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• MP-WGS and WES from CCND1-negative MCL

  BAM files from 5 CCND1-negative MCL cases. 4 BAM files corresponded to long insert size Mate Pair-WGS and 3 to WES. In 2 of the cases both technologies were performed.

  Dataset EGAD00001004161

• Whole Exome Sequencing and RNA-Seq to Characterize the Somatic Breast Cancer Landscape Among Latinas in California

  Somatic mutational profiles are increasingly being used to guide treatment. However, there is a dearth of data from non-European populations. To address this gap, we conducted paired tumor/normal whole exome paired-end sequencing and tumor RNA-Seq on 146 breast tumors from 140 Hispanic/Latina (H/L) women with breast cancer. We characterized somatic mutations, copy number alterations, tumor subtypes [Prediction Analysis of Microarray 50 (PAM50)], Catalogue Of Somatic Mutations In Cancer (COSMIC) mutation signatures and expression profiles, and compared them to breast tumors from non-Hispanic White (White) women in The Cancer Genome Atlas (TCGA). Using MutSigCV, we found that the most commonly mutated genes, including TP53, RUNX1, PTEN, PIK3CA, MAP3K1, GATA3, CDH1 and CBFB, were similar to those in breast tumors from non-Hispanic white women. Novel findings were that outliers of BLTP2 (aka KIAA0100) over-expression and COSMIC mutational signature 16 were more common in tumors from H/L women than White women. We also identified that the known germline APOBEC3A/B deletion variant was significantly more common in H/L women and was associated with indigenous American ancestry. Data available through dbGaP will be whole-exome sequencing (WES) and RNA sequencing (RNA-Seq) data, as well as phenotypic data, including estrogen receptor, progesterone receptor, and HER2 receptor status, tumor histology, stage, and grade, and age at diagnosis.

  Study phs003218

• ATAC-seq of a selected group of AML cases

  ATAC-seq data were generated for a number of selected patients to investigate changes in enhancer and promoter regions. ATAC-seq was essentially carried out as described in31. Briefly, prior to transposition the viability of the cells was assessed and 1 × 106 cells were treated in culture medium with DNase I (Sigma) at a final concentration of 200 U ml−1 for 30 minutes at 37 °C. After Dnase I treatment, cells were washed twice with ice-cold PBS, and cell viability and the corresponding cell count were assessed. 5 × 104 cells were aliquoted into a new tube and spun down at 500 × g for 5 minutes at 4 °C, before the supernatant was discarded completely. The cell pellet was resuspended in 50 µl of ATAC-RSB buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2) containing 0.1% NP-40, 0.1% Tween-20, and 1% Digitonin (Promega), and was incubated on ice for 3 minutes to lyse the cells. Lysis was washed out with 1 ml of ATAC-RSB buffer containing 0.1% Tween-20. Nuclei were pelleted at 500 × g for 10 minutes at 4 °C. The supernatant was discarded carefully and the cell pellet was resuspended in 50 µl of transposition mixture (25 µl 2× tagment DNA buffer, 2.5 µl transposase (100 nM final; Illumina), 16.5 µl PBS, 0.5 µl 1% digitonin, 0.5 µl 10% Tween-20, 5 µl H2O) by pipetting up and down six times. The reaction was incubated at 37 °C for 30 minutes with mixing before the DNA was purified using the Monarch PCR & DNA Cleanup Kit (NEB) according to the manufacturer’s instructions. Purified DNA was eluted in 20 µl elution buffer (EB) and 10 µl purified sample was objected to a ten-cycle PCR amplification using Nextera i7- and i5-index primers (Illumina). Purification and size selection of the amplified DNA were carried out with Agencourt AMPure XP beads. For purification the ratio of sample to beads was set to 1:1.8, whereas for size selection the ratio was set to 1:0.55. Purified samples were eluted in 15 µl of EB. Quality and concentration of the generated ATAC libraries were analyzed using the High Sensitivity D1000 ScreenTape Kit (Agilent) and libraries were sequenced paired-end on a NovaSeq (Illumina). ATAC-seq reads were aligned to the human reference genome build hg19 with bowtie2

  Dataset EGAD00001007583

• The double-hit signature identifies double-hit diffuse large B-cell lymphoma with genetic events cryptic to FISH​

  High-grade B-cell lymphomas with MYC and BCL2 and/or BCL6 rearrangements (HGBL-DH/THs) include a group of diffuse large B-cell lymphomas (DLBCLs) with inferior outcomes after standard chemoimmunotherapy. We recently described a gene expression signature that identifies 27% of germinal center B-cell DLBCLs (GCB-DLBCLs) as having a double-hit-like expression pattern (DHITsig) and inferior outcomes; however, only half of these cases have both MYC and BCL2 translocations identifiable using standard breakapart fluorescence in situ hybridization (FISH). Here, 20 DHITsig+ GCB-DLBCLs apparently lacking MYC and/or BCL2 rearrangements underwent whole-genome sequencing. This revealed 6 tumors with MYC or BCL2 rearrangements that were cryptic to breakapart FISH. Copy-number analysis identified 3 tumors with MYC and 6 tumors with MIR17HG gains or amplifications, both of which may contribute to dysregulation of MYC and its downstream pathways. Focal deletions of the PVT1 promoter were observed exclusively among DHITsig+ tumors lacking MYC translocations; this may also contribute to MYC overexpression. These results highlight that FISH fails to identify all HGBL-DH/THs, while revealing a range of other genetic mechanisms potentially underlying MYC dysregulation in DHITsig+ DLBCL, suggesting that gene expression profiling is more sensitive for identifying the biology underlying poor outcomes in GCB-DLBCL.

  Study EGAS00001004285

• Novel CNV contribution to schizophrenia from a genome wide study of 41,321 subjects

  Genomic copy number variants (CNVs) have been strongly implicated in the etiology schizophrenia (SCZ). However, apart from a small number of risk variants, elucidation of the CNV contribution to risk has been difficult due to the very low frequencies of risk alleles, all occurring in less than 1% of patients. We sought to address this obstacle through a collaborative effort unprecedented in psychiatry in which we applied a centralized analysis pipeline to a large SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden is observed in SCZ patients (OR=1.11, P=5.7e-15), and persists after excluding loci implicated in previous studies (OR=1.07, P=1.7e-6). CNV Burden is also enriched for genes associated with synaptic function (OR = 1.68, P = 2.8e-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3e-05). While only previously implicated loci surpass strict genome-wide testing correction, we identify “novel” CNVs (BH-FDR < 0.05) that confer both protective and risk effects on SCZ and are predominantly mediated by non-allelic homologous recombination (NAHR). Our combined data find genome-wide significant support for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2.

  Study EGAS00001001960

• Resistance to anti-EGFR therapy in colorectal cancer

  Monoclonal antibodies targeting the Epidermal Growth Factor Receptor (EGFR), such as cetuximab and panitumumab, have evolved to important therapeutic options in metastatic colorectal cancer (CRC). However, almost all patients with clinical response to anti-EGFR therapies show disease progression within a few months and little is known about mechanism and timing of resistance evolution. Here we performed whole genome sequencing of plasma DNA (plasma-Seq) from patients treated with anti-EGFR therapy. We demonstrate that development of resistance to anti-EGFR therapies is frequently associated with focal amplifications of KRAS, MET, and ERBB2. However, we also show that focal KRAS amplifications can be acquired in tumor genomes of patients under cytotoxic chemotherapy. Furthermore, we provide evidence that specific chromosomal polysomies, such as overrepresentations of 12p and 7p, harboring KRAS and EGFR, respectively, determine responsiveness to anti-EGFR therapy. In contrast, employing ultra-sensitive deep sequencing of genes associated with anti-EGFR resistance, such as KRAS, BRAF, PIK3CA, and EGFR, we did not observe the occurrence of novel, acquired mutations. Overall, whole-genome plasma DNA sequencing represents a non-invasive blood-based surrogate measure of changes in tumors. As such, plasma-Seq enables the identification of novel mutant clones and may therefore facilitate early adjustments of therapies that may delay or prevent disease progression.

  Study EGAS00001000582

• Field Studies of Human Immunity to Amebiasis in Bangladesh (NIH Birth Cohort) and Exploration of the Biologic Basis for Underperformance of Oral Polio and Rotavirus Vaccines in Bangladesh (PROVIDE)

  NIH birth cohort study Amebiasis is a common cause of diarrhea and is associated with malnutrition in grade-school aged children in an urban slum of Dhaka, Bangladesh. Field Studies of Human Immunity to Amebiasis in Bangladesh was designed to determine the contribution of amebiasis to illness in the first 2 years of life when most deaths due to diarrhea occur, and understand the immunologic and genetic factors that protect children from amebiasis. The hypothesis underlying the study is that susceptibility to amebiasis is determined by host innate and acquired immune responses that vary between individuals in part due to: human genetic polymorphisms; environmental influences including malnutrition and concurrent geohelminth infection; and virulence differences among Entamoeba histolytica genotypes. Specific aims proposed in the design of the study were to: a) Measure the incidence of amebiasis and correlate it with human and parasite genetic polymorphisms, immune responses, and environmental factors such as geohelminth infection and malnutrition; b) Test the hypothesis that protective immunity is mediated both by innate immune responses initiated via TLR stimulation as well as by mucosal IgA against the Gal/GalNAc lectin and systemic IFN-γ; c) Test for the association of common genetic polymorphisms in host innate and acquired immune genes with incidence of amebiasis. 629 newborn babies were enrolled and followed regularly through bi-weekly surveillance for diarrheal episodes, anthropometry at 3-month interval until 60 months of age. The infants that were consented for GWAS analysis were genotyped in 3 separate batches at different times, on 3 different arrays. Quality control was performed on the 3 separate data sets and then jointly after merging. Genetic data available on 447 infants together with their phenotype data is made available in this submission PROVIDE (Performance of Rotavirus and Oral Polio Vaccines in Developing Countries) Study Oral polio and rotavirus vaccines are significantly less effective in children living in the developing world. Environmental enteropathy, which is associated with intestinal inflammation, decreased absorption and increased permeability, may contribute substantially to oral vaccine failure in developing country settings. The primary objective of the study was to determine the association of environmental enteropathy with the efficacy of oral polio and rotavirus vaccines in children in Bangladesh. Secondary and exploratory objectives were designed to address other possible causes of oral vaccine underperformance including malnutrition, interference with maternal or breastmilk antibodies, changes in gut microbiota, and genetic susceptibility. The PROVIDE study was structured as a 2x2 clinical trial with a prospective birth cohort enrollment of 700 infants and their mothers in the urban slum of Mirpur, Dhaka, Bangladesh. All children received the full series of Bangladesh's Expanded Program on Immunization vaccines, including oral polio vaccine (OPV) and followed for their first 2 years of life. Half the children were randomized to receive an inactivated polio vaccine (IPV) for their 4th dose at 39 weeks instead of the standard OPV dose. In the other trial, half the infants received the 2-dose rotavirus vaccine (Rotarix) with delayed dosing at 10 and 17 weeks of age. A detailed description of the study design and procedures can be obtained from PROVIDE methods publication: Kirkpatrick B.D., Colgate R.E., Mychaleckyj J.C., Haque R., Dorothy D.M., Carmolli M.P., et al. (2015) Am J Trop Med Hyg 92, 744-751 The Poliovirus trial and results are described in Mychaleckyj et al, Vaccine 2016 The Rotavirus trial and results are described in Colgate et al, Clin Infect Dis 2016 The PROVIDE infants were genotyped on a custom Affymetrix Axiom array (30K SNPs) at the University of Virginia Center for Public Health Genomics; and on a pre-production version of the Illumina MEGA v2 chip at the Wellcome Trust Sanger Institute, UK. The latter genotyping was performed under the auspices of the VaccGene Consortium. Analyses are ongoing to identify variants associated with the included phenotypes. A manuscript describing the genotyping methods and analysis is in preparation for the initial phenotypes. The Infection Malnutrition Bangladesh Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001475 Infection Malnutrition Bangladesh Cohort. phs001476 Amebiasis Immunity phs001478 Polio Rotavirus Vaccines phs001665 Cryptosporidiosis Enteropathogens

  Study phs001475

• Angelman, Rett, Prader-Willi Syndrome Consortium (ARP) Rett Syndrome Natural History Protocol

  This observational study will involve the comprehensive assessment of the clinical features of Rett syndrome with this Rare Diseases Clinical Research Network. A clinical database of 1350 individuals with Rett syndrome including MECP2 mutation status for the purpose of elaborating phenotype-genotype correlations will be established. Eligible participants will be enrolled in the natural history study for 11 years from the 4 clinic sites currently involved with Rett syndrome (BCM, GGC, and UAB, CHB) as well as from the several thousand registrants in the International Rett Syndrome Foundation registry who will be invited to the nearest consortium site involved in Rett syndrome. Potential participants are expected to have had determination of their MECP2 mutation status, but will not be excluded should no mutation be present. All individuals who meet criteria and are currently receiving care from study sites will be invited to participate (N>600). Additional participants will be invited through the assistance of the International Rett Syndrome Foundation (IRSF). All individuals with RS registered with IRSF will be invited to participate in this study via the IRSF website and the IRSF newsletter. Potential participants will be apprised of the participating study sites and invited to contact one of the sites based on feasibility of travel. Inasmuch as the enrollment goal of 1350 participants is 40% of the current IRSF registry, we believe this will be a representative sampling. Bias can certainly occur based on travel requirements, level of interest, and other factors. However, inclusion of such a large sample should minimize sampling bias. No travel expenses will be covered, so it is likely that participants will be those with geographic proximity to Houston, Greenwood, Birmingham, or Boston. From the sample pool described above, the aim is to conduct the observational longitudinal (natural history) study on up to 1350 participants with classic Rett syndrome and variant forms of Rett syndrome, that is, participants who fully meet the established clinical criteria for Rett syndrome and those who meet some but not all of these criteria. All participants expressing MECP2 mutations irrespective of phenotype will be eligible for enrollment. For each of the eight common genetic mutations as well as those with large scale deletions, the prevalence of the following RS characteristics will be estimated for each age category and overall: seizure presence and frequency, ambulation status, scoliosis, ECG abnormality, breathing irregularities while awake, feeding difficulties, growth as measured in percentiles from NCHS standards curves, the presence of osteopenia as evidenced by bone fracture, and the presence of gallbladder disease. Both incidence and prevalence estimates will be made using a combination of data obtained at the regularly scheduled clinical visits and that obtained from the medical history. Incidence estimates will be calculated using time-to-event analyses (e.g., Kaplan-Meier survival curves) with appropriate calculations of standard errors and 95% confidence intervals. Cox proportional hazard regression models will be used to allow control for other factors, and t-tests will be calculated on the coefficients themselves. Appropriate transformations on explanatory variables will be used as deemed necessary in Cox models. Prevalence estimates will be calculated from estimates of proportions with exact confidence intervals. For a sample size of 275, the standard error of the estimate will not exceed 0.03 (3%) and for a sample size of 60, the standard error of the estimate will not exceed 0.06 (6%).

  Study phs000574

• Common Fund (CF) Genotype-Tissue Expression Project (GTEx)

  Lay Description The aim of the Genotype-Tissue Expression (GTEx) Project is to increase our understanding of how changes in our genes affect human health and disease with the ultimate goal of improving health care for future generations. GTEx will create a database that researchers can use to study how inherited changes in genes lead to common diseases. GTEx researchers are studying genes in different tissues obtained from many different people. The GTEx project also includes a study of the GTEx donor consent process - this study will help ensure that the consent process and other aspects of the project effectively address the concerns and expectations of participants in the study. GTEx is a pioneering project that uses state-of-the-art protocols for obtaining and storing a large range of organs and tissues, and for testing them in the lab. Until now, no project has analyzed genetic variation and expression in as many tissues from the same person in such a large population as planned for GTEx. Scientific Description Understanding the role of variation in the human genome is crucial to elucidating genetic contributions to human health and disease. Despite the results of genome-wide association studies (GWAS) documenting strong statistical associations between genetic variation and human traits, the functional role for most of these variants is largely unexplained. Nearly 90% of these GWAS-implicated sites lie outside of protein-coding sequences, suggesting that these variants might regulate gene expression. The goal of the Genotype-Tissue Expression (GTEx) project is to establish a resource database and tissue biobank in which to study the relationship between genetic variation and gene expression and other molecular phenotypes in reference/non-diseased tissues. The ultimate resource will include approximately 960 post-mortem donors with several dozen tissues from each, a resource large enough to study both cis- and trans- gene expression quantitative trait loci (eQTLs). Some tissue will also be banked for additional molecular analyses. To request biosamples, please see the Biobank page for more information. GTEx was initially funded as a 2-year pilot project by the NIH Common Fund (CF) in 2010, and has been scaled up after demonstration of feasibility. The project will collect and analyze RNA levels in many different human tissues and each donor will be characterized for germline genetic variation through dense genotyping arrays and sequencing of either whole exomes or whole genomes. By treating RNA expression levels as quantitative traits, eQTLs will be identified as sites containing genetic variation that correlate with changes in RNA expression. Such eQTLs have been associated with 4%-12% of expressed human genes, and with common complex human diseases, including obesity, atherosclerosis, type 2 diabetes, Crohn's disease, and asthma. Additionally, few studies have examined the tissue specificity of eQTLs. A subset of banked tissue samples will also be analyzed for other molecular phenotypes, such as DNA methylation, DNaseI hypersensitivity sites, and proteomics. The GTEx project will thus serve as a resource database and tissue bank for many future studies, especially for understanding the functional basis of inherited susceptibility to disease. All GTEx releases since Version 5 follow the NIH Genomic Data Sharing (GDS) Policy whereby there are no restrictions on use or publication after release. Additional information about the GTEx Data Release and Publication policy can be found on the GTEx Data Portal at www.gtexportal.org.

  Study phs000424

• Drug development for pediatric cancers: the importance of patient' s genomic data re-use

  Cancer in children is uncommon and the overall prognosis for most pediatric cancers is good. However, while the combined survival rates have improved over the last decades, certain childhood malignancies, such as high-grade gliomas or metastatic sarcomas, still remain incurable in most patients. New strategies for targeting those devastating diseases are imperative, and patient genomic data can become a key asset in the process [1]. The Pediatric Cancer Genome Project’s datasets At EGA, we store over 500 datasets with sequencing data from pediatric cancer patients. A remarkable case is the datasets belonging to the Pediatric Cancer Genome Project (PCGP) from St. Jude Children’s Research Hospital–Washington University (Table 1 - EGAS list). PCGP is an ambitious effort to identify the mutations that drive childhood cancer and find new cures. Those datasets include 600 patients with complete tumor and normal genomes from 15 different tumor types. PCGP datasets have been an important resource for various studies that pooled genomic data from different public and in-house datasets to perform extensive genomic characterizations and publish comprehensive pan-cancer pediatric studies [2],[3]. Other interesting pediatric cancer datasets are from the Pediatric Brain Tumor Consortium, Sickkids or ICGC PedBrain project. How data reuse impacts drug development for pediatric cancers Recently, in October 2024, Nature Communications published a work led by the University of Michigan where authors used data from EGA (PCGP) check the table below as part of their strategy to pursue the identification of new tumor vulnerabilities susceptible to becoming novel therapeutic targets in diffuse midline glioma. Diffuse midline gliomas (DMG) are treatment-resistant and uniformly fatal pediatric brain tumors. The prognosis of this brainstem tumor is dismal with a median overall survival of 9–12 months from diagnosis. In this study, the authors first developed a lab model of the disease and reanalyzed data from the EGA to identify genes potentially linked to tumor severity. This approach revealed involvement of specific metabolic pathways, suggesting new possibilities for therapeutic intervention. In mice, the study shows that the use of statins can improve survival. For a brief overview of the underlying science, diffuse midline gliomas present intratumor heterogeneity with subpopulations of less-differentiated oligodendrocyte precursors and more differentiated astrocytes. Authors established in vitro models to recapitulate both phenotypes and identify metabolic programs in both subpopulations. To determine the clinical relevance, the authors re-used gene expression data from 76 DMG patients identifying a gene signature predicting decreased overall survival. After extensive metabolic characterization of subpopulations, authors defined strategies to target specific metabolic vulnerabilities. Pre-clinical experiments in mice using OXPHOS inhibitors and statins showed a reduction in tumor burden and increased overall survival [4]. In this scenario, the re-use of high-quality patient’s sequencing data appeared as an advantageous strategy to support the clinical relevance of in-vitro and pre-clinical findings. On the other hand, in rare conditions such as childhood cancer, the availability of public datasets and the possibility of pooling data from different sources can be the only way to obtain impactful results that lead to improvements for patients. References Davidoff, A. M. Pediatric Oncology. Seminars in pediatric surgery 19, 225–233 (2010). Gröbner, S. N. et al. The landscape of genomic alterations across childhood cancers. Nature 555, 321–327 (2018). Venu Thatikonda et al. Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers. Nature Cancer 4, 276–289 (2023). Mbah, N. E. et al. Therapeutic targeting of differentiation-state dependent metabolic vulnerabilities in diffuse midline glioma. Nature Communications 15, (2024). Datasets and Studies ID Title Access Policy Year EGAD00001000134 Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAS0000100192 Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas St. Jude Children's Research Hospital - Washington University Pediatric Cancer Genome Project 2017 EGAS00001000575 Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue The hospital for sick children ("SickKids") 2016 EGAD00001000792 Exome sequencing reads of paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAD00001002006 Whole genome sequencing of paediatric glioblastoma in the ICGC PedBrain project ICGC PedBrain project 2016

  Blog drug-development-for-pediatric-cancers

• Download Metadata

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

  Documentation access/download/metadata

• Characterization_of_individual_foci_of_multicentric_multifocal_breast_cancer_using_targeted_next_generation_sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the “quadrants” of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients’ survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Study EGAS00001000407

• Microdissected Pancreatic Cancer Whole Exome Sequencing

  109 micro-dissected pancreatic cancer cases and normal control tissue were subjected to whole-exome sequencing. Microdissection enriches tumor cellularity and enhances mutation calling.

  Study phs000953

• RNASeq of PAX4 KO vs WT in 7 stages of differentiation from human iPSCs to BLC

  Transcriptomes were profiled along with the differentiation from human induced pluripotent stem cell (iPSC) to beta-like cell (BLC) with PAX4 knocked out or not.

  Dataset EGAD00001008582

• Dac for "Altered enhancer-promoter interaction leads to MNX1 expression in pediatric acute myeloid leukemia with t(7;12)(q36;p13)"

  Dac for the data of the manuscript "Altered enhancer-promoter interaction leads to MNX1 expression in pediatric acute myeloid leukemia with t(7;12)(q36;p13)" for Prof. Christoph Plass c.plass@dkfz.de

  Dac EGAC50000000072

• 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

• Massively Multiplex Single-Cell Hi-C of HeLa Cells

  In this study, we developed a massively multiplexed, single-cell Hi-C protocol to study the chromosomal architecture of single HeLa cells.

  Study phs001269

• Whole-exome-sequencing in Motor neuron disease (MND)

  To identify the genetic cause and modifiers of Motor neuron disease (MND), we performed Whole-exome-sequencing of Motor neuron disease (MND) patients.

  Study JGAS000422

• Whole-genome-sequencing and Whole-exome-sequencing in Myopathy

  To identify the genetic cause and modifiers of Myopathy, we performed Whole-genome-sequencing and Whole-exome-sequencing of Myopathy patients.

  Study JGAS000365

• Whole-exome-sequencing in Charcot-Marie-Tooth disease (CMT)

  To identify the genetic cause and modifiers of Charcot-Marie-Tooth disease (CMT), we performed Whole-exome-sequencing of CMT patients.

  Study JGAS000337

• NGS-based targeted exome sequencing of osteosarcoma

  The present study aimed to identify potential genomic markers for the prediction of chemosensitivity in patients with OS using a genomic approach.

  Study JGAS000282

• Clinical and neuroimaging study on preclinical Alzheimer's disease.

  This clinical study aims to discriminate MCI individuals at risk for development of Alzheimer dementia, as well as preclinical AD without clinical manifestations.

  Study JGAS000272

• Single cell transcriptome analysis of breast invasive carcinoma

  We performed single-cell RNA-seq of breast invasive ductal carcinoma to identify the expressional heterogeneity in Luminal subtype and HER2-positive subtype.

  Study JGAS000309

• Genome sequence comparison of human iPS cell lines

  We performed whole genome sequencing analysis on human iPSC lines to understand the impact of genetic variations on clonal epigenetic variations.

  Study JGAS000310

• Elucidation of molecular mechanism of NAFLD-HCC

  We aimed to elucidate the interaction between cancer cells and immune cells in the tumor immune microenvironment of non-viral hepatocellular carcinoma.

  Study JGAS000311

• Department of Human Genetics at Yokohama City University (YCU) — Data Access Committee

  The Data Access Committee at Yokohama City University (Department of Human Genetics) is overseeing controlled access to data for our research manuscripts. Access is granted to bona fide researchers in line with the Data Access Agreement and DUO restrictions.

  Dac EGAC50000000770

• Plasma cell‐free transcriptome profiling in chronic liver disease

  RNAseq data from plasma samples corresponding to a Grand Challenge Programme project to find biomarkers for liver disease, including NAFLD, NASH, Cirrhosis and Hepatocelullarcarcinoma. A template of the DTA and DAA files is available in the following zenodo repository https://doi.org/10.5281/zenodo.19047046.

  Dac EGAC50000000360

• Clonal hematopoiesis in metastatic urothelial and renal cell carcinoma

  This study aimed to determine the prevalence and clinical relevance of clonal hematopoiesis in metastatic urothelial and renal cell carcinoma.

  Study EGAS50000000870

• Tumor mutational landscape in individuals with CMMRD

  Whole exome sequencing data from the tumors (n=16) of individuals with constitutional mismatch repair deficiency. Data was aligned to GRCh38.

  Study EGAS50000000081

• scRNA-seq of monochorionic dizygotic twin chimera PBMC

  Single cell RNA-seq of PBMC of monochorionic dizygotic twin chimeras. 10x chromium v3.1 was used to generate barcoded scRNA library.

  Study EGAS50000000097

• WES of Adenoid Cystic Carcinoma Treated with Axitinib and Avelumab

  To determine potential mutational biomarkers of response to combination axitinib and avelumab, whole exome sequencing was performed on 24 adenoid cystic carcinomas treated with combination axitinib and avelumab with paired normal samples.

  Dataset EGAD50000002467

• 16S rRNA-Seq of rectal mucus from patients suspected to have colorectal cancer

  Metataxonomic sequencing data targeting the 16S rRNA gene hypervariable regions V3 and V4 on 545 rectal mucus samples from patients suspected to have colorectal cancer and healthy controls.

  Dataset EGAD50000001803

• Single-cell genotype-to-phenotype (scG2P) of normal esophageal epithelium

  Single-cell genotype-to-phenotype (scG2P) of normal esophageal epithelium, based on targeted DNA genotyping of mutation hot spots and targeted RNA capture.

  Dataset EGAD50000002066

• Spatial transcriptomics prostate cancer

  Spatial transcriptomic characterization of human fresh frozen prostate cancer and non-malignant regions from the same patient. 100 micron thick sections were made from the biopsies, adjacent to snRNA sequencing, and subjected to 10x Genomics Visium ST analysis.

  Dataset EGAD50000001634

• miRNA

  miRNA Sequencing of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.

  Dataset EGAD50000001532

• Sutherland Nine Raw Sequencing Data

  These Fastq-files contain the raw sequencing output from our two sequencing experiments (Shotgun and Capture). All libraries with "*SG*" refer to Shotgun genomes, while all files containing "*TF*" refer to 1240K capture data.

  Dataset EGAD50000001417

• WGS of human colorectal cancer organoid exposed to genotoxic pks+ E. coli

  Organoid cultures were exposed to different E.Coli strains and a dye control. In total 25 organoid cultures were whole-genome sequenced using the Novaseq6000 platforms. The data is deposited as .bam format.

  Dataset EGAD50000000304

• Tumor reactive γδ T cells contribute to a complete response to PD-1 blockade in a Merkel cell carcinoma patient

  Single cell RNA and TCR sequencing of γδ T cells FACS sorted from peripheral blood of two Merkel cell carcinoma patients

  Dataset EGAD50000000137

• Methylation Array of pre- and post-5ZA-treated head and neck cancer patients refractory to anto-PD-1 therapy

  Illumina MethylationEpic Beachip data generated from tissue samples collected from head and neck cancer patients refractory to anti-PD-1 therapy, collected before and after the 5AZA treatment

  Dataset EGAD00010002718

• Peripheral blood DNA methylation data from CD patients prior to vedolizumab treatment from John Radcliffe Hospital

  DNA methylation validation data as obtained using the Illumina HumanMethylation EPIC BeadChip array (V1) on peripheral blood from CD patients at the John Radcliffe Hospital, Oxford, UK prior to vedolizumab treatment

  Dataset EGAD00010002652

• Peripheral blood DNA methylation data from CD patients prior to and during vedolizumab treatment from AmsterdamUMC

  Longitudinal DNA methylation discovery data as obtained using the Illumina HumanMethylation EPIC BeadChip array (V1) on peripheral blood from CD patients at the AmsterdamUMC prior to and during vedolizumab treatment

  Dataset EGAD00010002651

• Peripheral blood DNA methylation data from CD patients prior to ustekinumab treatment from John Radcliffe Hospital

  DNA methylation validation data as obtained using the Illumina HumanMethylation EPIC BeadChip array (V1) on peripheral blood from CD patients at the John Radcliffe Hospital, Oxford, UK prior to ustekinumab treatment

  Dataset EGAD00010002650

• Peripheral blood DNA methylation data from CD patients prior to and during ustekinumab treatment from AmsterdamUMC

  Longitudinal DNA methylation discovery data as obtained using the Illumina HumanMethylation EPIC BeadChip array (V1) on peripheral blood from CD patients at the AmsterdamUMC prior to and during ustekinumab treatment

  Dataset EGAD00010002649

• NSCLC PC9 erlotinib RAF1 study

  This Data Access Committee (DAC) oversees the controlled access to genomic sequencing data generated by Prof. Hoon Kim's laboratory at Sungkyunkwan University. The DAC is responsible for reviewing data access requests related to cancer genomics research, including the study on RAF1 ecDNA-mediated erlotinib resistance in NSCLC models.

  Dac EGAC50000001001

• Medulloblastoma-associated DDX3 variant selectively alters the translational response to stress

  Medulloblastoma-associated DDX3 variant selectively alters the translational response to stress

  Dataset EGAD00001001210

• Use of deep sequencing to detect clonal mutations in sun exposed human epidermis - whole genome

  Deep sequencing of two skin biopsies to study the landscape of somatic mutations in human adult tissues.

  Dataset EGAD00001001123

• Matched WXS of 147 lung cancer patients treated with immunotherapy

  This data includes whole exome sequencing of matched normal-tumor samples of patients who have received immunotherapy. '-1' refers to matched normal sample and '-2' refers to matched tumor sample.

  Dataset EGAD00001005211

• DESIGN-NKI low coverage WGS

  Low-coverage whole genome sequencing data of 37 HPV-negative HNSCC specimens from patients treated at The Netherlands Cancer Institute. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for WGS to a depth of approx. 0.5X.

  Dataset EGAD00001005718

• DESIGN-VUMC low coverage WGS

  Low-coverage whole genome sequencing data of 37 HPV-negative HNSCC specimens from patients treated at the VU Medical Centre, Amsterdam. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for WGS to a depth of approx. 0.5X.

  Dataset EGAD00001005719

• GATCI whole exome germline variants

  Exome sequences were aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK Haplotype Caller to generate germline variant calls. Variant calls are in VCF format. Details for the call can be found in the VCF header

  Dataset EGAD00001005916

• GATCI whole exome somatic variants (MuTect)

  Exome sequences were aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK/MuTect, to generate somatic variant calls. Somatic variant calls are in VCF format. Details for the mutect call can be found in the vcf header.

  Dataset EGAD00001005917

• GATCI whole exome somatic variants (SomaticSniper)

  Exome sequences were aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK/SomaticSniper, to generate somatic variant calls. Somatic variant calls are in VCF format. Details for the mutect call can be found in the vcf header.

  Dataset EGAD00001005918

• Rucaparib in patients presenting a metastatic breast cancer

  Whole genome sequencing was performed on 24 patients (tumor DNA paired to constitutional DNA). WGS libraries were subjected to paired-end (2 x 100 bp) sequencing on NovaSeq (Illumina). The 96 files are in FASTQ format.

  Dataset EGAD00001006458

• Targeted sequencing of candidate regions on chromosome 22q predisposing to multiple schwannomas

  Targeted sequencing of candidate regions on chromosome 22q predisposing to multiple schwannomas

  Dataset EGAD00001008271

• DNA-seq from plasma of 14 liver transplantation patients

  We performed DNA sequencing on the plasma of 14 liver transplantation patients to study the liver DNA in the plasma.

  Study EGAS00001003116

• Epigenomic data of Human muscle stem cell

  To profile the epigenomic landscape of Human muscle stem cell, ChIP-seq of histone marks , WGBS and RNA-seq data were generated.

  Study EGAS00001006159

• The molecular landscape of colorectal cancer reveals genetic mutations.

  We performed whole-exome sequencing of tumor samples and adjacent normal mucosae from 46 patients to characterize the genetic alterations in China.

  Study EGAS00001001893

• ImmunoAgeing_Colonies

  Using patterns of shared mutations between haematopoietic stem cells in 14 individuals with clonal haematpoiesis, we aim to determine the timing of somatic mutation acquisition.

  Study EGAS00001003933

• The molecular landscape of colorectal cancer （17 cases）

  We performed whole-exome sequencing of tumor samples and adjacent normal mucosae from 17 cases to characterize the genetic alterations in china.

  Study EGAS00001002174

• Osteosarcoma_RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Study EGAS00001000615

• The molecular landscape of colorectal cancer （5 cases）

  We performed whole-exome sequencing of tumor samples and adjacent normal mucosae from 5 patients to characterize the genetic alterations in china.

  Study EGAS00001002374

• Epigenome-wide association study of cocaine use disorder in postmortem human brain tissue

  We aimed to identify cocaine use disorder associated DNA methylation alterations in the Brodmann Area 9 brain region.

  Study EGAS00001006826

• Lung_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Lung cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Study EGAS00001000148

• Microdissection_sequencing_of_normal_human_prostate

  Histology sections from pathologically benign human prostates were prepared and microdissections retrieved from Laser-Capture Microdissection are submitted to low-input whole-genome sequencing.

  Study EGAS00001003049

• Fungal infection in neural tissue from Amyotrophic Lateral Sclerosis

  The study shows that fungus infection, isolated from neural tissue, can be a risk factor to develop Amyothophic lateral sclerosis (ALS).

  Study EGAS00001002473

• Benchmarking DIA-type Proteomics Using Large-Scale Inter-Patient Heterogeneity Dataset

  Benchmarking Proteomics Quantitation in DIA-type data using real patient material to create a benchmark dataset comprising inter-patient heterogeneity

  Study EGAS00001005589

• Exome_sequencing_of_Non_syndromic_Congenital_Heart_Defects

  Exome sequencing of ~1,800 patients with non-syndromic Congenical Heart Defects (CHD) to identify genes enriched for damaging rare variants that increase risk of CHD

  Study EGAS00001002522

• BS-seq in plasma of CRC patients

  We performed whole genome bisulfite sequencing of plasma DNA in 11 colorectal cancer patients to study the colonic DNA in plasma.

  Study EGAS00001003117

• GEL_WGS_Comparison

  These samples are to be analysed with the CGP Developed cancer panel and the results will be compared with WGS data from 4 different comercial providers.

  Study EGAS00001000649

• WGS_of_AML_during_PARPi_therapy

  We will require WGS on Illumina X10 machines of three samples, along with storage and computational power to perform the relevant analysis.

  Study EGAS00001002274

• The genomic landscape of acute lymphoblastic leukemia with intrachromosomal amplification of chromosome 21

  Use single cell whole genome sequencing data from one iAMP21 patient SJBALL021901 to study the clonal evolution of iAMP21.

  Study EGAS00001006796

• 9 samples variant calling data

  This dataset comprise results of mutect2 variant calling in vcf format on 9 samples of rosette forming brain tumors (5 with paired normal tissue and 4 without). Only variants specific to the tumor where kept to comply with patients consent.

  Dataset EGAD00001009266

• Single-cell mRNA-sequencing to generate a transcriptomic atlas of RMS

  Single-cell mRNA-sequencing to generate a transcriptomic atlas of soft tissue sarcoma tumors

  Dataset EGAD00001009385

• RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

  RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

  Dataset EGAD00001009799

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

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

  Dataset EGAD00001011373

• 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

• Single-cell DNA sequencing reveals a high incidence of chromosomal abnormalities in human blastocysts

  Single cell DNA sequencing data from human preimplantation stage embryos from embryonic day 5 to 8, donated for research

  Study EGAS50000001913

• In vitro mutational load

  Clonally expanded human pluripotent and adult (liver + intestine) stem cell clones were subjected to whole genome sequencing to determine the mutational impact of in vitro culture

  Dataset EGAD00001004104

• macIDR validation data

  RNA-seq of 24 M-CSF differentiated human peripheral monocyte-derived macrophages (MDMs) activated with short exposure (3hours) to LPS, or long exposure (24 hours) to LPS, LPS with IFNγ, IFNγ, IL-4, IL-10, and dexamethasone.

  Dataset EGAD00001004584

• Cancer Risk Estimates Related to Susceptibility Genes (CARRIERS)

  The CARRIERS study utilized custom amplicon-based variant screening of known cancer predisposition genes in germline DNA from breast cancer cases and age matched unaffected controls taken from predominantly cohort-based breast cancer case-control studies to establish the risks of breast cancer associated with pathogenic variants in these genes.

  Study phs002820

• Application of targeted long-read methylation sequencing to dissected breast cancer tissues

  Four regions defined by pathological view were dissected from fresh frozen sections of breast cancer tissue using Millisect system. DNA and RNA extracted from the dissected tissues were applied to short-read WGS, short-read RNA-seq, short-read EM-seq, and targeted long-read methylation analysis t-nanoEM.

  Study JGAS000758

• A distinct monocyte cellular state links systemic immune dysregulation to pulmonary impairment in long COVID

  This is an independent cohort of Long COVID patients recruited from a rehabilitation centre. These patients had Long COVID from 8 months to more than 2 years since their acute COVID-19 disease. PBMC from these patients were collected and single cell transcriptomics dataset was generated.

  Study EGAS50000001216

• Multiple paralogues and recombination mechanisms contribute to the high incidence of 22q11.2 Deletion Syndrome

  To enable haplotype-specific assembly and rearrangement mapping in LCR22 clusters, we combined fiber-FISH optical mapping with whole genome (ultra-)long read sequencing or rearrangement-specific long-range PCR on 254 duos families (22q11.2DS patient and parent-of-origin) comprising several different LCR22-mediated rearrangements.

  Study EGAS50000000601

• Long-term Survival Update and Extended RAS Mutational Analysis of the CAIRO2 Trial: Addition of Cetuximab to CAPOX/Bevacizumab in Metastatic Colorectal Cancer

  Here we present updated survival of the CAIRO2 trial and assessed whether the addition of anti-EGFR to anti-VEGF therapy could still be an effective treatment option for patients with extended RAS/BRAF wildtype and left-sided metastatic colorectal cancer (mCRC).

  Study EGAS50000000775

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

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

  Dataset EGAD50000001871

• Genetically unique biospecimens derived from individuals with or without Type 1 Diabetes

  In this dataset, samples correspond to pools of genetically unique biospecimens derived from individuals with or without Type 1 Diabetes. Each sample alias contains all the DNA test numbers for that pool. Each experiment corresponds to scmxGEX (multiome RNA gene expression), scmxATAC (multiome ATAC sequencing), scRNA (single cell RNA sequencing), scATAC (single cell ATAC sequencing) for each pool. Runs link the appropriate fastq files to each experiment. Deconvolution using genetic information is required for single sample-based testing.

  Dataset EGAD50000001257

• Single-cell RNA-Seq analysis of thymic ILC1 progenitors and NK cell differentiation This analysis involved a multiplexed sequencing run to study thymic innate lymphoid cells (ILCs) and NK progenitors. The generated data requires a demultiplexing file to separate and identify the individual sample tags for downstream analysis.

  This dataset contains multiplexed single-cell RNA sequencing (scRNA-seq) data from human thymic tissue, focusing on ILC1 progenitors and NK cell differentiation. The data were generated using the BD Rhapsody system and sequenced on the Illumina NovaSeq S4 platform. A demultiplexing file is required to assign sample identities.

  Dataset EGAD50000001157

• CITEseq data of Reactive Lymph Nodes

  Mononuclear cells were isolated as cell suspensions by dissociation in a BD Horizon™ Dri Tumor & Tissue Dissociation Reagent (BD Biosciences) using a gentleMACS dissociator (Miltenyi Biotec). A totalseq-C antibody cocktail (Biolegend) was used, and the cell suspensions were diluted to a concentration of 1,000 cells/μL. Library sequencing was performed using the NovaSeq6000 System (Illumina). The FASTQ files were aligned to the 10x provided reference genome using 10x Genomics Cell Ranger software v7.1.0 to create unique molecular identifier count tables of gene expression of the samples.

  Dataset EGAD50000000538

• Chromatin profiling of baseline and Notch inhibitor treated HCC PDX model

  We generated chromatin accessibility profiles for anti-Notch2 (n=3) and anti-gD (n=3) treated LIV78 tumors. Tumors were isolated, snap frozen in liquid nitrogen and stored at -80C. Tumor tissue was pulverized using a Covaris CP02 CryoPrep Pulverizer. Flash frozen pulverized tumor samples were sent to Active Motif to perform the ATAC-seq assay. Resulting material was quantified using the KAPA Library Quantification Kit for Illumina platforms (KAPA Biosystems), and sequenced with PE42 sequencing on the NextSeq 500 sequencer (Illumina) to produce FASTQ sequencing files.

  Dataset EGAD50000000735

• WES data from 438 tumor/germline samples with non muscle invasive bladder cancer

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). This dataset contains 876 BAM files corresponding to the full WES dataset. Tumor and matched germline DNA were sequenced to a mean coverage of 132x (35x-338x) and 128x (31x-302x), respectively.

  Dataset EGAD50000000730

• Multiple paralogues and recombination mechanisms contribute to the high incidence of 22q11.2 Deletion Syndrome

  The 22q11.2 deletion syndrome (22q11.2DS) is the most common microdeletion disorder. Why the incidence of 22q11.2DS is much greater than that of other genomic disorders remains unknown. Short read sequencing cannot resolve the complex segmental duplications (SDs) to provide direct confirmation of the hypothesis that the rearrangements are caused by non-allelic homologous recombination between the low copy repeats on chromosome 22 (LCR22s). To enable haplotype-specific assembly and rearrangement mapping in LCR22 clusters, we used whole genome (ultra-)long read sequencing of 9 duos (patients and parent of origin).

  Dataset EGAD50000000855

• Bulk Iso-Seq from brain tissue and exosomes isolated from brain tissue using long-read PacBio sequencing of poly-adenylated transcripts

  Human brain sEVs were isolated from postmortem human brain tissue. RNA was extracted from both the source brain tissue and sEVs and prepared for long-read sequencing. cDNA was sequenced on the PacBio Sequel II. The data provided have undergone processing using the tool ccs (v6.0.0) to generate circula consensus reads. For further processing, it is recommended to follow the guidelines at https://isoseq.how/, starting with using lima to remove cDNA primers.

  Dataset EGAD50000000043

• Cambridge_INTERVAL_SomaLogic_pQTLs

  This dataset contains four data files relating to the Cambridge Interval SomaLogic pQTL study to go with the corresponding genetic data: (1) Genome-wide pQTL summary associations for each analyte. (2) Mapping table for the genetic variants analysed - containing rsID, position and allele information. (3) Normalised quantitative readouts for each analyte, along with covariates used for the pQTL analysis. (4) Table of SOMAmer analytes mapped to their protein targets. Please see the readme file in the dataset for more information.

  Dataset EGAD00001004080

• Congenital anosmia 1

  Congenital anosmias can be complete (the lack of a sense of smell) or specific (the inability to detect specific smells). To date, only a single recessive gene underlying complete anosmia has been identified. Here we sequenced the exomes of 10 individuals from a single family, including three with complete anosmia, across three generations to identify the genetic basis of congenital anosmia in this family. 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 EGAD00001002210

• Gene expression profile of mesothelial-derived carcinoma-associated fibroblasts

  RNA-sequencing was carried out on ascetic fluid-isolated mesothelial cells from low-grade serous ovarian cancer patients, high-grade serous ovarian cancer patients, chemotherapy-treated high-grade serous ovarian cancer patients and control mesothelial cells obtained from non-oncologic patients to identify differentially expressed genes associated to mesothelial-to-mesenchymal transition process. The dataset contains 18 samples: - Control mesothelial cells: 4 samples - Group 1, high-grade serous ovarian cancer patients: 3 samples - Group 2, chemotherapy-treated high-grade serous ovarian cancer patients: 5 samples - Group 3, low-grade serous ovarian cancer patients: 6 samples

  Dataset EGAD00001005133

• RNA sequencing of CD8 T cells from melanoma patients prior to and during checkpoint immunotherapy and untreated healthy controls

  We are interested in inter-individual variation in transcriptional response to immune checkpoint blockade. We have analysed poly A purified RNA expression from CD8 T cells (297 transcriptomes in total) isolated from metastatic melanoma patients (n=106) prior to and during treatment with either single agent (Pembrolizumab) or combination (Ipilimumab/ Nivolumab) immune checkpoint blockade. We compare expression at different stages of treatment and additionally contrast this with that from healthy controls (n=68).

  Dataset EGAD00001005973

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

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

  Dataset EGAD00001008091

• Dataset for identification of the dismal subtype of B-ALL with dysregulation of CDX2 and UBTF

  WGS (tumor and germline samples) was performed to identify structural variants in the UBTF/CDX2 subgroup. RNA-seq was performed to detect gene fusion in the UBTF/CDX2 subgroup. HiChIP was performed to investigate 3D chromatin architecture and enhancer landscapes of representative patient samples and cell lines harboring Type I and II FLT3-PAN3 deletions and amplifications.

  Dataset EGAD00001008416

• Application of short-RNA-seq in post-mortem human hippocampi from the Calgary Brain Bank (CBB) to assess transcriptome-wide deregulation in processing of SINE Alu RNAs in Alzheimer’s disease

  Here, we investigate through short-RNA_seq in human hippocampi from the Calgary Brain Bank (CBB) whether Alu RNAs are processed in human brains, and whether their processing ratio is deregulated in brains of AD patients compared to healthy aging individuals.

  Study EGAS00001004973

• WGBS analysis corresponding to representative cases of iBCP-ALL patients

  In this study, we performed whole genome bisulfite sequencing (WGBS) to characterize the methylome of representative iBCP-ALL cases from the Interfant study discovery cohort, including 2 pools of B-cell progenitors from healthy donors, 2 MLL-AF4+, 2 MLL-AF9+ and 2 non-MLLs from iBCP-ALL patients.

  Study EGAS00001003650