Search Results - EGA European Genome-Phenome Archive

Bone Microarchitecture

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

Study phs002102

The Sea Islands Genetic Network (SIGNET): Identifying genetic contributors to diabetes and dyslipidemia in African Americans

Recent genome-wide association studies (GWAS) have successfully identified genetic variants that influence diabetes risk in European populations, however most do not have a major impact on diabetes risk in populations of African descent. The African American (AA) population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, low levels of admixture, and in general, consume a diet rich in saturated fats. We postulate that this unique combination of ancestral and environmental factors results in a more consistent penetrance of diabetes risk alleles, as well as enrichment of risk alleles of African origin. The existing DNA samples and rich phenotypic data from the Sea Island Families Project comprise a unique resource for genetic studies of type 2 diabetes and related metabolic traits such as dyslipidemia. Our central hypothesis is that the increased risk for T2DM in AA compared with European American (EA) is due, in part, to susceptibility alleles of African origin, and that these alleles can be identified using a GWAS. The Specific Aims are to: 1) Identify genetic risk factors for type 2 diabetes utilizing DNA samples and data from the Sea Island Families Project, Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited from SC, GA, NC, and AL; and a GWAS approach; 2) Identify genetic contributors to lipoprotein subclasses in African Americans using the lipoprotein subclass profile (particle size and concentration for multiple subclasses of VLDL, LDL, and HDL) assessed by NMR at LipoScience, Inc., and the GWAS data from Aim 1. The rationale for this project is that identification and validation of novel pathophysiological pathways and informed selection of candidate genes for diabetes risk will inform development of new, targeted prevention and treatment strategies in this underserved, high risk population.

Study phs000433

Foundation Medicine Adult Cancer Clinical Dataset (FM-AD)

The Foundation Medicine adult cancer clinical dataset consists of 18,004 unique solid tumor samples that underwent genomic profiling on a single uniform platform as part of standard clinical care. The dataset is derived from the FoundationOne® genomic profiling assay version 2 that interrogates exonic regions of 287 cancer-related genes and selected introns from 19 genes known to undergo rearrangements in human cancer. Genomic DNA samples were sequenced to over 500x median coverage, and custom computational analyses identified all classes of genomic alterations (base substitutions, insertions and deletions, copy number alterations, and rearrangements). Since matched normal tissue was unavailable for analysis, these data underwent additional filtering to enrich for cancer-related events. The reported data includes genomic alterations that are known and suspected tumor drivers, as well as variants of unknown significance. To preserve patient anonymity, all known or suspected germline variants were removed from the data unless known to be associated with cancer development. The dataset contains genomic alteration profiles generated by FoundationOne version 2 testing for adult cancer patients (over 18 y.o.), and represents a vast diversity of tumor subtypes, including many rare diseases not profiled as part of large-scale profiling efforts. Cases are grouped into 16 broad disease categories containing tumors from 162 unique disease subtypes. Since specimens were profiled as part of clinical care, limited clinical parameters were available, including age, gender, tissue of origin, % of tumor nuclei, and diagnosis. Publication of this dataset is intended to allow the broad scientific community access to this unique cohort for use in scientific research projects of common and rare types of cancer, both for generating leads regarding causal mechanisms as well as cross-testing and confirming existing hypotheses. A pediatric cancer clinical dataset consisting of data from 1,215 patients under 18 y.o. is available separately at: FOUNDATION MEDICINE

Study phs001179

National Institute of Neurological Disorders and Stroke (NINDS), Family Study of Essential Tremor (FASET), Identification of Susceptibility Genes for Essential Tremor

The Familial Study of Essential Tremor (FASET) was designed to identify susceptibility genes for Essential Tremor. ET is among the most common neurological diseases with a prevalence (age > 40 years) estimated to be 4.0% and prevalence in advanced age (> 90 years) exceeding 20%. ET, often referred to as "familial tremor", is generally regarded as a highly genetic disorder with families, with affected members over multiple generations, and twin studies show high concordance among monozygotic twins. Probands (affected with ET) and relatives were enrolled in a family study of ET at Columbia University, New York between 2011 - 2014. The study was approved by the Institutional Review Board at Columbia University and written informed consent was obtained from all enrollees. The criteria for enrollment were: 1) the proband had early-onset ET with age at onset < 50 years, 2) the proband had a diagnosis of definite or probable ET, 3) in addition to the proband, there were at least two affected relatives in the family, 4) additional affected and unaffected family members were willing to participate in the study, and 5) the families contained more than two affected individuals in different generations. Blood samples were also collected for genetic research. For the genetic analyses, we excluded enrollees that we or others had diagnosed with Parkinson's disease (PD) or dystonia. The final sample includes 52 families (52 probands [affected with ET]) and 155 relatives). The number of affected individuals enrolled per family ranged from 3 - 7 (mean = 4.1). Genetic samples from FASET were analyzed with whole genome SNP genotyping (for linkage analyses) and whole exome sequencing. It is hoped that this resource will better help researchers to understand the genetic causes of ET and underlying disease pathogenesis.

Study phs000966

Functional Significance of Prostate Cancer Risk-SNPs

Prostate Cancer (PrCa), the most frequently diagnosed solid tumor in men in the U.S., results in ~192,000 new cases and ~27,000 deaths per year. Although the variation of PrCa incidence is likely to be the result of several factors, there is a large body of literature that strongly implicates a genetic etiology. Genome-wide association studies (GWAS) have emerged as the most widely used contemporary approach to identify genetic variants (in particular SNPs) that are associated with increased risk of human disease. For PrCa, at least five GWAS have now been performed yielding a substantial number of well-validated SNPs that are associated with an increased risk of PrCa, and that number continues to grow. A significant problem for many of the PrCa risk-SNPs identified so far, however, is that they do not lie within or near a known gene and they have no obvious functional properties. These findings suggest that many (if not most) of these risk-SNPs will be located in regulatory regions that control gene expression rather than in coding regions that may directly affect protein function. Therefore, in order to define the functional role of currently known risk-SNPs, the target genes must first be identified. A promising strategy to address this problem involves the use of expression quantitative trait loci (eQTL) analysis. Unfortunately, most of the publically available SNP-Transcript eQTL datasets utilize lymphoblastoid cells with only a handful using tissue from target organs. Although useful, these datasets alone are unlikely to be sufficient. Recent studies have demonstrated that gene expression and gene regulation occur in both a tissue-specific and tissue independent fashion and suggest that a complete repertoire of regulatory SNPs can only be uncovered in the context of cell type specificity. To date, such a tissue-specific dataset for normal prostate tissue does not exist. In this study, we have constructed a normal prostate tissue specific eQTL data set.

Study phs000985

ARDSnet and the iSPAAR Consortium: Genomic Basis of Susceptibility and Outcomes in Patients with the Acute Respiratory Distress Syndrome (ARDS)

Acute Respiratory Distress Syndrome (ARDS)/ Acute Lung Injury (ALI) is a syndrome defined by the presence of acute hypoxemic respiratory failure, bilateral pulmonary infiltrates on chest radiograph, a known clinical risk factor (e.g. sepsis, pneumonia, trauma, gastric fluid aspiration, pancreatitis, massive transfusion), and the absence of physiologic or clinical evidence of congestive heart failure. The Identification of SNPs Predisposing to Altered ALI Risk (iSPAAR) study is a multi-institutional cooperative study, funded through the NHLBI Recovery Act, that assembled samples and phenotype information from existing cohorts. The consortium included samples from patients with ARDS from the NIH NHLBI ARDS Clinical Trials Network (ARDSNet). Samples were obtained from 3 interventional treatment trials in patients with ARDS, including the Fluid and Catheter Treatment Trial (FACTT), the Albuterol to Treat Acute Lung Injury (ALTA) trial, and the Omega-3 Fatty Acid/Antioxidant Supplementation for ALI trial (Omega). In addition to ARDSnet samples, samples from the other cohorts included cases of established ARDS but also controls: critically ill patients who were at-risk for ARDS but who did not develop ARDS during their hospital course. These cohorts included the Molecular Epidemiology of Acute Respiratory Distress (MEA) Study enrolled at the Harvard University/Massachusetts General Hospital, the Systemic Inflammatory Immune Response Syndrome (SIRS) Patient Database and ICU Traumatic Injury cohorts from Harborview Medical Center, and cohorts collected from the ALI research programs at the University of Pennsylvania and the University of California, San Francisco. The Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000631 ARDSnet iSPAAR Consortium. phs000334 ESP_LungGO_ALI phs000686 ALI_GeneticRisk

Study phs000631

POPRES: Population Reference Sample

POPRES version 1 and 2 Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost-effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetic research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This resource was initially genotyped using the Affymetrix 500K SNP panel. This project includes nearly 6,000 subjects of African American, East Asian, South Asian, Mexican, and European origin. POPRES version 3 The discovery and development of novel drugs is challenging and with high attrition rates. Selection of the right target and optimal indications for novel therapeutics represent key decision points in this process, and are often hampered by our limited understanding of the biology of the target in humans. Building a robust body of knowledge of variation within drug target genes has in several cases increased the probability of success for novel therapeutics. Our knowledge of variation within drug target genes and their influence on traits of medical interest is still very limited. In an effort to fill this gap, we resequenced the exons of 202 known or suspected drug target genes in over 16,000 well-phenotyped individuals. A total of 863,883 bases were targeted, including 351 kb of coding and 323 kb of untranslated exon regions. The sequenced subjects included 3,381 from two studies that were part of the Population Reference Sample (POPRES) project: CoLaus (N = 2,059) and LOLIPOP (N = 1,322). Genotyping data generated through the targeted next generation sequencing is available through the dbGaP.

Study phs000145

Childhood Cancer Data Initiative (CCDI): Genomic Analysis in Pediatric Malignancies

Pediatric solid tumors are highly heterogeneous, encompassing a large number of histotypes. The genomic landscape of these diseases is characterized by few single-nucleotide variants (SNVs) compared to adult cancers. In contrast, many exhibit a high prevalence of structural or epigenetic changes that alter gene expression, underlining the need for comprehensive genomic approaches such as whole-genome sequencing (WGS). Several studies have specifically addressed the clinical utility of genomic analysis in the pediatric and AYA cancer setting. Review of these studies point to key challenges that must be addressed in order to advance the routine use of genomics in this population. We have established a large collection of solid tumor tissue samples through our biobanking efforts. Where possible, we obtain longitudinal samples from the same patient. These primary patient samples and their corresponding germline have been analyzed using whole genome and whole transcriptome sequencing methods and have been linked to clinical metadata using both manual curation and robust methods for automatic extraction from the electronic health record (EHR). Importantly, research-grade genomic analysis is performed in parallel to our CLIA-grade sequencing (“UCSF500”) efforts for some of the patients in this study cohort and have been submitted as part of the American Association for Cancer Research's project GENIE and/or the National Childhood Cancer Registry. For our sequenced tumor samples, we have retrospective clinical data and ongoing efforts to prospectively record key events throughout the patient's cancer journey. In our solid tumor program, we have developed many patient-derived xenograft models and a number of PDX-derived cell lines. These unique models have been evaluated using genomic and functional approaches including (in some cases) treatment with conventional chemotherapy or investigational agents. Lastly, these samples were collected from a population that is among the most diverse in the nation and includes significant numbers of Asian, Latino, Indigenous and African-American patients, groups that are traditionally underrepresented in many banking efforts.

Study phs002430

GATA2 Deficiency and the MonoMAC Syndrome

The aim of this study was to identify the germline mutation(s) in an extended family with individuals having MonoMAC Syndrome/GATA2 deficiency but lacking a canonical GATA2 mutation. GATA2 deficiency patients develop bone marrow failure, severe immunodeficiency and may progress to myeloid malignancies, including myelodysplastic syndrome (MDS), acute myeloid leukemia (AML), and chronic myelomonocytic leukemia (CMML). The definitive treatment for GATA2 deficiency is a bone marrow transplant. Approximately 90% of GATA2 deficiency patients have a known de novo or inherited germline mutation in the GATA2 gene, but ~10% have no identified mutation. The study was initiated with the first patient and her second cousin, both of whom were treated for MonoMAC Syndrome and received bone marrow transplants at the NIH. Pedigree analysis and clinical evaluation identified the individuals in several generations of these patients' near and distant relatives who are/were presenting or carrying the disease manifestations of GATA2 deficiency. Whole Genome Sequencing (WGS) was employed on these patients' two related nuclear families to identify variants that segregated with the disease trait and carrier status of their families. Genotyping was confirmed with direct DNA sequencing of these and other family members within the extended family across generations. A single base adenine-to-thymidine change was identified in a highly conserved enhancer element ~117,000 bp upstream of the GATA2 gene. It creates a new Composite Element, a DNA motif known to be critical in the regulation of hematopoiesis. This variant is unique to this family and is not present in dbSNP or other variant databases. It segregates with the disease trait and obligate carriers throughout a large pedigree. In vitro studies show that this variant drives allele-specific overexpression of the GATA2 gene in cultured cells and luciferase assays. The WGS sequence from the nuclear families will be shared on dbGaP.

Study phs003269

Adult Eosinophilic Esophagitis Registry Atlas

Eosinophilic esophagitis (EoE) arises in the setting of type 2 cytokine-driven inflammation, is characterized by the infiltration of eosinophils in the esophageal mucosa, and is associated with dysphagia and fibrostenotic complications. Disease development and progression involve complex interactions between epithelial cells, stromal cells and immune cells. Indeed, increased epithelial permeability is consistently found in EoE, potentially leading to increased antigen exposure and inflammation. Persistent inflammation can in turn lead to fibroblast activation and fibrosis, which, together with the mediators produced by eosinophils and mast cells, leads to dysmotility. To decipher the interactions between these cell types across distinct disease states, we obtained biopsies from 7 healthy controls and 15 EoE subjects, including both active disease and clinical remission, to perform single cell RNA-sequencing (scRNA-seq).Each biopsy sample was enzymatically digested within 3 hours of collection with collagenase/dispase to generate a single cell suspension. Suspensions were then loaded on a 10x Chromium controller, and libraries were generated with the 3' Chemistry pipeline (v2 or v3) before sequencing on an Illumina sequencer. The resulting sequence data was demultiplexed and analyzed with the CellRanger pipeline to generate raw fastq files and processed gene-count matrices for each sample. Altogether, our study generated transcriptomic profiles from 421,312 individual cells after quality control and filtering.Our analyses reveal 60 cell subsets and functional alterations in cell states, compositions, and interactions that highlight previously unknown features of EoE. Active disease displayed enrichment of ALOX15+ macrophages, novel PRDM16+ dendritic cells expressing the EoE risk gene ATP10A, and cycling mast cells, with concomitant reduction of TH17 cells. Receptor–ligand expression uncovered eosinophil recruitment programs, increased fibroblast interactions in disease, and IL-9+IL-4+IL-13+TH2 and endothelial cells as potential mast cell interactors. Resolution of inflammation-associated signatures included mast and CD4+ Tissue-resident memory T (TRM) cell contraction and cell type-specific downregulation of eosinophil chemoattractant, growth, and survival factors.

Study phs003574

Genomic Basis of Phenotypic Variability of Complex Disorders

The 520-kbp deletion on chromosome 16p12.1 is associated with multiple neurodevelopmental outcomes, including intellectual disability/developmental delay (ID/DD), schizophrenia, autism, and epilepsy. This variant is inherited in >95% of cases from carrier parents manifesting neuropsychiatric features, while affected children with the deletion were more likely to carry another large Copy Number Variation (CNV) or rare deleterious mutation elsewhere in the genome, or "second-hits", compared to carrier parents. Thus, while the 16p12.1 deletion confers significant risk for a range of disorders, the ultimate phenotypic trajectory is determined by "second-hit" variants in the genetic background. However, outstanding questions remain about the genetic background in these disorders, including the functional effects of "second-hit" variants towards gene expression or developmental phenotypes, the full spectrum of "second-hit" variants, and the mechanisms driving accumulation of these variants.In version 1, we performed deep clinical phenotyping, whole-genome sequencing (WGS), SNP microarray analysis, and RNA-sequencing of lymphoblastoid cell lines of 32 individuals in five large families with the 16p12.1 deletion. We found that specific classes of rare single-nucleotide and structural variants in coding and non-coding regions contributed towards expression changes in affected children based on their inheritance patterns, including a subset of variants that acted synergistically with the deletion to alter expression. We further found that rare variant-mediated expression changes contribute to specific developmental phenotypes in the carrier children, suggesting a potential genetic mechanism for variable expressivity of the deletion.In version 2, we additionally analyzed genetic and phenotypic data from individuals with 16p12.1 deletion and their spouses to assess the role of assortative mating modulating phenotypic outcomes of the 16p12.1 deletion. We identified significant within- and cross- disorder phenotypic correlations between spouses, but observed no significant genetic correlations between spouses, in line with expectations.

Study phs002450

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

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

Blog fega-affiliates-q&a

Circulating kidney injury molecule-1 (KIM-1) and association with response to adjuvant immunotherapy in renal cell carcinoma

Adjuvant immunotherapy is currently the standard of care for patients with resected renal cell carcinoma (RCC) at increased risk of recurrence, but there are no biomarkers available to guide treatment decisions. Kidney injury molecule-1 (KIM-1) has previously been described as a potential circulating biomarker in renal cell carcinoma. We evaluated biomarkers and outcomes among patients who participated in a randomized phase III trial of adjuvant atezolizumab versus placebo in resected RCC (IMmotion010). This trial did not meet its primary DFS endpoint in the intention-to-treat population. An affinity-based proximity extension proteomics assay was used to compare levels of circulating proteins among baseline (post-nephrectomy) serum samples and also with samples taken at time of recurrence. We demonstrate that serum KIM-1 was the most significantly enriched protein at recurrence versus baseline. Patients with serum KIM-1high at baseline had worse disease-free survival (DFS) (hazard ratio 1.68, 95% CI 1.35-2.09), but also had improved DFS when treated with adjuvant atezolizumab versus placebo (hazard ratio 0.72, 95% CI 0.52-0.99). An increase in KIM-1 during follow-up was associated with worse DFS compared to patients with no increase in KIM-1. Comparison of transcriptomic expression profiles in paired primary and recurrent tumor samples revealed that metastatic recurrence is associated with upregulation of transcriptional programs associated with tumor proliferation and myeloid immune suppression. Downregulation of an MHC class I signature was seen among patients with recurrence after treatment with atezolizumab but not placebo, suggesting this is a mechanism of resistance to PD-L1 immunotherapy. These analyses suggest that elevated post-nephrectomy serum KIM-1 enriches for benefit from adjuvant immunotherapy in RCC, and that biomarker driven adjuvant therapy should be evaluated as a potential new paradigm in RCC trials.

Study EGAS50000001285

Genetic_Heterogeneity_of_the_familial_gastric_neuroendocrine_tumors

Gastric neuroendocrine tumors (gNETs) occur with an estimated frequency of 2 per 100,000 in the general population. Type I gastric neuroendocrine tumors (NETs) represent the 75% of gNTEs and arise from gastric enterochromaffin-like (ECL) cells. They have late age of onset and usually benigh course. Classically, hypergastrinemia in patients who have autoimmune atrophic gastritis, causes hyperplasia of gastric ECL cells that progresses into type I gastric NETs and parietal cell (PC) destruction. The genetic bases in families with this disease are unknown. We performed an exome sequencing study of an atypical aggressive familial gNETs case (with early age onset, nodal infiltrations and gastric adenocarcinomas) that followed a recessive model. We identified a deleterious mutation in homozygosis in the ATP4A gene, which encodes the proton pump responsible for acid secretion by gastric parietal cells. This mutation lead to achlorhydria first, and hypergastrinemia and gNET developing as consequence (Calvete et al. 2014). Recently, two more families with gNETs, classical clinical traits and recessive model have been studies by WES but we didn't find any mutation in the ATP4a gene. However, putative mutations affecting genes that contribute to the development and the integrity of PC have been found suggesting that genetic alterations associated to this disorder target to a unique cell type (parietal cells). In order to cinfirm this hypothesis, it is necessary the search for new genes implicated in the gNETs, more familial cases are needed to be studied. We have identified four more new familial gNETs cases. Here, we propose their study by WES. The first family is formed by thress siblings with gNETs. The other families include two siblings with gNETs. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002273

Exome Sequencing to Define the Landscape of Plasma Cells in Systemic Light chain Amyloidosis

Systemic light chain amyloidosis (AL) is characterized by the deposition of immunoglobulin light chains as amyloid fibrils in different organs, where they form toxic protein aggregates. The underlying disease is a plasma cell disorder, but limited whole exome data are available. We report the findings of an exome sequencing study in AL to define a plasma cell signature and compare this to monoclonal gammopathy of undefined significance (MGUS) and myeloma (MM). Twenty-four samples from unselected newly diagnosed untreated AL patients were analysed. CD138+ cells were isolated from bone marrow cells using MACSorting (Miltenyi Biotech, Bisley, UK). Cells were lysed in RLT+ buffer and DNA/RNA extracted using the AllPrep kit (Qiagen, Manchester, UK). Peripheral blood was isolated from patients, white blood cells purified by Ficoll-Pacque and DNA extracted using the QIAamp DNA mini kit (Qiagen). There were a median of 47 acquired nonsynonymous variants (range 4-253) per patient. Thirty percent of patients yielded a mutation in a myeloma driver gene. These mutations were either clonal or sub-clonal. There was evidence of MAPK activation with NRAS mutations, NF-κB activation and DNA repair pathway alterations. Exome data were used to determine the cytogenetic groups of AL samples and identified hyperdiploidy in 33% of cases and t(11;14) in 33% of cases. All translocations were generated via class switch recombination and breakpoints on chromosome 11 fell into the expected regions. A novel translocation, unlikely to be driving disease progression was identified involving RCC1. Finally, further analysis of the APCS gene encoding for the SAP protein did not show any biased genotype in the AL population in comparison to the general population. We conclude that exome sequencing identifies a genetic make-up of AL that is similar to other plasma cell disorders such as MM and MGUS. This not only includes copy number abnormalities and translocations but also nonsynonymous mutations.

Study EGAS00001001418

Local In Time Statistics for processual research

Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

Study EGAS00001002520

Liver biopsy derived induced pluripotent stem cells provide an unlimited supply for the generation of patient-specific hepatocyte-like cells

Background: Hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs) have emerged as a promising cell culture model to study metabolism, biotransformation, viral infections and genetic liver diseases. However the derivation of iPSCs is restricted by ethical and procedural constraints. Furthermore, incomplete HLC differentiation remains a major challenge. iPSC may carry-on a tissue of origin dependent expression memory influencing iPSC differentiation into different cell types. If liver derived iPSCs (Li-iPSCs) maintain a liver specific gene expression profile is not known. It is also not known, if Li-iPSCs would allow the generation of more fully differentiated HLCs.Methods: Primary liver cells (PLCs) were expanded from liver needle biopsies and reprogrammed into Li-iPSCs using a non-integrative Sendai virus-based system. Li-iPSCs were differentiated into HLCs using established differentiation protocols. The HLC phenotype was characterized at the protein, functional and transcriptional level. RNA sequencing data were generated from the originating liver biopsies, the Li-iPSCs, fibroblast derived iPSCs, and differentiated HLCs, and used to characterize and compare their transcriptome profiles.Results: PLCs were obtained from small pieces of liver biopsies and could be reprogrammed into Li-iPSCs. Li-iPSCs indeed retain a liver specific transcriptional footprint. Li-iPSCs can be propagated to provide an unlimited supply of cells for differentiation into Li-HLCs. Similar to HLCs derived from fibroblasts, Li-HLCs could not be fully differentiated into hepatocytes. Relative to the originating liver, Li-HLCs showed lower expression of liver specific transcription factors and increased expression of genes involved in the differentiation of other tissues.Conclusions: PLCs and Li-iPSCs obtained from small pieces of human needle liver biopsies constitute a novel unlimited source for the production of HLCs. Despite the preservation of a liver specific gene expression footprint in Li-iPSCs, the generation of fully differentiated hepatocytes cannot be achieved with the current differentiation protocols.

Study EGAS00001002676

High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform

Telomeres are specialized nucleoprotein structures at the ends of linear chromosomes that are essential for the stability as well as the complete replication of the human genome. The progressive shortening of steady-state telomere length in normal human somatic cells is a promising biomarker for age-associated diseases. However, there remain substantial challenges in quantifying telomere length in clinics and research laboratories due to the lack of accurate and high-throughput telomere length measurement method. Here, we describe a novel workflow to capture and analyze telomeres accurately at the single-nucleotide resolution. By using newly designed telobaits that are complementary to the single-stranded G-rich 3’ telomeric overhangs, we can specifically and efficiently capture full-length telomeres and subject them to single-molecule real-time (SMRT) sequencing. We show that the telomere length can be measured at nucleotide resolution using the PacBio high fidelity (HiFi) sequencing platform, which provides the necessary accuracy and throughput to uncover the steady-state telomere length distribution in human culture cell lines as well as clinical patient samples. This new method is a valuable tool not only in population-wide epidemiology studies but also for the longitudinal assessment of telomere attrition in individuals. Our results also reveal the extreme heterogeneity of telomeric variant sequences (TVSs) that is dispersed throughout the telomere repeat region. Importantly, the unique distribution pattern and sequence of TVSs in individuals may be used as a fingerprint for sample identification. In addition, the presence of TVSs disrupts the continuity of the canonical (5’-TTAGGG-3’)n telomere repeats, which could affect the binding of shelterin complexes at the chromosomal ends. Therefore, TVSs may act as a form of genetic polymorphisms that impairs telomere protection. Together with the absolute telomere length in each individual, TVSs may have profound implications in human aging and diseases.

Study EGAS00001006103

A circulating biomarker for severity of facioscapulohumeral muscular dystrophy

Facioscapulohumeral muscular dystrophy (FSHD) is a prevalent, incurable skeletal myopathy. Clinical trials for FSHD are hindered by heterogeneous biomarkers poorly associated with clinical severity, requiring invasive muscle biopsy. Macroscopically FSHD presents with slow fatty replacement of muscle, rapidly accelerated by inflammation. Mis-expression of the transcription factor DUX4 is currently accepted to underlie FSHD pathogenesis and mechanisms including PAX7 target gene repression have been proposed. Here we perform RNA-sequencing on MRI guided inflamed (n=24) and isogenic non-inflamed (n=24) muscle biopsies from the same clinically characterised FSHD patients, alongside isogenic peripheral blood mononucleated cells from a subset of patients (n=13), and unaffected controls. We employ multivariate models to evaluate the clinical associations of 5 published FSHD transcriptomic biomarkers. We demonstrate that PAX7 target gene repression can discriminate control, inflamed and non-inflamed FSHD muscle independently of age and sex (p<0.013), while the discriminatory power of DUX4 target genes is limited to distinguishing FSHD muscle from control. Importantly, the level of PAX7 target gene repression in non-inflamed muscle associates with clinical assessments of FSHD severity (p=0.04). DUX4 target gene biomarkers in FSHD muscle show associations with lower limb fat fraction and D4Z4 array length, but not clinical assessment. Lastly, PAX7 target gene repression in FSHD muscle correlates with the level in isogenic peripheral blood mononucleated cells (p=0.002). A refined PAX7 target gene biomarker comprising 143/601 PAX7 target genes computed in peripheral blood (the FSHD muscle-blood biomarker) associates with clinical severity in FSHD patients (p<0.036). Our new circulating biomarker validates as a classifier of clinical severity in an independent data set of 54 FSHD patient blood samples, with improved power in older patients (p=0.03). In summary, we present the minimally invasive FSHD muscle-blood biomarker of FSHD clinical severity valid in patient muscle and blood, with potential utility in routine disease monitoring and clinical trials.

Study EGAS00001007350

In this study, blood-brain barrier (BBB)-forming brain endothelial-like cells were generated from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). Cells were subsequently exposed to focused ultrasound and microbubbles (FUS+MB) to induce BBB opening and their transcriptome analysed. RNA sequencing (RNA-seq) results demonstrated minimal changes in the gene expression following FUS+MB suggesting safety of FUS+MB application in the clinical setting.

The blood-brain barrier (BBB) is a major impediment to therapeutic intracranial drug delivery for the treatment of neurodegenerative diseases, including Alzheimer’s disease (AD). Focused ultrasound applied together with microbubbles (FUS+MB) is a novel technique to transiently open the BBB and increase drug delivery. Evidence suggests that FUS+MB is safe, however the effects of FUS+MB on human BBB cells, especially in relation to AD, remain sparsely investigated. Here we developed a human sporadic AD BBB cell platform to investigate the effects of FUS+MB on BBB cells and screen for the delivery of two potentially therapeutic AD antibodies. We generated BBB cells from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). We utilized this robust and reproducible platform to demonstrate increased delivery of potentially therapeutic antibodies across the BBB, including an analogue of Aducanumab (AduhelmTM) following FUS+MB treatment. Our results also demonstrate the safety of FUS+MB indicated by minimal changes in the cell transcriptome as well as little or no changes in cell viability and inflammatory responses within first 24 h post FUS+MB, with potentially important implications in a clinical setting. Finally, we report a more physiologically relevant hydrogel-based 2.5D BBB model as a key development for FUS+MB-mediated drug delivery screening, with potentially higher translational utility. Our results provide an important advancement for identifying FUS+MB-deliverable drugs and screening for cell- and patient-specific effects of FUS+MB, accelerating its use as a therapy in AD.

Study EGAS00001005944

High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform, P49-P104 and run1 replicates

Telomeres are specialized nucleoprotein structures at the ends of linear chromosomes that are essential for the stability as well as the complete replication of the human genome. The progressive shortening of steady-state telomere length in normal human somatic cells is a promising biomarker for age-associated diseases. However, there remain substantial challenges in quantifying telomere length in clinics and research laboratories due to the lack of accurate and high-throughput telomere length measurement method. Here, we describe a novel workflow to capture and analyze telomeres accurately at the single-nucleotide resolution. By using newly designed telobaits that are complementary to the single-stranded G-rich 3’ telomeric overhangs, we can specifically and efficiently capture full-length telomeres and subject them to single-molecule real-time (SMRT) sequencing. We show that the telomere length can be measured at nucleotide resolution using the PacBio high fidelity (HiFi) sequencing platform, which provides the necessary accuracy and throughput to uncover the steady-state telomere length distribution in human culture cell lines as well as clinical patient samples. This new method is a valuable tool not only in population-wide epidemiology studies but also for the longitudinal assessment of telomere attrition in individuals. Our results also reveal the extreme heterogeneity of telomeric variant sequences (TVSs) that is dispersed throughout the telomere repeat region. Importantly, the unique distribution pattern and sequence of TVSs in individuals may be used as a fingerprint for sample identification. In addition, the presence of TVSs disrupts the continuity of the canonical (5’-TTAGGG-3’)n telomere repeats, which could affect the binding of shelterin complexes at the chromosomal ends. Therefore, TVSs may act as a form of genetic polymorphisms that impairs telomere protection. Together with the absolute telomere length in each individual, TVSs may have profound implications in human aging and diseases.

Study EGAS00001006595

Clinical and ctDNA data for IMpassion031

Clinical and ctDNA data for IMpassion031, including survival, response, and ctDNA data from baseline through post-surgery time points. 222 samples run on Signatera assay. File type is csv.

Dataset EGAD50000001420

DynaTag for efficient profiling of transcription factors in small samples and single cells

The dataset included Dynatag data for the occupancy of transcription factors and single nuclei RNA-seq data. Corresponding metadata is provided for both experiments.

Dataset EGAD50000001562

Exome sequencing in HIV+ Viremic Non-Progressors (VNPs) and HIV+ Progressors

This dataset contains 184 paired fastq files sequences with Illumina NovaSeq600 from 38 participants. Relevant clinical and demographical data is also included.

Dataset EGAD50000000111

RNA sequencing of 20 intra/extra hepatic bileduct organiods

This dataset contains RNA sequencing data for 20 intra/extra hepatic bileduct organiods. Data is in BAM format and was processed by STAR.

Dataset EGAD00001005225

WGS of Biobank iPSC lines

WGS data from healthy reference iPSC lines. The median coverage is 41-50x. >85% have a coverage of >30x. 97% of the variants are known.

Dataset EGAD00001008769

Whole exome sequencing of a sinonasal glomangiopericytoma case

The is dataset includes the whole exome sequencing of the tumor from a sinonasal glomangiopericytoma case together with the matching blood. The whole exome sequencing revealed somatic PIK3CA and CTNNB1 mutations.

Dataset EGAD00001008291

Phylogenetic reconstruction of adult blood cancer reveals early origins and lifelong evolution - TGS

Mutations in cancer-associated genes drive tumour outgrowth. However, the timing of driver mutations and dynamics of clonal expansion that lead to human cancers are largely unknown. We used 580,133 somatic mutations from whole-genome sequencing of 1013 clonal haematopoietic colonies to reconstruct the phylogeny of haematopoiesis, from embryogenesis to clinical disease, in 12 patients with myeloproliferative neoplasms which are blood cancers more common in older age. JAK2V617F, the pathognomonic mutation driving the majority of these cancers, was acquired in utero or childhood, with upper estimates of age of acquisition from 33 weeks gestation to 10.8 years, in all 5 patients in whom JAK2V617F was either the only or the first driver event. Driver mutations associated with age-related clonal haematopoiesis occurred prior to or following JAK2V617F, as independent clonal expansions in JAK2V617F-mutated patients, and as large clonal expansions in JAK2V617F-unmutated patients . These mutations were also acquired in utero or childhood, with DNMT3A mutations occurring by 8 weeks of gestation to 7.6 years across 4 patients, and PPM1D mutation occurring by age 5.8yrs in a patient with MPN lacking phenotypic driver mutations. Sequential driver mutation acquisition was common, separated by decades across life, and often outcompeted ancestral clones. The mean latency between JAK2V617F acquisition and clinical presentation was 30 years (range 11-54 years). Rates of clonal expansion were inferred from phylogenetic trees and varied substantially (3% to 190% expansion/year), were affected by additional driver mutations, and were predictive of latency to clinical presentation. Driver mutations and rates of expansion would have been detectable in blood one to four decades before clinical presentation. This study reveals how driver mutation acquisition early in life with life-long growth and evolution underlie adult myeloproliferative neoplasms, providing opportunities for early detection and intervention and a new paradigm for cancer development.

Dataset EGAD00001007715

Diverse mutational landscapes in human lymphocytes

A lymphocyte suffers many threats to its genome, including programmed mutation during differentiation, antigen-driven proliferation and residency in diverse microenvironments. After developing protocols for single-cell lymphocyte expansions, we sequenced whole genomes from 717 normal naive and memory B and T lymphocytes and hematopoietic stem cells. All lymphocyte subsets carried more point mutations and structural variants than haematopoietic stem cells – the extra mutations were mostly acquired during differentiation, with burdens higher in memory than naive lymphocytes, although T cells also had a higher rate of mutation accumulation throughout life. Off-target effects of immunological diversification accounted for most of the additional differentiation-associated mutations in lymphocytes. Memory B cells acquired, on average, 18 off-target mutations genome-wide for every one on-target IGV mutation during the germinal centre reaction. Structural variation was 16-fold higher in lymphocytes than stem cells, with ~15% of deletions being attributable to off-target RAG activity. Mutational processes associated with ultraviolet light exposure and other sporadic mutational processes generated hundreds to thousands of mutations in some memory lymphocytes. The mutation burden and signatures of normal B lymphocytes were broadly comparable to those seen in many B-cell cancers, suggesting that malignant transformation of lymphocytes arises from the same mutational processes active across normal ontogeny. The mutational landscape of normal lymphocytes chronicles the off-target effects of programmed genome engineering during immunological diversification and the consequences of differentiation, proliferation and residency in diverse microenvironments.

Dataset EGAD00001008107

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

Moroccan Genome Project: Sequencing Data from 109 Whole Genomes of Moroccan Individuals

This study is the first phase of the Moroccan Genome Project, which included the complete sequencing of 109 genomes from the Kingdom of Morocco. The sequencing was performing using the Illumina NovaSeq6000 platform, with a mean coverage of 30X.

Dac EGAC50000000353

CRC organoid RNA-seq data access committee

This DAC is responsible for granting access to RNA-seq data (paired-end FASTQ files) from 10 patient-derived colorectal cancer organoid patients. The data was ad hoc generated as part of the development of NovumRNA, a non-canonical tumor-specific antigen prediction pipeline.

Dac EGAC50000000406

DAC for "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients."

This is the DAC for the study "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients." of Andreas Trumpp (a.trumpp@dkfz.de), Roberto Würth (r.wuerth@dkfz.de) and Martin Sprick (Martin.Sprick@hi-stem.de).

Dac EGAC50000000371

Dac for "Development of a fully human glioblastoma-in-brain-spheroid model for accelerated translational research"

This is the DAC for "Development of a fully human glioblastoma-in-brain-spheroid model for accelerated translational research" of Philipp Koch (philipp.koch@zi-mannheim.de), Frank Winkler (Frank.Winkler@med.uni-heidelberg.de), Moritz Mall( m.mall@dkfz-heidelberg.de)

Dac EGAC50000000480

Boyes Lab - DAC policy

Access to this data is controlled. Upon request from a third party for access to the data, a separate Data Sharing Agreement would be put in place between the University of Leeds and the third party prior to EGA granting access to the data to the third party.

Dac EGAC50000000283

Plasma cell‐free transcriptome profiling in chronic liver disease

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

Dac EGAC50000000360

PETAL trial Whole Exome Sequencing (WES) from Normal Samples

Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 55 Normal Samples. WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

Dataset EGAD50000002507

PETAL trial Whole Exome Sequencing (WES) from Tumor Samples

Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 224 Tumor Samples. WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

Dataset EGAD50000001172

Adipose tissue macrophage dysfunction is associated with a breach of vascular integrity in NASH

We report single-cell RNA sequencing data from myeloid cells of the human visceral adipose tissue in non-alcoholic fatty liver disease patients

Dataset EGAD50000000615

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

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

Dataset EGAD50000000304

South African breast cancer GWAS genotype data in VCF format

South African breast cancer GWAS genotype data for 2823 female African breast cancer cases. The data was generated using the H3Africa Custom microarray and genotyped on the Illumina HiScan instrument. The dataset is in VCF format.

Dataset EGAD00010002732

Clean sequence of LUAD in young never-smoker

we conducted whole genome sequencing (WGS) to characterize the genomic alterations of 36 never-smoker Chinese patients with lung adenocarcinomas (LUADs). This dataset is containing clean fastq files of 36 never-smoker Chinese patients with lung adenocarcinomas (LUADs)

Dataset EGAD00001003890

NSCLC PC9 erlotinib RAF1 study

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

Dac EGAC50000001001

TCS validation of 11 lung adenos

This is the targeted capture deep sequencing (TCS) data for validation of the mutations discovered in the WES step. There are 58 bam files of TCS data including 48 tumor samples and 10 peripheral blood WBC samples.

Dataset EGAD00001000985

GENCORD2_GENOTYPES

204 individuals were genotyped with the Illumina 2.5M Omni chip. Filtered genotypes were imputed into the 1000 genomes project European panel SNPs. Beagle R2 is indicated in VCF files for further filtering. See Materials and Methods in publication for details.

Dataset EGAD00001000428

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