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• Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) - OncoArray Genotypes

  The data come from 40 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). CIMBA recruits individuals with pathogenic mutations in BRCA1 or BRCA2. The majority of carriers were recruited through cancer genetics clinics offering genetic testing, and were enrolled into national or regional studies. The remainder were identified by population-based sampling of cases, or community recruitment. Eligibility to participate is restricted to carriers of pathogenic BRCA1/2 mutations who were 18 years or older at recruitment. Information collected included amongst other variables: age at recruitment; ages at breast and ovarian cancer diagnosis; and estrogen receptor (ER) status. Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in Phelan et al, Identification of twelve new susceptibility loci for different histotypes of epithelial ovarian cancer, Nat Genet. 2017 May;49(5):680-691 (PMID:28346442), and Milne et al, Identification of ten variants associated with risk of estrogen receptor negative breast cancer, Nat Genet (in press).

  Study phs001321

• Germline Genomic Analyses of Breast Cancer in Latinas

  In this case-control study of breast cancer among Hispanic/Latina (H/L) women, the goals were to identify breast cancer susceptibility genes and genetic variants for risk of developing breast cancer in H/L women. There were two phases with whole exome sequencing (WES) done in a discovery phase and targeted sequencing of candidate genes in the replication phase. The candidate genes selected for replication came from the first phase and from genes known to affect breast cancer risk in prior studies. Cases and controls were drawn from several studies. Breast cancer cases for discovery phase included women from the City of Hope (COH) Clinical Cancer Genomics Community Research Network (CCGCRN), UCSF Cancer Genetics Clinic and USC Cancer Genetics clinic. Controls for discovery phase included women who did not have breast and were recruited through City of Hope community fairs. A separate group of controls included women from the California Teachers Study. Additional controls for discovery were obtained from WES already generated by the Multi-ethnic cohort (MEC) study. The discovery/WES results of known breast cancer genes were published (PMID 31206626). In the replication phase, we included cases and controls from the Cancer de Mama (CAMA) study which is a case-control study of breast cancer in Mexico, MEC for those not included in the discovery dataset, the San Francisco Bay Area Cancer study (phs000912), the Northern California Breast Cancer Registry, and the California Pacific Medical Center Research Institute Women's Cohort (phs000395). Cases from the PATHWAYS study who were recruited from Northern California Kaiser Permanente were also included. Results from the combined discovery and replication analyses are reported in PMID 36747679.

  Study phs003144

• Multimodal Analysis for Human Ex Vivo Studies Shows Extensive Molecular Changes from Delays in Blood Processing

  Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMCs up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states.

  Study phs002280

• Multi-omics datasets (WES, RNA-seq) of mesothelioma NERO study, a phase II PARP inhibitor clinical trial

  Niraparib Efficacy in Patient With Unresectable Mesothelioma, NERO, this randomised phase II trial is designed to evaluating the efficacy of the PARP inhibitor Niraparib versus active symptom control.

  Study EGAS50000001825

• Single-cell RNA-seq of cervix and placenta

  Placental trophoblasts have been detected in cervical smears early in gestation, creating opportunities for non-invasive prenatal diagnosis. However, trophoblast isolation is limited by the lack of a cell catalogue and molecular profile of cervical smears. To establish an atlas and to explore the potential of single-cell RNA-sequencing to detect cervical trophoblasts, 10,539 single-cell transcriptomes from 12 non-invasive exocervical smears from pregnant women were profiled. In addition, we characterized 34,565 cells from six placental biopsies. We uncovered a novel extravillous trophoblast cell subtype characterized by epithelial marker genes and reduced HLA-G expression. Integration of both cell atlases demonstrated surprisingly similar expression profiles between maternal epithelial cells and placental extravillous trophoblasts, indicating that these trophoblasts retained epithelial properties without an invasive mesenchymal phenotype. Additionally, differential expression analysis identified novel markers discriminating cervical and placental cell types. Those analyses may contribute to trophoblast discovery and isolation from cervical smears.

  Study EGAS00001007044

• GOSH_Childhood_Leukemia_Behjati_WellcomeCore_RNA

  Paediatric single-cell archival project This project is taking sequential samples of children with B-cell acute lymphoblastic leukaemia (B-ALL) treated at Great Ormond Street Hospital (GOSH) between 2011 and the present day. Patients selected, are those that have done badly (e.g. had to escalate treatment, relapsed or died) despite having apparently ""good"" or ""intermediate"" risk cytogenetics, and often also had immunotherapy (e.g., the bi-specific T-cell engager blinatumomab) because of this. Using samples from key treatment-points, we hope to better characterise their disease and treatment response, to re-define understandings of risk for patients who did unexpectedly poorly. Additionally, we hope to define the disease/immunological factors that determine response to increasingly used immunotherapies within the field of paediatric B-ALL. Each of the samples will be viably frozen bone marrow-derived mononuclear cells. They will come in Eppendorf's, frozen and de-anonymised, from GOSH. We plan to primarily do single cell analysis (GEX, BCR +/-TCR), and then tumour-only WGS and bulk-RNA expression on left-over

  Study EGAS00001007616

• Kids First: Pediatric Research Project on the Genomic Analysis of Congenital Diaphragmatic Hernia

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both, childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. In collaboration with the University of Utah, DNA from four families were selected for high-depth WGS (60X) including diaphragm and skin tissue to identify mosaicism. In collaboration with the Broad Institute, DNA from four families underwent linked long read sequencing using 10X Genomics technology. Probands with congenital diaphragmatic hernia/defects and both biological parents enrolled as part of the DHREAMS study.

  Study phs001110

• EGAD00000000054

  NCI-H209 is an immortal cell line derived from a bone marrow metastasis of a patient with small cell lung cancer, taken before chemotherapy. The specimen showed histologically typical small cells with classic neuroendocrine features. NCI-BL209 is an EBV-transformed B-cell line derived from the same patient as the small cell lung cancer cell line, NCI-H209

  Dataset EGAD00000000054

• Genomic Characterization of Meningiomas

  Meningiomas are the most common primary brain tumor in the US. Although the tumor suppressor gene NF2 is disrupted in approximately half of meningiomas, the complete spectrum of genetic changes in meningiomas remains poorly understood, particularly in the large subset of tumors without NF2 alterations. Therefore we performed whole-genome sequencing from 11 Grade I meningioma tumor-normal pairs and whole-exome sequencing from an additional 6 tumor-normal pairs to identify somatic mutations, insertions-deletions, copy-number alterations and rearrangements. We validated our results by performing focused sequencing across 48 additional meningiomas.

  Study phs000552

• ChIP-seq of GOF p53 mutants

  Gain-of-function TP53 mutations were detected in 41.3% of cases, in which co-occurring del(17p) underscored a dominant effect in >25%. Missense mutations of TP53 clustered within the core DNA-binding domain, where R249S was most common. To explore the transcriptional effect of mutant p53(R249S), we performed chromatin immunoprecipitation-sequencing in the HCC cell line HKCI-11, which has a p53(R249S) mutation, and the human hepatocyte line MIHA, which is p53(WT). The results revealed distinct binding profiles between wildtype p53 and p53 mutant.

  Study EGAS00001002463

• Human induced pluripotent stem cells display a similar mutation burden as embryonic pluripotent cells in vivo

  Induced pluripotent stem cells (iPSCs) hold great promise for regenerative medicine, but genetic instability is a major concern. Embryonic pluripotent cells also accumulate mutations during early development, but how this relates to the mutation burden in iPSCs remains unknown. Here, we directly compared the mutation burden of cultured iPSCs with their isogenic embryonic cells during human embryogenesis. We generated developmental lineage trees of human fetuses by phylogenetic inference from somatic mutations in the genomes of multiple stem cells, which were derived from different germ layers. Using this approach, we characterized the mutations acquired pre-gastrulation and found a rate of 1.65 mutations per cell division. When cultured in hypoxic conditions, iPSCs generated from fetal stem cells of the assessed fetuses displayed a similar mutation rate and spectrum. Our results show that iPSCs maintain a genomic integrity during culture at a similar degree as their pluripotent counterparts do in vivo.

  Study EGAS00001005939

• Variant calling dataset from the whole-exome study of familial pulmonary fibrosis in the Canary Islands-VCF files

  Sequence reads were obtained from a set of 13 families with familial pulmonary fibrosis in the Canary Islands, Spain, using Illumina paired-end reads, respectively, at the Institute of Technology and Renewable Energy (ITER). Briefly, we used bcl2fastq v2.18 to perform sample demultiplexing and BWA-MEM v0.7.15 (https://github.com/lh3/bwa) to align reads to GRCh37/hg19 reference. Resulting BAM files were assessed with SAMtools v1.3 (http://www.htslib.org) and Picard v2.10.10 (https://broadinstitute.github.io/picard/) for quality control steps. Small insertions/deletions (< 50 bp) and single nucleotide variants (SNVs) were identified using an in-house bioinformatics pipeline based on GATK HaplotypeCaller v3.8 (https://gatk.broadinstitute.org/hc/en-us/articles/360037225632-HaplotypeCaller). This pipeline follows the Best Practices recommendations for germline variant calling and its description is publicly available (https://github.com/genomicsITER/benchmarking/tree/master/WES).

  Dataset EGAD50000001152

• Comparison of structural variations from 10X Genomics linked-reads and conventional Illumina short-reads sequencing

  Structural variations (SVs) are large genomic rearrangements that can drive many diseases. Conventional short-reads whole genome sequencing (cWGS) allows their identification with base-pair resolution, but suffers from high false discovery rate. cWGS taps in short-range information from short-reads while linked-reads sequencing (10XWGS) utilizes long-range information. 10XWGS allows linkage of short-reads originating from the same large DNA molecule with a unique barcode captured in a gel bead in emulsion. This mitigates alignment-based artefacts from cWGS especially in repetitive regions. However, the false discovery rate of this technology is unclear. In this study, we performed a comprehensive analysis of different type and size of SVs predicted from these two technologies. The SVs common between both technologies were found to be highly specific by PCR and Sanger sequencing while validation rate dropped for uncommon events. Further, we propose a novel enrichment approach for filtering out false positive calls from both the technologies independently. To this end, we trained a machine learning model for respective technologies and used it to characterise SVs from MCF7 cell line and a primary breast cancer tumor with high precision. This approach would be valuable in understanding true mechanisms driven by SVs in various diseases.

  Study EGAS00001004093

• Gene expression-based prediction of pazopanib efficacy in sarcoma (HIPO, H021)

  The multi-receptor tyrosine kinase (RTK) inhibitor pazopanib is approved for the treatment of advanced non-adipocytic soft-tissue sarcoma and has also shown activity in other sarcoma subtypes. However, its clinical efficacy is highly variable, and no reliable predictors exist to date to select patients who are most likely to benefit from this drug. We analyzed the molecular profiles and clinical outcomes of pazopanib-treated sarcoma patients enrolled in a prospective observational study by the German Cancer Consortium, DKTK MASTER, that employs whole-genome/exome sequencing (WGS/WES) and transcriptome sequencing to inform the care of adults with advanced cancer across histologies who are younger than 51 and patients with rare tumors, including rare subtypes of more common entities, regardless of age.​ Among a total of 109 patients with available WGS/WES data, there was no correlation between clinical parameters, specific genetic alterations, or mutational signatures and clinical outcome. In contrast, analysis of a subcohort of 62 patients who underwent molecular analysis before pazopanib treatment and had transcriptome sequencing data available showed that mRNA levels of NTRK3 (hazard ratio [HR]=0.53, p=0.021), IGF1R (HR=1.82, p=0.027), and KDR (HR=0.50, p=0.011) were independently associated with progression-free survival (PFS). Based on the expression of these RTK genes, i.e., the features NTRK3-high, IGF1R-low, and KDR-high, we developed a pazopanib efficacy predictor (PEP) that stratified patients into three groups with significantly different PFS (p&lt;0.0001). Application of the PEP to an independent cohort of pazopanib-treated sarcoma patients from DKTK MASTER (n=43) confirmed its potential to separate patient groups with significantly different PFS (p=0.02), whereas no such association was observed in sarcoma patients from DKTK MASTER (n=77) or The Cancer Genome Atlas sarcoma cohort (n=256) who were not treated with pazopanib. A score based on the combined expression of NTRK3, IGF1R, and KDR allows identification of sarcoma patients with good, intermediate, and poor outcome following pazopanib therapy and warrants investigation as a predictive tool in prospective studies to optimize the use of this drug in the clinic.

  Study EGAS00001005836

• Gastrointestinal Cancer Treatment Responders

  Comprehensive genomic profiling of colon adenocarcinomas has revealed multiple recurrent alterations that may inform new treatment strategies. Clinical trials of these agents are ongoing, although the mechanisms of response and resistance to these agents are not well characterized. The goal of this study is to perform comprehensive profiling of pre-treatment and post-resistance tumor and germline samples obtained from patients with colon cancer who receive these agents by carrying out whole exome sequencing and RNA sequencing, and to use these data to identify mechanisms of response and resistance.

  Study phs000803

• Chinese Alternating Hemiplegia of Childhood (AHC) Disease Study

  AHC is a rare and severe neurological disorder, and characterized by episodic hemiplegia or quadriplegia attacks, accompanied by other paroxysmal symptoms of oculomotor abnormalities, dystonia, seizures and autonomic disturbances; the age of onset usually occurrs before 18 months of life. Sodium-potassium ATPase alpha3 subunit (ATP1A3) has recently been identified as a causal gene for sporadic AHC by three groups. However, there has not been any large genetic study on a Chinese cohort. In the submitted data, whole-exome sequencing of three trios and three sporadic cases in a Chinese cohort produced an average of 18.8 gigabases of raw sequence. Through our analysis pipeline including BWA mapping, GATK recalibration, variant calling and filtering, all six patients contained missense mutations in ATP1A3 which were further confirmed as de novo mutations. Along with validation in additional patients, this study confirmed ATP1A3 as a causal gene in Chinese AHC patients, and reported six novel mutations.

  Study phs000660

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas

  RNA polymerase II mediates the transcription of all protein-coding genes in eukaryotic cells, a process that is fundamental to life. Genomic mutations in this enzyme have not been previously linked to any pathology in humans, a testament to its indispensable role in cell biology. Based on a combination of next-generation genomic analyses of 775 meningiomas, we report that recurrent somatic p.Gln403Lys or p.Leu438_His439del mutations in POLR2A, which encodes the catalytic subunit of RNA polymerase II1, are sufficient to hijack this essential enzyme and drive neoplasia. POLR2A mutant tumors reveal dysregulation of key meningeal identity genes, including WNT6 and ZIC1/ZIC42,3. In addition to POLR2A, NF2, SMARCB1, TRAF7, KLF4, AKT1, PIK3CA and SMO4-8, we also report somatic mutations in AKT3, PIK3R1, PRKAR1A, and SUFU in meningiomas. Our results identify a role for essential transcriptional machinery in driving tumorigenesis and define mutually exclusive meningioma subgroups with distinct clinical and pathological features.

  Study EGAS00001001916

• Integrative molecular analysis of pediatric Anaplastic large cell lymphoma reveals subtypes with distinct immune suppression signatures.

  Anaplastic large cell lymphoma (ALCL) is a peripheral T-cell lymphoma accounting for 10–15% of all childhood lymphomas. While more than 90% of the ALCL cases contain ALK-rearrangement, these tumors possess significant inter-tumor molecular heterogeneity that contributes to distinct morphologic differences and clinical impact. To gain insight into the molecular heterogeneity within ALK+ ALCL, we performed whole-exome sequencing, RNA-sequencing, and methylome analysis of 42 primary pediatric ALK+ ALCL patients. Our data showed that ALK+ALCLs was subclassified into two subtypes based on ALK gene expression, methylation profiles, and somatic mutation patterns. ALK-low samples had more highly methylated gene regions while enriched with immune infiltration. ALK-high samples were enriched with somatic copy number alteration and high expression of MYC and PD-L1. These data indicate that ALK expression, somatic mutations, and aneuploidy status are negatively associated with immune infiltration, stipulating that ALK expression status might be associated with resistance to immune checkpoint inhibitors.

  Study EGAS00001004189

• A multicenter study of susceptibility genes to type 1 diabetes

  The first genome-wide association study of fulminant type 1 diabetes mellitus was performed in Japanese individuals. As previously reported using a candidate gene approach, a strong association was observed with multiple SNPs in the HLA region, and the strongest association was seen for rs9268853 in the class II DR region (P=1.56 x 10-23, odds ratio [OR] 3.18). In addition, rs11170445 in CSAD/lnc-ITGB7-1 on chromosome 12q13.13 showed an association at a genome-wide significance level (P=7.58 x 10-9, OR 1.96). Fine mapping of the region revealed that rs3782151 in CSAD/lnc-ITGB7-1 showed the lowest P value (P=4.60 x 10-9, OR 1.97 [95% CI 1.57-2.48]). The risk allele of rs3782151 is a cis-expression quantitative trait locus (eQTL) for ITGB7 that significantly increases the expression of this gene. CSAD/lnc-ITGB7-1 was strongly associated with the susceptibility to fulminant, but not classical autoimmune, type 1 diabetes, implicating this locus in the distinct phenotype of fulminant type 1 diabetes.

  Study JGAS000144

• Genetic Markers of Caries Risk in Diverse Underserved Children: CIDR

  The study Predicting Caries Risk In Underserved Children, From Toddlers To The School-age Years In Primary Healthcare Settings, is a renewal of an initial project designed to develop a dental caries risk tool for use in primary medical and dental healthcare settings to identify high dental caries risk children, expanding from the toddler (1-4 years old, referred to as Stage 1 grant) to the school-age years (6-9 years old, referred to as Stage 2 grant); and to determine the relationships between dental caries risk profiles and dental caries disease patterns. 1326 children, 12 +/- 3 months of age, and their primary caregivers, were enrolled in the study. This cohort represents a diverse population, including ethnic and racial minorities and low socio-economic status groups. There are a total of six in-person visits (at child age 1, 2.5, 4, 6.5, 8 and 9.5 years), and at each one the primary caregiver (PCG) completes a dental caries risk questionnaire, and the child receives a detailed dental caries examination. Saliva samples were collected during the age 8 visit (2019-2020) from 1,059 racially and ethnically diverse individuals (543 children and 516 PCGs) for the purposes of human genetic testing, to study the genetics of dental caries experience of children and their primary caregivers.

  Study phs003280

• ERG ALTERATIONS DEFINE A NOVEL SUBTYPE OF ACUTE LYMPHOBLASTIC LEUKEMIA

  Structural chromosomal alterations are a hallmark of acute lymphoblastic leukemia (ALL) yet many patients lack an identifiable abnormality on conventional cytogenetic analysis. Here, using integrated analysis of genome-wide DNA copy number and gene expression data of 1764 childhood and adult ALL cases, including whole-genome, exome and mRNA-sequencing of 72 cases, we report a novel subtype of B-progenitor ALL (B-ALL) representing 4-13% of B-ALL cases characterized by a distinct gene expression profile, and focal deletions of ERG (ETS related gene) in 56% of cases. These cases are characterized by expression of a ERG transcript that utilizes a novel exon in intron 6 of ERG spliced to the canonical reading frame of ERG exons 7-10, encoding a 27 kDa C-terminal ERG protein that retains the ETS and transactivating domains but lacks the N-terminal pointed and regulatory domains. This protein is a competitive inhibitor of wild-type ERG and is leukemogenic in vivo. ERG-altered ALL cases have a favourable outcome despite the presence of alterations associated with poor prognosis in non-ERG ALL, such as deletions of IKZF1. These findings identify a new subtype of leukemia characterized by a novel mechanism of ETS transcription factor dysregulation in cancer.

  Study EGAS00001000514

• T cell landscape definition by multi-omics identifies galectin-9 as novel immunotherapy target in chronic lymphocytic leukemia (CLL)

  Failure of immunotherapy after applying checkpoint inhibitors or CAR-T cells is linked to T cell exhaustion. Here, we explored the T cell landscape in chronic lymphocytic leukemia (CLL) by single-cell omics analyses of blood, bone marrow and lymph node samples of patients and spleen samples of a CLL mouse model. By single-cell RNA- sequencing, mass cytometry (CyTOF), and multiplex image analysis of tissue microarrays, we defined the spectrum of phenotypes and transcriptional programs of T cells and and their differentiation state trajectories. We identified disease-specific accumulation of distinct regulatory T cell subsets and T cells harboring an exhausted phenotype exclusively in the CLL lymph node tissue. Integration of TCR data revealed a clonal expansion of CD8+ precursor exhausted T cells, suggesting their reactivity for CLL cells. Interactome analyses identified the TIM3 ligand Galectin-9 as novel immunoregulatory molecule in CLL. Blocking of Galectin-9 in CLL-bearing mice slowed down disease development and reduced the number of TIM3 expressing T cells. Galectin-9 expression correlated with shorter survival of CLL patients. Thus, Galectin-9 contributes to immune escape in CLL and represents a novel target for immunotherapy.

  Study EGAS00001006864

• Transcriptomic Profiling of Peripheral Immune Cells in a Trial of Ruxolitinib with Nivolumab for Anti-PD1 Non-Responsive cHL

  Treatment with checkpoint inhibitors is effective in multiple cancer types. However, even in cancers with high response rates such as Hodgkin lymphoma, some patients fail to respond or relapse following an initial response to checkpoint inhibitors. In this study, we examined patients enrolled in a clinical trial of ruxolitinib with nivolumab in relapsed or refractory Hodgkin lymphoma (NCT03681561). Patients relapsed or refractory to anti-PD1 therapy received ruxolitinib for 8 days followed by nivolumab every 4 weeks and continued ruxolitinib twice daily. For this transcriptomic study, peripheral blood mononuclear cells (PBMCs) were collected at baseline and 8 days of ruxolitinib therapy and analyzed by single-cell and bulk RNA-sequencing.

  Study phs003601

• RNA sequencing data of pediatric BCR::ABL1 acute lymphoblastic leukemia

  The BCR::ABL1 fusion results from the t(9;22)(q34;11.2) translocation, also known as the Philadelphia chromosome. In children, BCR::ABL1-positive leukemia is rare, accounting for approximately 3% of cases. The BCR::ABL1 oncoprotein activates multiple signaling pathways that drive cell proliferation. Historically, this subtype was associated with an extremely poor prognosis; however, the incorporation of tyrosine kinase inhibitors into therapy has markedly improved outcomes, with overall survival now approaching 80% in pediatric patients. Relapse most commonly occurs through the emergence of clones harboring kinase domain mutations, yet 30–40% of relapses arise in the absence of such mutations, a phenomenon that remains poorly understood.

  Study EGAS50000001798

• Genomic catastrophes frequently arise in esophageal adenocarcinoma and drive tumorigenesis.

  Oesophageal adenocarcinoma (EAC) incidence is rapidly increasing in Western countries. A better understanding of EAC underpins efforts to improve early detection and treatment outcomes. While large EAC exome sequencing efforts to date have found recurrent loss-of-function mutations, oncogenic driving events have been underrepresented. Here we use a combination of whole-genome sequencing (WGS) and single-nucleotide polymorphism-array profiling to show that genomic catastrophes are frequent in EAC, with almost a third (32%, n=40/123) undergoing chromothriptic events. WGS of 22 EAC cases show that catastrophes may lead to oncogene amplification through chromothripsis-derived double-minute chromosome formation (MYC and MDM2) or breakage-fusion-bridge (KRAS, MDM2 and RFC3). Telomere shortening is more prominent in EACs bearing localized complex rearrangements. Mutational signature analysis also confirms that extreme genomic instability in EAC can be driven by somatic BRCA2 mutations. These findings suggest that genomic catastrophes have a significant role in the malignant transformation of EAC.

  Study EGAS00001000750

• Targeted Sequencing of Human Myeloid Malignancies

  This study involves targeted sequencing of samples from myeloid malignancies at different timepoints to assess clonal evolution of malignancy a. 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 EGAD00001002225

• Woodcock et al TenMenDeep Study EGA Dataset A

  Woodcock et al TenMenDeep EGA Dataset A. These are Illumina based deep sequencing data based on bait capture sequencing. See Woodcock et al methods for more detail. Note: the Amplicon sequencing data type is selected because the EGA Website currently has no option to select Bait Capture Sequencing or similar.

  Dataset EGAD00001005381

• Woodcock et al TenMenDeep Study EGA Dataset B

  Woodcock et al TenMenDeep EGA Dataset B. These are Illumina based deep sequencing data based on bait capture sequencing. See Woodcock et al methods for more detail. Note: the Amplicon sequencing data type is selected because the EGA Website currently has no option to select Bait Capture Sequencing or similar.

  Dataset EGAD00001005382

• Ancestry and somatic profile predict acral melanoma origin and prognosis – RNA

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015756

• UROMOL 2020 - RNA-seq data validation

  For this project about non-muscle invasive bladder cancer (NMIBC), we analysed total RNA-seq data from 47 patients used for validation. Sequencing of total RNA was performed using KAPA RNA HyperPrep Kit with RiboErase HMR (Roche). RNA input was 100 to 500 ng. The dataset is composed of 94 fastq files.

  Dataset EGAD00001006967

• Single cell RNAseq and TCRseq data from tumor and blood samples from 4 patients with muscle invasive bladder cancer

  For this dataset we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients. This dataset contains 4 tumor samples as well as 4 blood samples. Each sample is made up of 2 sets of paired fastq files. The first pair contains reads corresponding to RNA transcripts (_Transcripts in file name), while the second pair contain reads corresponding to TCRs (_VDJ in file name). Sequenced on the Illumina NovaSeq6000 platform in a paired-end run using an SP flow cell (v1.5, 300 cycles).

  Dataset EGAD50000001381

• Glioblastoma stem cell lines RNA-seq (Guilhamon et al.)

  RNA was extracted from GSCs using the Qiagen RNeasy Plus kit. RNA sample quality was measured by Qubit (Life Technologies) for concentration and by Agilent Bioanalyzer for RNA integrity. All samples had RIN above 9. Libraries were prepared using the TruSeq Stranded mRNA kit (Illumina). Two hundred nanograms from each sample were purified for polyA tail containing mRNA molecules using poly-T oligo attached magnetic beads, then fragmented post-purification. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This is followed by second strand cDNA synthesis using RNase H and DNA Polymerase I. A single “A” base was added and adapter ligated followed by purification and enrichment with PCR to create cDNA libraries. Final cDNA libraries were verified by the Agilent Bioanalyzer for size and concentration quantified by qPCR. All libraries were pooled to a final concentration of 1.8nM, clustered and sequenced on the Illumina NextSeq500 as a pair-end 75 cycle sequencing run using v2 reagents to achieve a minimum of ~40 million reads per sample.

  Dataset EGAD00001006813

• Whole Exome Sequencing of controls performed at the Broad Institute on a cohort from Bristol, UK

  These data were generated as part of a collaboration between University of Bristol, UK and the Stanley Center at the Broad Institute. This project sequenced and analysed the whole exomes of 2969 samples from the Avon Longitudinal Study of Parents and Children (ALSPAC). ALSPAC is a population-based pregnancy cohort with participants acting as ‘controls’ for this project. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina NovaSeq 6000 machines producing CRAM files. ALSPAC recruited pregnant women in the Avon County of south-west England between 1991 and 1992. Of the 15,447 pregnancies, 14,901 children were alive at 1 year of age.  DNA was extracted from child blood samples taken between ages 7 and 24.

  Dataset EGAD50000000716

• Detection and Targeting of Splicing Deregulation in Pediatric Acute Myeloid Leukemia Stem Cells

  This study evaluates the gene expression and splicing changes between pediatric patients with and without Acute Myeloid Leukemia (AML) and pediatric and adult patients with AML. We obtained bone marrow or peripheral blood from patients and isolated CD34+ stem and/or progenitor cells from pediatric patients with AML (10) or without AML (6) and adult patients with AML (5). In parallel, a targeted analysis for known, deleterious, genetic mutations in the KRAS, NRAS, and KMT2C genes identified 2, 5, and 6 AML patients with alterations, respectively. Additionally, Tapestri analysis further identified a mutation in the intronic region of the SF3B1 gene in multiple pediatric AML patients. RNA-Seq was performed on the purified cell populations at The Scripps Research Institute Next Generation Core on an Illumina NextSeq 500 sequencer with 150bp paired-end reads.These datasets revealed that, similar to adult AML, pediatric AML samples were enriched for Leukemia Stem Cells (LSC) markers. A deeper analysis showed widespread dysregulation of splicing in pediatric AML samples compared to age-matched non-leukemic samples. In addition, the splicing regulator RBFOX2 was downregulated with an accompanying increase in specific CD47 splice isoforms in the pediatric AML samples. Thus, the increased presence of LSCs in pediatric AML is possibly driven by global splicing deregulation, and the treatment with splicing modulators like Rebecsinib has a potential therapeutic value for eradicating LSCs in these patients.

  Study phs003196

• Successful BRAF/MEK-inhibition in a young patient with BRAF V600E-mutated extrapancreatic acinar cell carcinoma (HIPO-021)

  Pancreatic acinar cell carcinoma (PAC) is a rare disease with a poor prognosis. Treatment options for metastatic PAC are limited and often follow chemotherapeutic regimens for pancreatic ductal adenocarcinoma. Although recurrent genomic alterations, such as BRAF fusions and defects in genes involved in homologous recombination DNA repair, have been described in PAC, data on the clinical efficacy of molecularly guided, targeted treatment are scarce. Here we describe the case of a 27-yr-old patient with BRAF V600E-mutated PAC who was successfully treated with a combination of BRAF and MEK inhibitors. The patient presented to our clinic with abdominal pain and weight loss. Imaging showed extensive retroperitoneal disease as well as mediastinal lymphadenopathy. Because of elevated alpha-fetoprotein (AFP) levels and inconclusive histologic findings, a germ cell tumor was suspected; however, PEI chemotherapy was unsuccessful. A repeat biopsy yielded the diagnosis of PAC and treatment with FOLFIRINOX was initiated. Comprehensive molecular profiling within the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) precision oncology program revealed a somatic BRAF V600E mutation and a germline PALB2 stop-gain mutation. Therapy was therefore switched to BRAF/MEK inhibition, resulting in almost complete remission and disease control for 12 mo and a remarkable improvement in the patient's general condition. These results indicate that BRAF alterations are a valid therapeutic target in PAC that should be routinely assessed in this patient population.

  Study EGAS00001004282

• Study on the Genetics of Alcoholism (COGA): African American Family GWAS

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative African American families were selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Omni2.5_080814_1 chip to genotype 3,438 subjects selected from densely affected families. Genotyping was performed at CIDR. This sample complements a set of densely affected European American families previously made available under dbGaP study accession phs000763. In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2.For version 3, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings, Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance abuse variables are made available in version 3. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study (phs000125). GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data (phs000763). GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS (phs000976). GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS (phs001208). GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000976

• Genetic and epigenetic variation at regulatory regions contribute to cancer evolution under endocrine treatment

  Comprehensive profiling of hormone-dependent breast cancer (HDBC) has identified hundreds of protein-coding alterations contributing to cancer initiation, but only a handful have been linked to endocrine therapy resistance, potentially contributing to 40% of relapses. If other mechanisms underlie the evolution of HDBC under adjuvant therapy is currently unknown. In this work, we employ integrative functional genomics to dissect the contribution of cis-regulatory elements (CREs) to cancer evolution by focusing on 12 megabases of non-coding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Massive parallel perturbation in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance9. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies non-coding changes involved in therapy resistance. Overall, our data uncover actionable transient transcriptional programs critical for dormant persister cells and unveil new regulatory nodes driving evolutionary trajectories towards disease progression.

  Study EGAS00001006340

• Alzheimer's Disease Genetics Consortium (ADGC) Genome Wide Association Study -NIA Alzheimer's Disease Centers Cohort

  The National Institute on Aging (NIA) Alzheimer&#39;s Disease Centers (ADCs) cohort includes subjects ascertained and evaluated by the clinical and neuropathology cores of the 29 NIA-funded ADCs. Data collection is coordinated by the National Alzheimer&#39;s Coordinating Center (NACC). NACC coordinates collection of phenotype data from the 29 ADCs, cleans all data, coordinates implementation of definitions of AD cases and controls, and coordinates collection of samples. The ADC cohort consists of autopsy-confirmed and clinically-confirmed AD cases, and cognitively normal elders (CNEs) with complete neuropathology data who were older than 60 years at age of death, and living CNEs evaluated using the Uniform dataset (UDS) protocol who were documented to not have mild cognitive impairment (MCI) and were between 60 and 100 years of age at assessment. ADCs sent frozen tissue from autopsied subjects and DNA samples from some autopsied subjects and from living subjects to the National Cell Repository for Alzheimer&#39;s Disease (NCRAD). DNA was prepared by NCRAD for genotyping and sent to the genotyping site at Children&#39;s Hospital of Philadelphia. ADC samples were genotyped and analyzed in separate batches. [Reprinted from AC Naj et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer&#39;s disease. Nature Genetics 43, 436-441 (2011). doi:10.1038/ng.801. PMID: 21460841.]

  Study phs000372

• NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)

  ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID: 18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID: 20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID: 21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID: 24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252.

  Study phs001472

• Common early-life exposure of the colorectal epithelium to the microbiome-derived mutagen colibactin

  Colibactin is a mutagen produced by bacterial strains in the colorectal microbiomes of some healthy people. It generates somatic mutations characterised by the mutational signatures SBS88 and ID18 in normal human colorectal epithelial cells in vivo. Increasing prevalence of colibactin mutagenesis during the 20th century is hypothesised to have caused recent international increases in early-onset colorectal cancer incidence. Here, we establish the early-life prevalence, timing, mutation burdens and distribution through the colon of colibactin mutagenesis by sequencing normal colorectal epithelial cell genomes to detect SBS88 and ID18 in children and adolescents from the UK and Denmark biopsied between 2016 and 2024. Colibactin mutagenesis was found in ~40% individuals. It starts soon after birth and often ceases by age five years, although some children show longer exposures. Mutation burdens are higher in the left than right colon and show substantial variation between exposed individuals, in some causing &gt;100-fold increases in total mutation loads compared to unexposed children of the same age. Therefore, colorectal mutagenesis by colibactin is currently common in some populations, occurs during early childhood and can produce markedly elevated somatic mutation burdens. The future public health implications of this widespread mutagen exposure will depend on clarification of its role in colorectal cancer causation.

  Dataset EGAD00001015830

• Memory-like HCV-specific CD8+ T cells retain a chronic scar after cure of chronic HCV infection

  Chronic hepatitis C virus (HCV) infection is associated with CD8+ T-cell exhaustion characterized by limited effector functions and thus compromised anti-viral activity. Exhausted HCV-specific CD8+ T cells are comprised of memory-like and terminally exhausted CD8+ T-cell subsets. So far, little is not known about the molecular profile and fate of these cells after elimination of chronic antigen stimulation by direct acting antiviral therapy (DAA). Here, we report an antigen-driven molecular core signature underlying exhausted CD8+ T-cell subset heterogeneity in chronic viral infection with a progenitor/progeny relationship of memory-like and terminally exhausted HCV-specific CD8+ T cells via an intermediate stage. Furthermore, transcriptional profiling reveals that the memory-like cells remain after DAA-mediated cure while terminally exhausted HCV-specific CD8+ T-cell subsets are lost. Thus, the memory polarization of the overall HCV-specific CD8+ T-cell response after cure does not result from re-differentiation of exhausted T cells. Consequently, antigen elimination has little impact on the exhausted core signature of memory-like CD8+ T cells that remains clearly different from bona fide T-cell memory. These results identify a molecular signature of T-cell exhaustion that is imprinted like a chronic scar in HCV-specific CD8+ T cells even after HCV cure, highlighting the requirement of re-programming to elicit full effector potential of exhausted T cells.

  Dataset EGAD00001006259

• WGS and WES of 78 pairs Chinese gastric cancer

  Gastric Cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with 3 primary tumours and 2 matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC).

  Study EGAS00001001056

• WGS of cell-free DNA derived from plasma of CRC patients and healthy controls, and WGS of matched tumor tissue and saliva

  This dataset contains: 1.) Whole-genome sequencing (WGS) data (~6x) of 259 cfDNA samples obtained from 50 colorectal cancer (CRC) patients and 61 healthy controls. Paired-end sequencing was performed with 2x101 bp reads on the NovaSeq 6000 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38). 2.) WGS data (~1x) of 50 tumor biopsy and 45 saliva samples from CRC patients. Paired-end sequencing was performed with 2x101 bp reads on the NovaSeq 6000 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38).

  Dataset EGAD00001009309

• Intercepting Progression from Pre-Invasive to Invasive Lung Adenocarcinoma

  An improved understanding of the biology of lung cancer is needed to intercept the disease at an early point in its progression. In this project we have used multidimensional methods to profile the tumor microenvironment (TME) and to determine the crosstalk between cancer cells and the TME in pre-invasive to invasive human lung non-solid adenocarcinomas. Comparative analysis of the cellular and molecular events associated with the distinct histological stages will lead to identification of the critical events triggering progression and thereby identify targets to intercept disease progression. The data being submitted represents the genomic profiles of patient samples with pre-invasive and invasive human lung adenocarcinomas.

  Study phs002818

• Copy number profiles detected by shallow coverage WGS

  We performed shallow coverage whole genome sequencing on 147 glioma samples and analyzed their copy number profile. The coverage of each sample is about 2. Data are presented as VCF files which describe the copy number segments and their log2 ratio.

  Dataset EGAD00001005062

• NPY methylated ctDNA is a promising biomarker for treatment response monitoring in metastatic colorectal cancer

  Dac EGAC00001003001

• CD3 bispecific antibody-induced cytokine release is dispensable for cytotoxic T cell activity

  Study EGAS00001003734

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Cancer cells enter a reversible drug tolerant persister (DTP) state to evade death from both chemotherapies and targeted agents. It is increasingly appreciated that the DTP state is an important driver of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer xenograft models to identify and characterize the cancer cells capable of generating DTPs in response to standard-of-care chemotherapy. Barcode analysis revealed no loss in clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fits a mathematical model in which all cancer cells, and not a small subpopulation, possess an equipotent capacity to enter the DTP state. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides new insights into how cancer cells use a developmentally conserved mechanism to drive the DTP state pointing to novel therapeutic opportunities to target diapause-like DTPs.

  Dataset EGAD00001006849

• The effect of freezing delay of cell-type specific transcriptome responses in human brain via snRNA-seq

  In other analysis in the current manuscript, we find a similar gene signature (to dissociation based artifacts in mouse and human tissue) is present in post-mortem microglia and astrocytes, across all snRNA-seq datasets analyzed, although it is highly variable between subjects. ​ Using acutely-resected neurosurgical tissue, we performed single-nucleus RNA-seq and reveal that a similar signature can be detected in microglia following prolonged exposure to room temperature. Tissue handling and methods details, as well as sequencing and analysis details) can be found in the methods section of related manuscript (Marsh et al., 2022). Together, these results suggest that the presence of this signature in post-mortem brain samples may be the result of a combination of acute pre-mortem (agonal state, cause of death, comorbidities, etc.) and post-mortem (post-mortem interval (PMI), storage time, RNA quality, etc.) variables and may not represent normally present cell state.

  Dataset EGAD00001008541

• DAC Portal documentation

  DAC Portal Welcome to the DAC Portal documentation! If you are involved in governance or legal aspects, technical or operational aspects, or serving as a data steward, this page will be helpful for you. By exploring these materials, you can define your own Data Access Committee (DAC) and policies, understand the minimal requirements for a DAC and a policy object, and comprehend how the EGA data access requests are managed. DAC Portal Index Setting up your account DACs and Policies Pending Request table Manage Data Requests History page Audit your DACs, policies, and datasets Deprecation User Preferences DAC API - A programmatic approach Setting up your account Register yourself as an EGA user. The Helpdesk team will validate your account (this could take up to 48 hours). After validation, you will receive an email with a link to verify your email - Make sure you click on the link to verify your account! If you don’t receive the email, please check your spam folder. Once your account is active you can login to the DAC Portal. We recommend you to check out the Take The Tour! DACs and Policies Create a DAC Click on Create a DAC Add the title and description to your DAC. Once ready, click on the ‘Create’ button. You will have to wait until the Helpdesk Team validates the creation of your DAC. Once approved by Helpdesk, your DAC will be assigned with a persistent identifier (EGAC). Edit a DAC Once your DAC is registered and approved, you can edit it and add contacts. Remember, you can add as many contacts as needed. And, you can also remove/add contacts anytime. To add a contact, you must write the username or email of a registered EGA user in the Members field. Once you have typed the whole username or email, a drop-down menu will appear where you can select the contact. Select a contact from the drop-down menu. Make sure you write the full username or email of the contact so it appears as an option. Make sure that you select one main contact. Set up the role you want to grant to the new contact of the DAC. We recommend you to check out the FAQ to learn more about the different roles! After adding all the necessary contacts and assigning roles, click on Update. This will send an email notification to the new DAC member, letting them know about the invitation to managing the DAC. Once they log into the DAC Portal, they will be able to either accept or turn down the invitation. Create a policy First, please note that all information registered in a policy metadata object will be publicly available on the EGA website. For each released dataset, all users will be able to read the policy under the “Data Access” tab. Select Create a Policy from the Policies tab. Select the DAC that you want your policy to depend on. Add the title and terms and conditions for accessing and using your data. If you already have an external website for data access requests, you can add the URL directly here (see example here). You can find a template of a Data Access Agreement (DAA) document in our Policy documentation page. The DAA template is provided for guidance only and should be adapted to suit your own purpose depending on the security policies, terms for publication or embargoes, and restrictions on data use or sharing. You can also add Data Use Ontologies (DUO) to your policy. These DUO codes are used to semantically tag the terms and conditions of using the data linked to the policy (example). For more information, you can refer to the Data Uso Ontology documentation. Once completed, make sure to click the Create button in order to register your policy. A persistent identifier (EGAP) will be assigned automatically. Edit a policy Please, note that you will not be able to edit the policy if it shows in orange. Meaning that you are a member of the DAC linked to that policy. Members don’t have edit rights. Only admins can edit objects. You can check your registered policies on My policies, available at the menu in the top-right corner. Select your policy. It will then display the information of that policy, allowing you to edit the information. Once you are done with the modifications, click Update. Pending Requests Table Table Settings Upon selecting a specific DAC, you will be presented with a customisable table showcasing all pending data access requests. This table allows you to tailor the displayed information according to your preferences by selecting desired columns. Available Columns (Displayed with the Eye Icon): Date: The date when the data access request was submitted. Full Name: Name and surname of the user submitting the request. Email: Email address associated with the user's request. Username: The username linked to the EGA account of the user submitting the request. Organisation: Affiliated organisation of the user submitting the request. Dataset: EGA accession ID for the requested EGA dataset. Dataset Title: Title of the requested dataset. DAC Comment: Space provided for internal comments related to the request. Expiration: Option to specify an expiration date for granted permissions. Check more information on the pending request table here! Table Filters By default, all data access requests are displayed. However, you have the option to apply filters to refine your view. Follow these steps to apply filters: Click on the More button. This action will reveal the different columns available for applying filters. As you select columns, the checked fields will be displayed at the top of the request table. Choose the specific values within the selected columns that you want to filter for. Click the Search button to apply the selected filters. Do you find yourself frequently applying the same filters? You can save multiple combinations of filters for easy access at any time! Here's how: Click the Save button. Provide a descriptive name for the filter combination. Click Save to confirm. To load saved filters, simply select the saved filter from the dropdown menu to apply it automatically. Check more information on filters here! Advanced Search For users requiring more granular control over their data access requests, the DAC Portal offers an Advanced Search feature using JIRA Query Language (JQL). With JQL, you can craft precise and complex queries to filter and retrieve specific data access requests based on various criteria such as date, user details, dataset attributes, and more. Using JQL's flexibility, you can create custom queries to meet your specific needs, allowing for advanced filtering options beyond the standard filters provided. You can find the Advanced Search feature following these steps: Click the … button Select Advanced To view the allowed fields for filtering and explore all available options, simply click on the info icon. Once you have written the filtering values, click the Search button to apply. Check more information on filters here! Manage Data Requests Upon logging into the DAC Portal, you'll notice a sand clock icon next to the DAC ID, indicating the number of pending requests. Click on the DAC to review these requests. Accept requests Click on the right side of the toggle button to grant access to the user. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with granting permissions. Deny requests Click on the left side of the toggle button to deny access to the user. Provide a reason for the denial. Note that the user will receive an email with this reason. Click on the Done button. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with denying permissions. Tips! Apply a filter to view all requests to be managed at once. Use the toggle in the row with column names to grant or deny permissions for multiple requests simultaneously. You can grant and deny permissions in the same action, simplifying the process. The confirmation box will provide a summary of all actions, including grants, denials, DAC comments, and expiration dates. History Page The History page serves as a dedicated space to view information regarding all requests managed by all DAC members. Here, you can review active permissions and revoke them as needed. Go to the History page by clicking on the "HISTORY" button from a DAC page in the DAC Portal. Here are the different row types you may find: Current permissions: row in green with a toggle button to revoke permissions on the right. Approved requests: row in green, with no toggle button. Request denied: row in red with “request denied” on the right. Permission revoked: row in red with “permission revoked” on the right. Distinctions to Note! Between Request Denied and Permission Revoked: Request Denied: Refers to requests that were rejected from the outset, indicating that access to the dataset was never granted. Permission Revoked: Indicates that permissions were previously granted but have since been revoked. Users with permissions revoked have previously accessed the dataset. Between Approved Request and Current Permissions: Approved Request: Represents an entry when a data access request has been approved in the past. Current Permissions: Denotes ongoing permissions where a user has present access to the dataset. An approved request may now appear as Permission Revoked in the present. By observing these different rows, users can gain insight into the complete history of a user's interactions and permissions regarding a dataset over time. To revoke access to a specific user for a dataset, follow these steps: Go to History page Look for the row with the specific permissions. You can use the filters! Click on the toggle button to revoke access. Add a denial reason. Bear in mind that the requester will receive the denial reason! Click on the Apply button. Check more information on the Hisotry page here! Audit your metadata objects In the DAC Portal, you can efficiently manage and audit various metadata objects pertinent to your role as a Data Controller. Upon accessing the DAC Portal, you will encounter three primary tabs on the homepage: DAC: Contains information about Data Access Committees (DACs). Policies: Provides insights into linked policies. Datasets: Displays datasets and relevant details. Within each tab, you'll find a comprehensive list of the objects you manage, these being grouped by type (DAC, Policies, Datasets), as well as by your role (member/admin). Whilst the lists give you a quick look, to check how things are connected, we've added a table at the bottom DACs and policies. DACs Let’s check which policies are linked to a specific DAC: Go to "My DACs." Select a DAC. Click on "EDIT" to see more details. You are now on this page: Scroll down to see the linked policies. Click on “List of linked policies of this DAC” and you will see a list of all policies linked to your selected DAC. Policies Do you want to view a list of datasets connected to a particular policy? Follow the same steps mentioned earlier, but head to the policy tab this time. In the policy tab, you'll find a list of all your policies. Here, you may notice two different icons next to the policy ID (EGAP): DAC Icon (): This represents the DAC. Hover your mouse over the icon to see the DAC ID. Dataset icon (): This indicates datasets falling under that policy. The number next to the icon tells you how many datasets are linked to the policy. For example, if you see "2" next to the icon, it means there are two datasets linked to that policy. If you want to check the linked datasets and their relevant information, simply click on a specific policy. You'll then find the "List of linked datasets of this policy" at the bottom of the page. Datasets Finally, in the dataset tab, by default you will see a list of all the datasets you can manage with all your DACs and policies. Yet, we've included two handy ways to organise them: DAC vs. policy: You can group by datasets, either by DAC or policy. Released vs. unreleased: You can sort out datasets based on their release status. Feel free to experiment with both options! For instance, if you want to see which DACs have unreleased datasets, simply select DAC and unreleased, and you'll get the details you need! Deprecation Do you have a bunch of metadata objects like DACs and policies that you don’t need anymore? This section shows you how to get rid of them! But what does "deprecation" mean for EGA? It's basically changing the status of a metadata object to "deprecated," which means we won't be using it in the future. In simple terms, it's like saying these objects are no longer useful. However, because we believe in making metadata FAIR, once an object has a persistent identifier, we can't just delete it. So, instead of deleting, we deprecate it. Here's a helpful tip! If you want to make a metadata object disappear from the DAC Portal, deprecate it. You won’t see it in the portal anymore! Let’s say you want to deprecate a DAC. Let’s do it! Go to "My DACs." Select a DAC. Click "EDIT" to see more details. You are now in this page: Click on the Deprecate button It will then appear a message. There are two options here: Your DAC is not linked to any policy, hence it’s ready to be deprecated. Click on “Yes. Confirm” to deprecate your DAC object! Your DAC is linked to at least one policy, and you need to either: Deprecate the linked policy first, or Link the policy to a different DAC Now, let’s say you don’t want to get rid of the policy altogether, but you want to change the DAC it’s linked to. Here's how: Go to the policy tab. Find the policy you want to change (for example, EGAP50000000019). Choose a new DAC to link it to. Click on Update. See the Edit Policy section for more details. After ensuring that the DAC we want to deprecate isn’t linked to any policy, return to the "My DACs" section and follow the steps outlined previously. This will lead you to a confirmation message. You can only deprecate DACs and Policies. To deprecate a dataset, please contact our Helpdesk team. Check more information on how deprecation works here! User Preferences We have implemented email notifications in the DAC Portal. Here’s the complete list: DACs: Pending requests Approved by Helpdesk Rejected by Helpdesk DAC Invitation Requesters: Data access request approved Data access request denied Permissions revoked Upcoming expiration date As a DAC member, you will be able to decide whether you want to receive the DAC notifications or not. For that, go to the top-right corner menu, select User Preference. You will be able to decide whether you want to receive notifications for: Approved by Helpdesk Rejected by Helpdesk DAC Invitation For pending requests, you will be able to select how often do you want to receive the notification: Daily Weekly Fortnightly As a DAC member, you are responsible for managing data access requests. Consequently, you will receive notifications for pending requests. If you prefer not to manage these requests, please arrange to be removed as a contact for your DAC. Here's a tip! Do you have a pending request that you don’t want to receive a notification? Add a DAC comment! The EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! DAC API - A programmatic approach In addition to the new DAC Portal, we are excited to announce the release of the DAC API. This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can click the button below. Check out the DAC API specification!

  Documentation access/data-access-committee/dac-portal