the defects that lead to intellectual disability remain unclear. Human brain development is precisely choreographed through tightly regulated transcriptional programs. Proper regulation of these transcriptional programs is necessary for developing the numerous functionally distinct regions, cell types, and connections of the brain, and forming the basis for human-specific social, cognitive, and motor abilities. These data establish a reference of molecular features of the DS developing brain. Such foundational information will provide not only a reference for any existing and future models, but also a basis for understanding disrupted neural development and impaired cognition in DS.Dataset 1 contains single-nucleus RNAseq and ATACseq from frozen postmortem human basal forebrain tissue. Dataset 2 contains single-nucleus RNAseq and ATACseq from frozen postmortem human dorsolateral prefrontal tissue. Dataset 3 contains single-nucleus RNAseq and ATACseq from frozen postmortem human caudate nucleus tissue.

Study phs004098

Next_gen_seq_of_eye_cancers

Retinoblastoma (RB), the commonest eye cancer in children was the first cancer for which a genetic cause was identified: the Rb1 gene is a tumour suppressor gene that is mutated in RB. The Rb1 gene defect alone does not predict the clinical outcome. We propose to study other possible mechanisms: 1. Stepwise further mutations occur in RB, increasing its carcinogenesis. We will sequence the whole genome in RB tissue, and relate the different genes expressed to the treatments used. 2. Extracellular matric proteins contribute to a tumour permissive environment for RB to continue to grow. This includes Samll Leucine Rich Proteoglycans (SLRP), a family of 15 secreted extracellular matrix proteins involved in eye development. 3. Cancer stem cells (CSC), a subpopulation of treatment resistant cells, drive RB tumours, and whether these stem cells can be manipulated for new therapies. The aim of this study is to assist finding targeted diagnostic techniques and treatments for RB.

Study EGAS00001002309

Resequencing_candidate_genes_for_male_spermatogenic_impairment

This study aims to identify novel candidate variants from human Y-chromosomal genes DAZ, BPY2 and CDY1 by resequencing the coding regions of these genes from male patients with spermatogenic impairment. The coding regions of the genes have been amplified by standard PCR, amplicon lengths range from 244 to 486 bp. A total of 61 amplicons were amplified for each of the 96 patients, totalling to approx. 25 kb per sample. Amplicons were quantified by gel electrophoresis and pooled in approx. equimolar concentrations per patient. For each of the 96 submitted samples, approx. 1 microgram of amplified DNA pool is provided in a total volume of 120 microlitres. The samples need to be indexed and libraries prepared for a PE250bp Illumina MiSeq run. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002157

Single-cell level characterization of B cell depletion and repopulation following rituximab in systemic lupus erythematosus

Rituximab, a CD20+ B cell depletion therapy, is frequently used in the treatment of systemic lupus erythematosus (SLE). However, variability in patient response highlights the need for a deeper understanding of the underlying immune cell dynamics of B cell depletion and repopulation. In this study, we conducted longitudinal single-cell profiling of nine SLE patients treated with rituximab from pretreatment to up to 15 months post-treatment. These were compared to eight healthy controls. We profiled PBMCs via 10X Genomics single-cell RNA, surface protein (CITE-seq), B cell receptor (BCR), and T cell receptor (TCR) sequencing and sequenced bulk BCR repertoires in parallel. For single cell sequencing, 10 pools were created with an equal number of cells from 4 samples each. Samples collected at different timepoints from the same patient were distributed across different pools to allow demultiplexing of individuals using genotypes captured from the scRNA-seq data. Libraries were pooled using a ratio of GEX:CITE:TCR:BCR=9:2:1:1 and were sequenced across two lanes of the NovaSeq 6000. For bulk BCR sequencing, individual samples were demultiplexed using primer barcodes and paired-end BCR amplicon reads were merged prior to submission; data are provided as unmapped single-end reads.

Dataset EGAD00001015817

Privacy Notice for the Account User

Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Username and password (to authenticate access to the system) IP Address (for anonymous usage statistics) We process your personal data: to provide you with the authenticated access to the EGA service (opening and managing submission and distribution account), to publicly publish some aggregate data to facilitate scientific research (e.g. number of accounts, geographic distribution), to better understand the needs of the users and to guide future improvements of the service, to create anonymous usage statistics. If you do not provide us with your personal data we will not be able to open the user account and offer you our services or we will only provide you a subset of functionalities available within the service. 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), Requested dataset Data access committee – DAC will have access to the name, email, organization, affiliation, title/position of the distribution user account, using it for their own purpose of granting access to their datasets. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Distribution user account data are in the process of granting access disclosed to dataset(s) DAC, which might be a recipient in countries outside of the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI) is necessary for important reasons of public interest embedded in the aims of the EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union. 6. How long do we keep your personal data? All data are stored for as long as you have the account open. Thereafter the storage is prolonged for as long as our service is live, even if you stop using our services. This prolongation is necessary for further scientific research, to ensure legal compliance and security and to facilitate internal and external audits it they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

Documentation data-protection/privacy-notice/ega-user-account

The Role of CDX2 in Controlling ABCB1 Expression and Chemosensitivity in Human Colon Cancer

This study reports the results of RNA sequencing (RNA-seq) experiments performed on two human colon cancer cell lines (HT-29, DLD-1) that were genetically engineered to achieve either the constitutive expression (in HT-29 cells) or the selective inactivation (in DLD-1 cells) of the transcription factor CDX2, a master regulator of embryonic gut development and a key regulator of multi-lineage differentiation in adult colon epithelial cells. Our previous studies had identified lack of CDX2 expression as a prognostic biomarker of poor prognosis and a predictive biomarker of benefit from adjuvant chemotherapy in Stage-II and Stage-III colon cancer patients (Dalerba et al., NEJM, 374:211-222, 2016; PMID: 26789870). The molecular basis of these associations, however, remained poorly understood. The present study was designed to identify which genes are under the transcriptional control of CDX2, in order to clarify their role in shaping colon cancer resistance to chemotherapy. Of the two lines included in this study, the first (HT-29) is CDX2-negative at baseline, and was infected with a lentivirus vector encoding for the cDNA of the human CDX2 gene under the control of a constitutive promoter (CMV). The second line (DLD-1) is CDX2-positive at baseline, and was infected with a series of lentivirus vectors encoding for CRISPR/Cas9 constructs designed to selectively inactivate the CDX2 gene. In both cases, infected cells were purified by fluorescence-activated cell sorting (FACS), based on the differential expression of a green fluorescent reporter (EGFP) that was also encoded by the lentivirus vectors, and transcribed in tandem with either the CDX2 cDNA (HT-29) or CRISPR/Cas9 gRNAs targeting CDX2 (DLD-1). The experiments were designed to include 3 experimental replicates per condition, and to compare the transcriptional profile of genetically engineered cells with that of autologous controls (i.e., HT-29 cells infected with an "empty" version of the same lentivirus vector used to over-express CDX2, DLD-1 cells engineered with a "non-targeting" CRISPR/Cas9 gRNA). In the specific case of DLD-1 cells engineered with CRIPSR-Cas9 constructs targeting CDX2, infected cells were sorted based on the differential expression of EGFP and then plated as single-cells, in order to sub-culture three isogenic clones, all of which were genetically sequenced to confirm bi-allelic knock-out of the CDX2 gene, and confirmed to lack CDX2 protein expression by Western blot. The results of our experiments demonstrate that, in human colon epithelial cells, CDX2 controls the expression of the ABCB1 efflux pump, by positively regulating the transcription of the corresponding gene.

Study phs002903

DNA-Sequencing of Baseline Plasma From the Phase III Alliance A031201 Trial

Liquid biopsy assays tailored for metastatic castration-resistant prostate cancer (mCRPC) patients are needed to identify molecular alterations and predict survival in the context of androgen receptor (AR) inhibitors. We developed a novel plasma cell-free DNA (cfDNA) sequencing assay to detect circulating tumor DNA (ctDNA) and alterations in key mCRPC driver genes, and tested associations with clinical features and survival outcomes in a phase III trial. cfDNA was isolated from evaluable baseline plasma specimens of untreated mCRPC patients (n=790) enrolled in the Alliance A031201 randomized phase III trial (NCT01949337) prior to enzalutamide therapy with or without abiraterone acetate and prednisone. A customized targeted cfDNA sequencing assay was used to detect AR and non-AR alterations in mCRPC. For this, DNA-seq libraries were constructed from cfDNA using Takara ThruPLEX Tag-Seq or Plasma-Seq kits, and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. ctDNA positivity was defined as >20% ctDNA using an aneuploidy-based estimate derived from ichorCNA (Group 1) or a novel definition of ≤20% ctDNA, but with detection of any alteration in AR, or gain of MYC and/or MYCN (Group 2). cfDNA sequencing data was obtained from 776 patients. There were 480/776 (62%) ctDNA-positive patients, with 324 (42%) in Group 1 and an additional 156 (20%) in Group 2 with AR or MYC/MYCN alterations detected. ctDNA-positive patients in Groups 1 and 2 had similarly poor median overall survival (OS) of 25.4 months (95% CI: 21.8-29.0) and 29.7 months (95% CI: 27.3-35.5), respectively, as compared to ctDNA-negative patients who had a median OS of 49.1 months (95% CI: 42.3-53.5). Relative to ctDNA-negative patients, OS was inferior in ctDNA-positive patients in Group 1 (HR 2.3, 95% CI: 1.9-2.9, P AR inhibitors in a contemporary phase III trial.

Study phs003325

RNA-seq study of longitudinal blood cell samples from children at risk of type 1 diabetes

The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (Case subjects) at a young age and matched control subjects.

Study EGAS00001004071

Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): A Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study

UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI). Due to additional sharing restrictions, data from one site can be found in phs003094.

Study phs003066

DirectHRD Enables Sensitive Scar-Based Classification of Homologous Recombination Deficiency (HRD)

Homologous recombination deficiency (HRD)-induced genomic scars are an FDA-approved biomarker for identifying cancers likely to respond to PARP inhibitors. However, detecting HRD scars from blood biopsies has been challenging due to the low tumor content in blood samples. To address this limitation, we developed DirectHRD, a genomic scar-based HRD classifier leveraging whole-genome sequencing (WGS) data for non-invasive blood biopsy testing. DirectHRD was applied to 90 cell-free DNA (cfDNA) samples across four cancer types: breast, ovarian, prostate, and pancreatic. The method achieved an AUC of 0.87 and demonstrated the ability to detect HRD at tumor fractions as low as 1%, offering a tenfold increase in sensitivity compared to state-of-the-art methods.

Study phs003760

Integrative analysis of small cell lung cancer

Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype. We conducted integrated analysis of genome sequencing, transcriptome, and copy number analysis and found an extremely high mutation rate of 7.4±1 protein-changing mutations per million basepairs. Evidence for inactivation of TP53 and RB1 was found in all sequenced cases. Furthermore, we identified recurrent mutations in CREBBP, EP300, and MLL, observed mutations in PTEN, in SLIT2, and EPHA7, as well as focal amplifications of the FGFR1 locus. As a major feature of SCLC we found mutation in histone modifying genes, observed genome alterations that are therapeutically tractable, and provide a framework for identifying biologically relevant genes in the context of a high mutation rate. Peifer et al., 2012, Nature Genetics.

Study EGAS00001000299

WHOLE GENOME SEQUENCING FOR THE CHARACTERIZATION OF CLEAR CELL RENAL CELL CARCINOMA IN VHL PATIENT

To characterize clear cell Renal Cell Carcinoma (ccRCC), we set up a comprehensive multi-omics pilot study on a VHL-ccRCC-patient. Whole Genome Sequencing (WGS) was applied on six ccRCCs, four cysts and one blood DNA sample as germinal control. Raw-data were analyzed with GENomics-DRAGEN platform. We will upload WGS-Data for 11 samples (6 ccRCCs, 4 Cysts, 1 blood).

Dataset EGAD50000000425

Single-cell expression of Hodgkin lymphoma

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

Dataset EGAD00001005739

Fine-mapping clustered GWAS hits enhances the identification of disease risk and protective genetic variants

This dataset contains: 1) Raw FASTQ and BAM files for short reads. Here, DNA libraries were prepared using Nextera Rapid Capture Custom Enrichment kit (Illumina) and paired-end sequenced on a HiSeq2500 (Illumina). 2) Raw FASTQ and BAM files for long reads. Here, DNA libraries were prepared using 1D DNA ligation Sequencing Kit (SQK-LSK109, Oxford Nanopore) and single-end sequenced on a MinION device (Oxford Nanopore).

Dataset EGAD00001006916

shallow WGS of cell free DNA

12.5 ng of cfDNA was used as input for shallow whole-genome sequencing (sWGS), aiming for a coverage of x0.2-0.4-fold. Library preparation was performed using the TruSeq Nano DNA High Throughput Library Prep Kit (Illumina, San Diego, CA, USA) on an automated Hamilton STAR liquid handling system (Hamilton, Germany GmbH, Robotics, Gräfeling, Germany) with dual indexing, and sequencing was performed on the NextSeq500/550 platform (Illumina). The fraction of tumor-derived DNA in cell-free DNA was estimated using the R package ichorCNA.

Dataset EGAD00001009796

Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer using Cell-Free DNA Fragmentomics

The circulating tumor DNA (ctDNA) mutation-based approach shows limited performance in minimal residual disease (MRD) detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, A total of 87 NSCLC patients, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for high-throughput sequencing.

Dataset EGAD00001010300

Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

Dataset EGAD00001010320

Longitudinal genome-wide analysis of progressive chronic lymphocytic leukemia under uniform front-line therapy of pentostatin, cyclophosphamide, and rituximab

Samples from two-center prospective phase 2 clinical trail conducted at Ohio State University (Columbus, OH) and Mayo Clinic (Rochester, MN) were analyzed in 12 cases. All patients had progressive CLL as defined by National Cancer Institute (NCI) Working Group criteria. Patients provided written informed consent for correlative studies according to the Declaration of Helsinki on an institutional review board approved protocol for the collection and use of samples for research purposes from both participating institutions. Eligible patients received a regimen consisting of pentostatin (2 mg/m2), cyclophosphamide (600 mg/m2), and rituximab (375 mg/m2) provided intravenously on day 1 of a 21-day cycle for a maximum of 6 cycles. Responses were assessed by NCI Working Group criteria and included a bone marrow evaluation and two-color flow cytometry 2 months after completion of therapy. Peripheral blood samples from these patients collected longitudinally before (Pre-Baseline), at (Baseline) and after therapy (Relapse) were analyzed for genomic heterogeneity and clonal complexity by high throughput Exome sequencing.

Study phs000794

Polycystic Ovary Syndrome (PCOS) Genetics

PCOS is a complex genetic disease reflecting the interplay of susceptibility genes and environmental factors. The cardinal reproductive feature of the syndrome, hyperandrogenemia, appears to play a direct role in the pathogenesis of the associated metabolic abnormalities. Male as well as female first-degree relatives have reproductive and metabolic phenotypes including increased prevalence rates of type 2 diabetes (T2D), metabolic syndrome (MBS) and other risk factors for cardiovascular disease (CVD). Northwestern University (NU) investigators lead a team that has extensive experience in phenotyping PCOS and in the genetic analysis of complex diseases including genome-wide association study (GWAS). Together with an expert group of collaborators from the Hershey Medical Center, and The University of Chicago, we have conducted a GWAS to identify PCOS susceptibility alleles using a large cohort of extensively and consistently phenotyped PCOS cases. Population controls for this study come from the NUgene project described below. NUgene project: In 2002, Northwestern committed to the development of a DNA repository to serve as a platform for the identification and validation of genotype-phenotype associations that will impact healthcare. The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators.

Study phs000368

Bone Microarchitecture

Osteoporosis affects more than 28 million people in the United States and the lifetime risk for osteoporosis-related morbidity is higher than a woman's combined risk for breast cancer, endometrial cancer and ovarian cancer. Health care expenditures for osteoporotic patients in this country are currently nearly 13 billion dollars per annum and are predicted to increase markedly in the next decades due the aging of the population; therefore, it is important to understand the factors that contribute to bone strength and fracture risk. With the advent of skeletal imaging modalities such as high resolution peripheral quantitative computed tomography (HR-pQCT), it is now possible to study the genetics of more highly refined peripheral skeletal microarchitecture phenotypes. Because these refined phenotypes have not been measured in many cohort studies, this project was a collaborative effort to include almost all the existing data on HR-pQCT of the radius and tibia, and genetics from around the world. Cohorts involved in the discovery included: 1) Framingham Osteoporosis Study, 2) Mayo Clinic cohort; 3) Geneva Retirees cohort; 4) OFELY cohort from Lyon France; 5) STRAMBO cohort from Lyon France; 6) Swedish Male cohorts. Replication cohorts undergoing de novo genotyping include: 1) QUALYOR cohort from Lyon France; 2) CaMOS cohort from Canada. Other than the Framingham cohort and the Swedish male cohorts, all discovery cohorts underwent genome wide genotyping with the Affymetrix Axiom Biobank array that had common variants along with exome content based on the early findings from the Exome Sequencing Project. All genotype data from the discovery cohorts were then imputed using the Haplotype Reference Consortium reference panel. Variants for replication genotyping using the Kasp technology were selected based on novelty compared with previously identified loci using DXA phenotypes, minor allele frequency, underlying LD structure within a locus, and likelihood of a variant being functional as assessed using various algorithms for coding and non-coding variants.    

Study phs002102

Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

Study EGAS00001005405

Gene expression data of 2D duodenum organoids with or without continuous flow

We developed a monolayer culture system for small intestinal organoids, and then placed the culture plate on a rotator to generate a constant flow in the overlay medium. This mechanical stimulation facilitated the formation of villus-like structures from the monolayer of small intestinal organoids. We analyzed gene expression of 2D normal duodenum organoids with or without medium rotation. Total RNA was extracted from organoids with or without a four-day medium rotation, and after 0, 1, 2 or 4 days of medium rotation, and sequenced with HiSeq X Ten (Illumina).

Study JGAS000256

RNA-sequencing of ex vivo exhausted human antigen-specific T cells

Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. To explore new pathways for reinvigoration of anti-tumor immune functions, we developed a human ex vivo exhaustion model by repetitive antigenic stimulation of primary CD8 T cells. This results in T cells that resemble patient-derived T cells in tumors on a phenotypic and transcriptional level. Four human healhy donor CD8+ T cells were isolated, transduced with an NY-ESO-1 TCR lentivirus construct, stimulated in four different conditions (Trested, Ttumor, Tex, Teff) with T2 tumor cells and specific peptides over 12 days. Cells were then sorted for TCR Vbeta 13.1+ (NY-ESO-1 TCR) CD8+ CD3+ CD56- CD4- DAPI- cells. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode (2x51bp) on 2 lanes of an Illumina NovaSeq 6000 flow-cell. FASTQ sequence files were generated with the Illumina RTA version 3.4.4 and Base-calling Version bcl2fastq-2.20.0.422.

Dataset EGAD00001009754

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Patient-Derived Breast Cancer Organoid Study

MutWP5__CRUK_Mutographs_of_Cancer__Breast__Cancer_Mastectomy__Exome_

Investigating_the_genetics_of_immunity_against_Salmonella_in_humans

Genomic Signatures Reveal DNA Damage Response Deficiency in Brain Metastases of Colorectal Cancer

TRIGR collaboration between University of Helsinkin and Children's Mercy Research Institute

RRBS - MBD4-deficient AML

H3Africa TrypanoGEN Main WGS

Martin_Ravenscroft-AUS1

Fecal whole metagenomic shotgun sequencing data.

HV31 - MGI standard short-read sequencing

HV31 - MGI CoolMPS short-read sequencing

Treatment arm information and sample sheet

Genomic and transcriptomic determinants of host susceptibility, protection, and viral mutation in experimental SARS CoV-2 infection: RNA (2025-08-11)

A study of the immune system in patients with peripheral inflammatory neuropathy (CIDP): RNA adult (2025-10-02)

Transcriptomic profiling of the Enteric Nervous System in Hirschsprung Disease (2025-07-31)

MASS_Pilot: Muscle and Ageing Science Study - Collaboration with Wellcome Sanger Institute to characterise skeletal muscle ageing using Human Cell Atlas approaches (2025-07-31)

Additional RNAseq data of metastatic breast cancer samples

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-010

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-009

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-025

Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution

Single-cell RNA sequencing of pediatric Hodgkin Lymphoma to study the inhibition of T cell subtypes

Lebanon_HighCov_seq

Lebanon_LowCov_seq

ChIP-seq for 10 samples

Sequencing data for oesophageal and related samples - Alex Frankell et al (RNA)

Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets

DETECT-A NGS Data Batch 1

iPSC and iNeuron RNAseq, chip-seq and single cell CRISPR activation

Sequencing data for oesophageal / related samples - Kazachenka et al (DNA)

DETECT-A NGS Data Batch 6

DETECT-A NGS Data Batch 4

DETECT-A NGS Data Batch 5

WXS dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

RNA-seq dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Versions 1 and 2 (ROC-Cardiac Epistry 1 and 2-BioLINCC)

FEGA and European GDI: working together to improve human health

Resident memory CD8 T cells persist for years in human small intestine

Comprehensive Genomic Characterization of Translocation Renal Cell Carcinoma

Field studies of Cryptosporidiosis and Enteropathogens in Bangladesh

Human genomic and phenotypic synthetic data for the study of rare diseases

BCR Signaling in human BM PC

Human breast transcriptome analysis

RNA-Seq Brest Patient-derived Tumor Organoids

Common origin and somatic mutation patterns of composite lymphomas and leukemias

RNASeq from PC12 cell lines (derived from PPGL) cultivated under 21% (normoxia) and 1% (hypoxia) oxygen conditions.

Multi-region RNA-Seq data of 10 neuroblastoma cases

eMERGE Network Phase III Clinical Sequencing: eMERGEseq Panel

Molecular Characterization of Prostate Cancer Specimens by Bulk and Single Cell Analysis

Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types (RNAseq)

Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types

WGS of 11 MPNSTs, 7 ANNUBPs and 7 blood and normal tissue controls

H3Africa ACEGID Array Phenotype

CancerSEEK ctDNA FASTQ files

SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

Kidney tumour_DNA (2018-09-19)

Transcription factor binding in human monocyte differentiation

Fecal 16S rRNA gene sequencing

CBD-RAW-SC-ATAC: 10X Single-Cell ATAC

CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) of CLL_24

Raw count matrix for 418 baseline samples

cell-free methylated DNA immunoprecipitation and high-throughput sequencing data for samples from liver transplant recpients with graft pathologies

WXS dataset of Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

Characterizing Individual Cells Obtained from Bone Marrow Biopsies of MPN Patients

ALLELE Consortium Glioblastoma Project

INCLUDE: Down Syndrome Early Post-Natal Brain Multiome

Next_gen_seq_of_eye_cancers

Resequencing_candidate_genes_for_male_spermatogenic_impairment

Single-cell level characterization of B cell depletion and repopulation following rituximab in systemic lupus erythematosus

Privacy Notice for the Account User

MutWP5__CRUK_Mutographs_of_CancerBreastCancer_Mastectomy__Exome_