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• SGI Single-cell team GC Data Access Committee

  Dac EGAC00001001420

• Long-read trio sequencing Team Data Access Commitee

  Dac EGAC00001001532

• UZ Ghent Prostate Cancer Team Data Access Committee

  Dac EGAC00001001608

• Single-cell Omics Glioma Team Data Access Committee

  Dac EGAC00001002256

• Signal Transduction Team ICR (2011) Data Access Committee

  Dac EGAC00001000040

• INSERM U981 Team : Genomics of Non-Melanoma Skin Cancer

  Dac EGAC00001001644

• Single-cell Multiomics Clonal Hematopoiesis Team Data Access Committee

  Dac EGAC00001002735

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001003071

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001003083

• WGS of Multiple Myeloma/MGUS/SMM cases (germline) - VCF files (SNPs)

  WGS - PCR-free library preparation (whole blood gDNA), paired-end (2x100bp) sequencing on DNBseq sequencing platform (BGI) Number of samples: 26

  Dataset EGAD50000001800

• WES dataset of a TIL-ACT metastatic melanoma cohort

  Whole-exome sequencing (WES) data from 13 patients with metastatic melanoma in a TIL-ACT cohort, generated to characterize tumor genomics and neoantigen landscapes relevant to adoptive T cell therapy.

  Dataset EGAD50000001731

• NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica

  This administrative supplement to the project, "The Genetic Epidemiology of Asthma in Costa Rica" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.

  Study phs000988

• All counts

  This dataset is the expression profiling by high throughput sequencing, including all counts of genes for all samples in two groups. It includes 26 samples totally (Lean healthy group includes 12 samples: s001/SR01_Bright, s002/SR01_Dim, s004/SR02_Bright, s005/SR04_Dim, s006/SR04_Bright, s007/SR05_Dim, s008/SR05_Bright, s009/SR06_Bright, s011/SR07_Dim, s012/SR07_Bright, s013/SR08_Bright, s014/SR08_Dim; DM2 group includes 14 samples: s015/SR201_Bright, s017/SR202_Bright, s018/SR202_Dim, s019/SR203_Bright, s020/SR203_Dim, s021/SR204_Bright, s022/SR204_Dim, s023/SR205_Dim, s025/SR206_Dim, s026/SR206_Bright, s027/SR207_Dim, s028/SR207_Bright, s029/SR208_Bright, s030/SR208_Dim). It is a TAB file.

  Dataset EGAD50000001715

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001002266

• scRNA-seq analysis of HGSC tumors, including immune TME, before and after NACT

  Gene expression profiles of single cells from 26 tumor and ascites samples samples from 17 patients

  Dataset EGAD50000000862

• Ancient genomes reveal insights into ritual life at Chichén Itzá

  To better understand the origin and biological relationships of the sacrificed children from Chichén Itzá to each other and to present-day inhabitants of the region, here we used a combined bioarchaeological and genomics approach to investigate 64 subadults interred within a chultún near the Sacred Cenote and compare them to 68 present-day Maya inhabitants of the nearby town of Tixcacaltuyub, as well as to other available ancient and contemporary genetic data from the region. The community of Tixcacaltuyub has been collaborating with our research team for many years, and their perspectives informed the development of this project.

  Study EGAS50000000296

• “Human population genetics” team (Muséum national d’Histoire naturelle, Paris, France)

  Dac EGAC00001000147

• Cancer Biomarkers team at The ICR DAC

  DAC for Cancer Biomarkers

  Dac EGAC50000000200

• TAKEDA DAC

  Team of TAKEDA DAC: Members: - Amit - Vinu - Jay - Sachin

  Dac EGAC50000000779

• The Dutch retinoblastoma research team from the VU University medical center

  Dac EGAC00001000431

• Spatiotemporal single cell transcriptomic analysis of human gut macrophages team commitee

  Dac EGAC00001002166

• DAC - U1085 Team Physiology and Physiopathology of the urogenital tract (INSERM / IRSET)

  Dac EGAC00001002830

• H3Africa H3AChipDesign TrypanoGEN1

  26 samples from Cameroon generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004393

• Location and Function of NSun2-Mediated Cytosine-5 Methylation in RNA and its Effect on Translation

  Mutations in the cytosine-5 RNA methyltransferase NSun2 can cause neurodevelopmental disorders and symptoms commonly found in patients with Dubowitz-like syndrome. Some tRNAs are known to be methylated NSun2, however the occurrence of cytosine-5 methylation (m5C) in other RNA biotypes is still under debate. Location in RNA and function of m5C has not been studied yet. This study is aimed at identifying new m5C methylated RNA biotypes, as well as the location at specific structures or sequences and the ultimate biological function. The impact of the loss of NSun2-mediated methylation is also determined by comparing gene expression data with the global cytosine-5 RNA methylome in Dubowitz-like syndrome patients. We also use ribosomal profiling to assess the impact of the loss and rescue of Nsun2-mediated cytosine-5 RNA methylation on translation rates and ribosome occupancy.

  Study phs000645

• Center for Common Disease Genomics [CCDG] Neuropsychiatric: Autism Spectrum Disorder (ASD) – Whole Exomes

  The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of 1) undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases, 2) understanding how best to design rare variant studies for common disease, and 3) developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The goal of the Autism Spectrum Disorder (ASD) program is to work together to utilize dramatic new advances in DNA sequencing technology to reveal the genetic architecture of autism through comprehensive examination of the exotic sequence of all genes.

  Study phs002502

• Presence of rare potential pathogenic variants in subjects under 65 years old with very severe or fatal COVID‑19

  Rare variants affecting host defense against pathogens could be involved in COVID‑19 severity and may help explain fatal outcomes in young and middle‑aged patients. Our aim was to report the presence of rare genetic variants in certain genes, by using whole exome sequencing, in a selected group of COVID‑19 patients under 65 years who required intubation or resulting in death (n = 44). To this end, different etiopathogenic mechanisms were explored using gene prioritization‑based analysis in which genes involved in immune response, immunodeficiencies or blood coagulation were studied. We detected 44 different variants of interest, in 29 different patients (66%). Some of these variants were previously described as pathogenic and were located in genes mainly involved in immune response. A network analysis, including the 42 genes with candidate variants, showed three main components, consisting of 25 highly interconnected genes related to immune response and two additional networks composed by genes enriched in carbohydrate metabolism and in DNA metabolism and repair processes. In conclusion, we have detected candidate variants that may potentially influence COVID‑19 outcome in our cohort of patients. Further studies are needed to confirm the ultimate role of the genetic variants described in the present study on COVID‑19 severity.

  Study EGAS00001006372

• ATAC-seq

  ATAC-seq data for 26 CLL samples (7 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005967

• Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genome

  Mutation in the germline is the ultimate source of genetic variation, but little is known about the influence of germline chromatin structure on mutational processes. Using ATAC-seq, we profile the open chromatin landscape of human spermatogonia, the most proliferative cell-type of the germline, identifying transcription factor binding sites (TFBSs) and PRDM9-binding sites, a subset of which will initiate meiotic recombination. We observe an increase in rare structural variant (SV) breakpoints at PRDM9-bound sites, implicating meiotic recombination in the generation of structural variation. Many germline TFBSs, such as NRF, are also associated with increased rates of SV breakpoints, apparently independent of recombination. Singleton short insertions (>=5 bp) are highly enriched at TFBSs, particularly at sites bound by testis active TFs, and their rates correlate with those of structural variant breakpoints. Short insertions often duplicate the TFBS motif, leading to clustering of motif sites near regulatory regions in this male-driven evolutionary process. Increased mutation loads at germline TFBSs disproportionately affect neural enhancers with activity in spermatogonia, potentially altering neurodevelopmental regulatory architecture. Local chromatin structure in spermatogonia is thus pervasive in shaping both evolution and disease.

  Study EGAS00001005366

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

  DAC for RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

  Dac EGAC50000000627

• Refractory Classic Hodgkins Lymphoma (cHL) sWGS

  Associated with the study: Blood-based Monitoring of Relapsed/Refractory Hodgkin Lymphoma Patients Predict Responses to Anti-PD-1 Treatment. 26 ctDNA Samples from 4 patients followed longitudinally. sWGS performed for copy number aberration (CNA) analysis.

  Dataset EGAD50000001163

• DAC for Hungarian human exome team (Department of Medical Biology, University of Szeged, Hungary)

  Dac EGAC00001000838

• RNAseq of ribosomal footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Dataset EGAD00001001930

• Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

  Gene expression profiles of single cells from 26 chemo-naïve and IDS tumor tissue and ascites samples from 17 HGSC patients

  Study EGAS50000000607

• dataset1

  Contains 14 control samples and 26 case samples.

  Dataset EGAD00001008576

• BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001513

• High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 26 individuals.

  Deposited here are whole-genome sequencing data for 26 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence coverage is 118x for DCIS samples and 41x for matched-normals. Matched-normal samples are from blood. Sequencing was performed on an Illumina HiseqX. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

  Dataset EGAD50000002237

• RNA-Sequencing and Somatic Mutation Status of Adrenocortical Tumors: Novel Pathogenetic Insights

  To investigate the relationship between transcriptome profile and genetic background in a large series of adrenocortical tumors and to identify new potential pathogenetic mechanisms, we performed transcriptome profiling by high-throughput sequencing. We collected snap-frozen tissue from patients with adrenocortical tumors (n = 59) with known genetic background: 26 adenomas with Cushing syndrome, 17 adenomas with mild autonomous cortisol secretion, 9 endocrine-inactive adenomas, 7 adrenocortical carcinomas. Additionally, we sequenced 4 control samples.

  Study EGAS00001004533

• Sequencing files for "Transcriptional Mechanisms of Resistance to Anti-PD-1 Therapy"

  Files from whole exome sequencing of 26 tumors and two matched normals from one melanoma patient. The 26 tumors include the untreated primary, cutaneous metastases and distant metastases to internal organs.

  Dataset EGAD00001003200

• WES of melanoma tumours prior to combined immune checkpoint blockade treatment.

  Paired melanoma tumor and normal (PBMC) WES data from a cohort of 26 patients subsequently treated with combined immune checkpoint blockade.

  Dataset EGAD00001005941

• Center for Common Disease Genomics [CCDG] - Autoimmune: Inflammatory Bowel Disease (IBD) Exomes and Genomes

  The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of: undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases; understanding how best to design rare variant studies for common disease; developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The overarching aim of the Inflammatory Bowel Disease (IBD) program is to define the full allelic spectrum of protein-altering variation in genes associated to IBD, and assess their role in both Crohn's Disease (CD) and Ulcerative Colitis (UC) risk. The whole genome sequencing data generated here is comprised of samples from US-based diverse populations including African American, Puerto-Rican, Caribean and Cuban origins.

  Study phs001642

• MSI-Exome-DAC Team Microsatellites Instability and Cancer, INSERM Hospital Saint-Antoine, Paris 12, France Carte d'identité des tumeurs, French league against cancer, Paris France

  Dac EGAC00001000665

• endogene.bio

  The Endogene Bio Data Access Committee oversees and manages access to controlled genomic and clinical datasets deposited by the Endogene Bio research team.

  Dac EGAC50000000786

• Long-read data (PacBio)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006597

• L1 Retrotransposon sequencing in Cocaine Use Disorder - Study 1

  Cocaine Use Disorder (CUD) is a global public health problem, with no effective pharmacotherapies. While CUD is marked by high heritability, discovery of variants associated with risk for CUD has proven difficult. We used Restriction Enzyme Based Enriched L1 sequencing (REBELseq) to amplify L1 retrotransposons in gDNA isolated from medial prefrontal cortex NeuN+ neuronal nuclei from 25 CUD cases and 26 controls. Amplified libraries were sequenced on the Illumina HiSeq 4000 platform, and sequencing data was analyzed with the REBELseq bioinformatics pipeline.

  Study phs001966

• 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

• How upcycled prostate cancer sequences enabled key findings on telomeres length

  The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

  Blog prostate-cancer-sequences-enabled-key-findings-on-telomeres-length

• Neurodevelopment_Nantes_hospital

  The neurodevelopmental team in the genetics unit of Nantes hospital focus on the identification on new genes causing neurodevelopmental disorders through whole-genome and transcriptomics sequencing.

  Dac EGAC50000000542

• scMultiome (snRNA + snATAC) data of 26 regionally sampled GBM tissue from 6 patients

  This dataset contains snRNA-seq data of 26 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed unsorted or by sorting with 7AAD to remove debris and dead cells. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit, nuclei were barcoded and RNA and ATAC libraries were constructed, allowing for simultaneous capture of transcriptome and epigenome from the same cells.

  Dataset EGAD50000001838

• MEC/SEF RNA-seq

  RNA transcript expression sequencing of 27 MEC/SEF tumor samples. Samples were sequenced at Beijing Genomics Institute. Prior to sequencing, rRNA removal library preparation was done for any samples that had degraded. Samples were sequenced on a DNBseq platform sequencer with a read length of 100PE, producing approximately ~40M raw reads (~8GB) raw data per sample.

  Dataset EGAD50000000761

• Extensive and differential platinum chemotherapy mutagenesis in livers of children - Targeted NanoSeq

  Targeted NanoSeq using a bait set consisting of 285 genes, comprising mostly cancer genes, of a Validation cohort that includes platinum-exposed (n=195) and platinum naïve (n=60) samples from 26 individuals (children and foetal tissues). The samples are mainly liver samples (normal and cancer tissues) and obtained from children with liver cancer.

  Dataset EGAD00001016120

• Young Boost Trial for Breast Cancer patients

  The Young Boost Trial (YBT, YOUNG BOOST / BOOG 2004-01 (Borstkanker) | Kanker.nl investigated the optimal radiation dose for breast cancer patients aged 50 years or younger, treated with breast-conserving therapy (BCT). In this randomized study, participants were assigned to receive either a 26 Gy or a 16 Gy radiation boost, with the primary endpoint being local recurrence. To explore potential predictive biomarkers of treatment response in this patient group, whole exome sequencing (WES) was performed on tumor samples to identify genetic factors that could guide personalized treatment strategies and improve clinical outcomes for these young breast cancer patients.

  Study EGAS50000000797

• Oral Immunotherapy for Induction of Tolerance and Desensitization in Peanut-Allergic Children (IMPACT)

  Brief Summary:This is a randomized, double-blind, placebo-controlled, multi-center study comparing peanut oral immunotherapy (OIT) to placebo in the induction of tolerance and desensitization in peanut-allergic children. Eligible participants with peanut allergy will be randomly assigned to receive either peanut OIT or placebo for 134 weeks followed by peanut avoidance for 26 weeks.Detailed Description:An initial oral food challenge (OFC) to 1 g of peanut flour (500 mg peanut protein) will be conducted. Participants must have a clinical reaction during this OFC to initiate study dosing. After the initial OFC, the study design includes four phases:Initial dose escalation (1 day): Peanut or placebo dosing will be given incrementally and increase every 20 minutes until a dose of 12 mg peanut flour (6 mg peanut protein) or placebo flour is given. Build-up (30 weeks): Initial observed dose administration of highest tolerated dose, followed by daily OIT at home with return visit every 2 weeks for dose escalation. Maintenance (104 weeks):The participant will continue on daily OIT with return visits every 13 weeks. At the end of this phase the participant will undergo a blinded OFC to 10 g peanut flour (5 g peanut protein). Avoidance (26 weeks): In this final phase participants will be seen every 13 weeks. At the completion of this phase participants will have a final blinded OFC to 10g peanut flour (5 g peanut protein)

  Study phs003109

• Exome Sequencing of Esophageal Adenocarcinoma

  The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. When coupled to the five-year survival rate of only 15% for this disease, identification of new therapeutic targets for EAC is of great importance. Here, we analyze the mutational spectra identified from the whole genome sequencing of 16 EACs and complete exome sequencing of 149 EAC tumors and matched germline samples. We identify a novel mutation signature marked by high prevalence of A to C transversions at AA*(N) trinucleotides. Notably, the development of EAC is preceded by pathologic intestinal metaplasia of the lower esophagus, Barrett's esophagus, itself a response to injury from gastric-esophageal reflux disease (GERD). Thus, we hypothesize to represent these AA*(N) mutations to a novel signature of GERD-induced mutagenesis. Analysis of the exome data identified 26 genes subject to statistically significant recurrent mutation. Of these 26 genes, only TP53, CDKN2A, SMAD4, and PIK3CA had been previously implicated in EAC. Novel mutations include those targeting chromatin modifying factors and novel candidate contributors to EAC: SPG20, TLR4, ELMO1 and DOCK2. Of these, ELMO1 and DOCK2 are notably direct dimerization partners that act to activate Rac1 to enhance cellular invasiveness, thus generating new hypotheses about the potential for the Rac1 pathway to be a novel target for therapy of EAC. "Reprinted from 'Unraveling the mutational complexity of esophageal adenocarcinoma', with permission from Nature Genetics."

  Study phs000598

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• Genetic analysis of HLA and immune escape genes in Diffuse Large B-cell Lymphoma

  We performed genetic analysis of HLA and immune escape genes in samples from 44 patients sequenced by whole exome sequencing (34 tumor samples, 32 normal samples) and whole genome sequencing (10 tumor samples, 12 normal samples). We also performed HLA targeted sequencing in 26/44 patients (26 tumor samples, 26 normal samples).

  Dataset EGAD00001007565

• InsPIRE islets

  We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors and 26 FAC sorted beta-cells.

  Study EGAS00001003997

• Dedifferentiated Melanoma (2021-02-02)

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006931

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

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

  Dataset EGAD00001003706

• Peripheral blood DNA transcriptomics of ustekinumab treatment response in patients with Crohn's disease

  Data pertains longitudinal transcriptomic data measured from blood obtained from patients with Crohn's disease that were starting treatment with ustekinumab. Samples were obtained prior to treatment and approximately 26 weeks into treatment during response assessment. At response assessment, patients were classified as responders (R) or non-responders (NR) based on a strict combination of endoscopic, biochemical and clinical criteria: ≥50% reduction in the endoscopic SES-CD score, corticosteroid-free clinical remission (≥3 point drop98 in HBI or HBI ≤4 and no systemic steroids) and/or biochemical response (C-reactive protein (CRP) and fecal calprotectin reduction ≥50% or ≤5 mg/L and fecal calprotectin ≤250 µg/g). Modified response was defined as a combination of corticosteroid-free clinical- (HBI ≤4) and biochemical (CRP ≤5 mg/L and/or fecal calprotectin ≤250 µg/g) remission between week 26-52 without treatment change through week 52. Transcriptomic analyses was conducted through RNA sequencing, wherein mRNA was extracted utilizing the QIAsymphony system, converted into cDNA and sequenced in a paired-end format on the Illumina NovaSeq6000 at the Amsterdam UMC Core Facility Genomics, generating a dataset comprising 40 million 150 bp-reads.

  Dataset EGAD50000000386

• Peripheral blood DNA transcriptomics of vedolizumab treatment response in patients with Crohn's disease

  Data pertains longitudinal transcriptomic data measured from blood obtained from patients with Crohn's disease that were starting treatment with vedolizumab. Samples were obtained prior to treatment and approximately 26 weeks into treatment during response assessment. At response assessment, patients were classified as responders (R) or non-responders (NR) based on a strict combination of endoscopic, biochemical and clinical criteria: ≥50% reduction in the endoscopic SES-CD score, corticosteroid-free clinical remission (≥3 point drop98 in HBI or HBI ≤4 and no systemic steroids) and/or biochemical response (C-reactive protein (CRP) and fecal calprotectin reduction ≥50% or ≤5 mg/L and fecal calprotectin ≤250 µg/g). Modified response was defined as a combination of corticosteroid-free clinical- (HBI ≤4) and biochemical (CRP ≤5 mg/L and/or fecal calprotectin ≤250 µg/g) remission between week 26-52 without treatment change through week 52. Transcriptomic analyses was conducted through RNA sequencing, wherein mRNA was extracted utilizing the QIAsymphony system, converted into cDNA and sequenced in a paired-end format on the Illumina NovaSeq6000 at the Amsterdam UMC Core Facility Genomics, generating a dataset comprising 40 million 150 bp-reads.

  Dataset EGAD50000000385

• Pre-existing immunity drives the response to neoadjuvant chemotherapy in esophageal adenocarcinoma

  Esophageal adenocarcinoma (EAC) is a highly aggressive tumor. Patients with locally advanced disease undergo neoadjuvant chemotherapy (nCT) before surgery, however fewer than 30% of treated patients achieve a pathological complete response associated with increased 5-year overall survival. We set out to elucidate the mechanisms the response to nCT by multi-dimensional profiling of pre-treatment tumor biopsies and blood samples from EAC patients. In particular we performed whole exome sequencing (WES) and RNAseq on n=26 baseline EAC tumor; two additional EAC samples underwent only WES. WES on matched peripheral blood mononuclear cells (PBMCs) were used as germline control.

  Study EGAS00001007245

• Genetics of Neuropsychiatric and Neurodevelopmental Disorders

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

  Study phs000682

• Whole Exome Sequencing of gliomas

  Dataset EGAD00001001614

• Frequent germline mutations of HAVCR2 in sporadic subcutaneous panniculitis-like T-cell lymphoma.

  Subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare subtype of peripheral T-cell lymphoma affecting younger cases and associated with hemophagocytic lymphohistiocytosis. To clarify the molecular pathogenesis of SPTCL, we analyzed paired tumor and germline DNAs from 13 patients by whole exome sequencing.

  Dataset EGAD00001004795

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  Study on RNA-seq data from tumor tissue samples of primary tumors of advanced clear cell renal cell carcinoma patients enrolled in the NIVOREN GETUG-AFU-26 trial who consented to and participated in the translational program. The goal of this study was to assess previously published gene expression signatures and evaluate their association with the benefit and/or resistance to nivolumab, as well as their association with circulating soluble factors.

  Study EGAS50000001057

• Bladder cancer sequencing data

  Dataset EGAD00001001036

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

• Low-pass nanopore whole genome sequencing of brain tumors

  Dataset EGAD00001003382

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• RNA sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  RNA-seq for 26 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study, and 32 samples from a previously uploaded dataset.

  Dataset EGAD50000001365

• Cancerous Adaptive Dosing Melanoma WGS Dataset

  Illumina NovaSeq 6000 30x WGS of 26 samples, each with up to 5 matched timepoints. Timepoints A,B,C,D,and E correspond to Pretreatment, Week 3, Week 6, Week 9, and Week 12 after treatment, respectively. Additional sample metadata (sample recurrence, treatment course, age, sex, comorbidities, etc.) are present in sample description.

  Dataset EGAD00001010926

• Aligned FOS RNA sequencing data

  Total RNA-sequencing Paired-End was performed by GenomeScan (Leiden, the Netherlands) on the NovaSeq6000 platform for full-length FOS (FOS FL), truncated FOS (FOSΔ), a FOS isoform with an L376N mutation (FOS mut), untransduced fMSC (unt) and fMSC with empty pLV (pLV) at week 0, 1, 2, and 3 in triplicate (total of 60 samples). Raw RNA-seq data were processed by the RNA-seq BioWDL pipeline pipeline version 5.0.0 developed by the SASC team at LUMC, LUMC, Leiden, the Netherlands).

  Dataset EGAD50000001839

• European Genome-phenome Archive 15th Anniversary Celebration

  2023 marks the 15th Anniversary of the EGA, jointly managed by the European Bioinformatics Institute (EMBL-EBI) and the Centre for Genomic Regulation (CRG). To mark the occasion, a simultaneous celebration was held in both institutions on the 13th of December 2023. The teams gathered online to play a quiz game and celebrate all the achievements and milestones with two wonderful anniversary cakes. In 2008, the European Genome-phenome Archive was created at the EBI-EMBL in Cambridge to guarantee that human genome and phenome data were available to the international scientific community while data privacy was preserved. The six-person staff at the beginning of the project is now far behind us, with a team that reaches the number of 35 members. Since 2013, the European Bioinformatics Institute and the Centre for Genomic Regulation share responsibility for The European Genome-phenome Archive (EGA). At that time, the EGA had data for about 0,5 petabytes. Currently, the Archive contains more than 12 petabytes. 2023 comes to an end with several good news. The EGA has been renewed as an ELIXIR Core Data Resource. This was announced during the GA4GH 11th Plenary held in San Francisco last September when ELIXIR-Beacon was also confirmed to be a GA4GH Driver Project. Thus, the Beacon API has maintained this title since 2018. What’s more, the first Federated EGA dataset is now live on our website. This year we also launched new services for EGA users in September. By the numbers, in 2023 the EGA counts 2.5 PB archived, 371 studies published, 208 new submitters and 19 active projects in which the team is participating, among others. We look forward to continuing to support your research in 2024!

  Blog 15-anniversary

• Combination_therapies_for_personalized_cancer_medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Study EGAS00001000655

• Identification of putative multiple myeloma (MM) susceptibility genes

  We sought to identify novel MM susceptibility genes using a collection of families with multiple cases of MM/MGUS, including 189 affected individuals from 40 families, and index cases from an additional 88 families, along with 170 early-onset (EO) MM cases (≤ 55 years). We analyzed a total of 347 affected individuals using whole exome (N=321) and whole genome (N=26) sequencing. Samples were identified and collected through nation-wide efforts in France, Sweden and Greece. We focused on rare (MAF<0.5%) germline protein truncating and likely deleterious missense variants in genes harboring variants in at least two families showing variant-disease segregation, and in additional index (≥2) and/or early-onset (≥2) cases.

  Study EGAS50000001259

• Metastatic Prostate Follow Up 2

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000989

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: kidney (2019-03-26)

  This dataset contains all the data available for this study on 2019-03-26.

  Dataset EGAD00001004867

• Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer.

  This dataset consists of shallow whole genome sequencing data and amplicon sequencing data for 26 ovarian cancer patients (21 high-grade serous ovarian cancer, 4 low-grade serous ovarian cancer and 1 clear cell ovarian cancer). The data are provided as single end FASTQ files for the shallow whole genome sequencing data (31 libraries) and paired end FASTQ files for the amplicon sequencing data (98 libraries).

  Dataset EGAD00001008716

• Single nucleus RNA Seq of LUAD patient derived lung samples

  Fastq files of single nucleus RNA Sequencing data from 26 patients including 26 lung adenocarcioma and 12 matched healthy tissue samples for 8 young female never smokers, 8 young female smokers, 7 elderly female never smokers and 3 male never smokers.

  Dataset EGAD00001008955

• GEDI: A Developmental Model of Gene-Environment Interplay in SUDs: Combined Genotype Dataset from the "Great Smoky Mountains Study" and the "Caring for Children in the Community Study".

  1. Great Smoky Mountains Study (GSMS; Costello et al. 1996, 1997) Three cohorts of boys and girls, aged 9, 11, and 13 years at intake in 1993, were selected from a rural population of some 20,000 children using a household equal probability design. A two-phase procedure was used for White and African-American youth to increase power by oversampling children at risk for psychiatric and SUDs. Parents (usually mothers) of the first stage random population sample completed a questionnaire about their child&#39;s behavioral problems. Of 4,195 subjects selected, 95% (N=3,896) of parents completed the screen. All children scoring above a predetermined threshold (the top 25% of the total scores), plus a 10% random sample of the remaining 75%, were recruited for detailed interviews. Results can be back-weighted to population levels for analyses. Half of the sample consists of females, and 6% are African Americans, reflecting the population of the study area. The interviewed sample of white and African-American subjects was 1,070 (80% of those recruited). American Indian youth were oversampled (100%) because they are an understudied group known to be at high risk for stressful events, substance disorders, and mood disorders. Of 431 age-eligible children, 350 (81% boys, 49% girls) participated. Thus, the size of total GSMS sample is 1,070 + 350 = 1,420. Data collection is complete for ages 9-26, and age 30 interviews are in progress. By age 26 a total of 9,858 interviews had been completed; the average number of interviews per subject was seven, and by age 26, 97.3% completed two or more interviews. 2. The Caring for Children in the Community Study (CCC; Angold et al., 2002) This representative study of psychiatric illness and service use in African-American and White youth took place in four rural counties in the southeastern USA. The two-stage sampling design and methods are similar to those used in the GSMS. Of 4,500 youth randomly selected from the 17,117 9- to 17-year-olds in the public school&#39;s database, 3,613 (80.0%) were successfully contacted and agreed to complete the behavioral screen. Of the 1,302 selected to participate in the study, 920 (70.7%) interviews were completed. Because CCC was also the only study in GEDI to contain more than a very few African-American participants, these were omitted from the multi-site analyses. Reprinted with permission from Cambridge University Press from Costello et al., 2013: PMID: 23461817 References: Costello et al., 1996: PMID: 8956679 Costello et al., 1997: PMID: 9184514 Angold et al., 2002: PMID: 12365876

  Study phs000852

• Stratton__WGS___RCC___Japan

  The Stratton team uses DNA sequencing for somatic mutations to advance understanding of the causes of cancer. In particular, the investigation of “mutational signatures”, which report the mutational processes operative over the lifetime of each individual, to understand whether they are generated by endogenous or exogenous exposures and the extent to which these vary between human populations. Our work brings together global cancer epidemiology and genomics and is particularly characterised by large-scale multinational studies.

  Study EGAS00001008001

• CPC-GENE Prostate Cancer Heterogeneity Study

  Raw sequence data, fastq format

  Dataset EGAD00001002885

• A dataset compiled as a resource a for orthogonal assessment of exon CNV calling in NGS data

  The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect. The full dataset includes FASTQ files, target BED file, and MLPA results.

  Study EGAS00001002428

• Functional characterisation of CpG islands in human tissues

  Functional characterisation of CpG islands in human tissues

  Dataset EGAD00001000212

• Test Study for EGA using data from 1000 Genomes Project - Phase 3

  The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes &gt;99% of SNP variants with a frequency of &gt;1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies...

  Study EGAS00001005042

• PETAL Network: Outcomes Related to COVID-19 Treated With Hydroxychloroquine Among Inpatients With Symptomatic Disease (ORCHID) Trial

  ORCHID was a multicenter, blinded, placebo-controlled randomized trial conducted at 34 hospitals in the US between April 2 and June 19, 2020. Adults hospitalized with respiratory symptoms from severe acute respiratory syndrome coronavirus 2 infection were enrolled, with the last outcome assessment on July 17, 2020. The planned sample size was 510 patients with five interim analyses; however, the trial was stopped at the fourth interim analysis for futility with a sample size of 479 patients.The distribution of the day 14 clinical status score (measured using a 7-category ordinal scale) was not significantly different for patients randomized to receive hydroxychloroquine compared with placebo.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002299

• Error-corrected sequencing of 26 driver genes

  387 swab samples were sequenced. The bam files contain consensus reads.

  Dataset EGAD50000000079

• The Longevity Genes Project

  Aging is a complex, universal condition leading to the functional decline of all cells and organisms, and to major national and global public health problems. Although aging is the major risk factor for developing most adult-onset diseases, systematic investigations into the fundamental physiology, biology and genetics of aging are only just beginning. In the Longevity Genes Project at Albert Einstein College of Medicine, Dr. Nir Barzilai and his team conducted genetic research on more than 500 healthy elderly people between the ages of 95 and 112, and on their children. The identification of longevity genes by Einstein researchers could lead to new drug therapies that might help people live longer, healthier lives and avoid or significantly delay age-related diseases such as Alzheimer&#39;s disease, type 2 diabetes and cardiovascular disease.

  Study phs000584

• Radiation-Related Genomic Profile of Papillary Thyroid Cancer after the Chernobyl Accident

  The April 26, 1986 accident at the Chernobyl nuclear power plant in northern Ukraine resulted in the release of radioactive contaminants, which were deposited in the surrounding areas in Ukraine, Belarus, and Russia. The main radiation-related health effect resulting from these exposures is the increased occurrence of thyroid cancer among individuals who were children at the time of the accident or born shortly thereafter. The purpose of this study was to conduct a comprehensive genomic landscape analysis of papillary thyroid tumors arising in individuals who were exposed as children to radioactive iodine (I-131) from the Chernobyl nuclear power plant accident.

  Study phs001134

• COVID-19-Induced Immune Alterations in Infants

  Although previous studies have described some overlap between COVID-19-induced immune alterations in adults and children, no systematic immune profiling studies have been reported in infants. We applied a multidimensional approach to decipher the immune responses to SARS-CoV-2 infected infants (n=26; 10 mild, 11 moderate and 5 severe) and healthy matched controls (n=14). Single-cell RNA-seq profiling (scRNA-seq) of PBMCs revealed alterations in cell composition upon infection, with most cell types demonstrating an interferon-stimulated gene (ISGhi) state. Our findings shed insight into the immune responses to SARS-CoV-2 in the first year of life.

  Study phs002655

• 'IL-17A-Producing ILC3s and Duodenal Adenoma in FAP'

  Familial Adenomatous Polyposis (FAP) is a hereditary tumor syndrome that significantly enhances the risk of duodenal adenomas, with variations observed even among carriers of the same genetic variant. In this study, intestinal ILCs were isolated from 82 FAP and 26 non-FAP patients and analyzed through flow cytometry, qRT-PCR, and bulkRNA-sequencing. The data revealed a heightened frequency of ILC3s in FAP patients, and increased IL-17A production of duodenal NKp44(-)ILC3s was associated with FAP. Significant elevations in IL1B, IL23A, and DLL4 mRNA expression levels were found in FAP duodenal adenoma tissue, along with enhanced expression of DUOX2 and DUOXA2. The results suggest the involvement of IL-17A-producing NKp44(-)ILC3s in duodenal adenoma formation in FAP.

  Study EGAS00001007347

• Anaplastic meingioma methylation

  Methylation of anaplastic meningiona samples

  Dataset EGAD00010001629

• Bulk RNA-seq of ATCWGS42 PDX models

  This dataset contains bulk RNA-seq dataset for ATCWGS42 PDX models

  Dataset EGAD50000002145

• PROstate Cancer Medically Optimized Genome Enhanced ThErapy (PROMOTE) of Castration Resistant Prostate Cancer (CRPC) Patients Treated with Abiraterone Acetate

  The Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study uses genetic clues in castration-resistant prostate cancer that may identify an individualized treatment approach for men with the disease. Understanding the molecular biology behind castration-resistant prostate cancer has led to more treatment options, but there are still no definite conclusions about which specific drug best treats patients - maximum suppression of cancer growth while minimizing side effects. The PROMOTE study explores the genetic characteristics of each tumor to predict these treatment paradigms for the future, resulting in more effective and less toxic options for patients. Our long-term goal is to improve treatments for men with advanced prostate cancer by using genomic sequencing to increase life span and quality of life. We also will uncover novel vulnerable targets in the cancer genome that may provide new drug therapies. PARTICIPATION Eligible participants are men: With castration-resistant prostate cancer or prostate cancer not responding to hormone treatments About to begin abiraterone acetate therapy Agreeable to undergoing two tumor biopsies During the study, participants travel to Mayo Clinic for an initial biopsy (before beginning abiraterone acetate) and a second biopsy approximately three months later. The cell tissue collected is analyzed to identify gene alterations in the tumor that could eventually be targeted with treatments. Tissue is preserved for future research. Participants can continue to be treated by their local cancer care team during this period and beyond. In addition, the Mayo team carefully monitors participants' cancer via follow-up studies and the genetic signature of tumors that were biopsied so that patients may benefit from future treatments.

  Study phs001141

• Longitudinal sampling in relapsed and refractory Hodgkin lymphoma

  Ultra-deep next-generation panel-sequencing on 59 FFPE-samples (20 LTR, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. Data was processed as described in the publication and mark duplicated bam files were uploaded.

  Dataset EGAD50000000210

• All you need to know about the new Submitter Portal

  In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.

  Blog new-submitter-portal

• Paired Biopsy Project: West Coast Dream Team

  This project contains the 16 WGS tumor samples and the corresponding 15 WGS normal tissue samples (germline control) not yet deposited in the public domain (e.g., EGA, dbGaP) at the time of submission of the manuscript (Zhu et al.)

  Dataset EGAD50000000473

• Error-corrected sequencing of 26 driver genes (additional cohort)

  An additional 320 swab samples were sequenced. The bam files contain consensus reads.

  Dataset EGAD50000000641

• Whole Exome Sequencing

  Whole Exome Sequencing Data for 10 patients for treatment with the ICI Nivolumab

  Dataset EGAD00001011117

• WES of der(1;7)(q10;p10) myeloid neoplasms

  The study examined WES of der(1;7)(q10;p10) myeloid neoplasm cases. BAM files of WES of 26 myeloid neoplasm patients with der(1;7)(q10;p10) were used to identify key driver genes in patients with der(1;7)(q10;p10). This study is one of the largest WES for der(1;7)(q10;p10)(+) myeloid neoplasm cases.

  Study EGAS50000000704