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• Loss of Epigenetic Barrier is Required for Enhancer Hijacking-Mediated Oncogenic Transcription

  Structural variants (SVs) involving enhancer hijacking can disrupt chromatin topologies to cause oncogene activation in cancer genomes, yet the molecular determinants for the transcriptional output of enhancer hijacking remain largely unknown. We developed a multimodal approach to integrate genome sequencing, chromosome conformation, and sequence-based deep learning for quantitative analysis of transcriptional effects and structural reorganization imposed by SVs in leukemic genomes. We identified candidate pathogenic SVs including recurrent t(5;14) translocations that cause the hijacking of BCL11B enhancers for oncogenic activation of TLX3-dependent transcriptional programs. By engineering patient-associated t(5;14) in isogenic leukemia cells, we uncovered an uncharacterized mechanism whereby DNA methylation serves as an epigenetic barrier to enhancer hijacking and loss of epigenetic barrier is a molecular determinant for the transcriptional output of pathogenic SVs. Hence, leveraging the epigenetic barriers of SV-mediated oncogenic programs may provide new opportunities to reprogram gene regulation as epigenetic therapies in human disease.

  Study EGAS00001006140

• Northern Ireland COhort for the Longitudinal study of Ageing

  The Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA) is a representative sample of ~8,500 people from across Northern Ireland. The study, which was set up in 2012, aims to understand what it is like to grow older in Northern Ireland. • NICOLA has a strong focus on molecular biomarkers so there is complementary genetic, epigenetic and transcriptomic data available for a subset of individuals. • We inherit much of our DNA from our parents while a small amount of this material changes as we get older. In NICOLA we have 551,839 directly genotyped and 18,148,478 imputed Single Nucleotide Polymorphisms (SNPs) currently available for 2969 participants. • Summary statistics for the association of these gene polymorphisms with ~30 phenotypes were generated. • Epigenetics provides a link between our inherited DNA and environmental influences from a person’s diet, medication and lifestyle. NICOLA has the epigenetic quality controlled profiles of 1984 individuals arising from variations in DNA methylation at 862,927 genetic sites.

  Study EGAS00001007915

• Asian Genome Project(BioBank Japan genotype data)

  Biobank Japan registrants sequenced for Asian Genome Project

  Study JGAS000647

• Heart

  Whole-Exome-Sequencing of 5 pooled patients for SNP-based demultiplexing

  Study EGAS50000000655

• Identifying causative mutations for Thrombocytopenia with Absent Radii

  Identifying causative mutations for Thrombocytopenia with Absent Radii

  Dataset EGAD00001000018

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• snv calls for subclonal reconstruction

  single nucleotide variant calls from somatic sniper, vcf format. input for subclonal reconstruction

  Dataset EGAD00001003753

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000695

• DATA FILES FOR SJEPD

  DATA FILES FOR SJEPD

  Dataset EGAD00001000854

• Oxford Nanopore sequencing for APL

  Raw fast5 file of Oxford Nanopore sequencing for an APL patient sample

  Dataset EGAD00001008151

• International Consortium for Blood Pressure (ICBP)

  The ICBP consortium is an international effort to investigate blood-pressure genetics. The consortium was formed by two parent consortia, the CHARGE-BP consortium (Cohorts for Heart and Aging Research in Genomic Epidemiology - blood pressure) and the GBPGEN consortium (Global Blood Pressure Genetics Consortium). In 2011 we performed genome-wide association analyses based on genome-wide SNPs imputed to HapMap for systolic and diastolic blood pressure (SBP and DBP) and mean arterial pressure and pulse pressure (MAP and PP). In 2016 we performed an analysis based on the Cardio-MetaboChip for SBP and DBP. All these datasets are available here, however, full association statistics including effect size directions, only under controlled access by dbGaP.

  Study phs000585

• Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS)

  Advances in antiretroviral therapies (ART) and patient management have improved survival of people living with HIV (PLWH). However, with exposure to ART and associated side effects and toxicities as well as to the virus itself, PLWH are at an increased risk of several chronic diseases. The Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS) research network integrates longitudinal clinical data and treatment management of PLWH and provides research infrastructure to support HIV-associated clinical, social, and behavioral outcomes and comparative effectiveness research using data collected from 8 Centers for AIDS Research clinical sites across United States. For detailed study description, see Kitahata et al. (2008, PMID:18263650).

  Study phs001788

• A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy

  The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and non-canonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in-silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens and high-confidence tumor-specific antigens.

  Study EGAS50000000228

• Star2xml: metadata converter into XML

  Star2xml: metadata converter into XML Welcome to the landing page for star2xml - a tool developed by the European Genome-phenome Archive (EGA) that enables users to convert metadata into XML format that is compliant with EGA's programmatic submission system. For starters, if you are not sure what metadata is in this context, you may want to explore our brief metadata introduction. . Star2xml is useful for users who have already submitted their data to the EGA and want to also submit their metadata programmatically without having to create the XML files manually. The need for these XMLs containing metadata is explained in the EGA's metadata schemas and programmatic submission guidelines. In summary, star2xml allows for users to deposit metadata in a tabular format (e.g. excel spreadsheet) and transform it into a compliant XML format. This saves time in large submissions, where the sheer size of metadata makes it difficult to manage. For smaller submissions, it is recommended to use EGA's Submitter Portal (SP) instead. The installation of the tool is straightforward, and it contains detailed documentation on how to use it in its GitHub repository . While star2xml can help users convert metadata formats, it does not validate the resulting metadata against EGA's schemas. Therefore, after creating your XMLs, you should still validate your metadata before submitting it to EGA, as described in the documentation for programmatic metadata validation.

  Documentation tools/star2xml

• Identifying causative mutations for Thrombocytopenia with Absent Radii

  Thrombocytopenia with Absent Radii is an inherited disorder that manifests itself with major limb skeletal abnormalities and low platelet count (and therefore a bleeding diathesis). The syndrome is well-characterised and defined phenotypically and there is a well-established database of UK-based families affected with ths disorder. The causative mutation for the disorder is yet to be identified. If known, it would allow for pre-natal screening and counselling avoiding life-long care for patients who are affected and are therefore severely disabled. We postulate that exon sequencing of 4 unrelated affected individuals would give enough power to narrow down potential candidate mutations which would thereafter be confirmed using DNA from other affected families.

  Study EGAS00001000054

• A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

  Study EGAS00001008051

• Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia - Acute myeloid leukemia

  The advent of high-throughput next generation sequencing (NGS) technologies that are revolutionizing genomics and transcriptomics by providing a single base resolution tool for a unified deep analysis of diseases complexity allows a fast and cost-efficient fine-scale assessment of the genetic variability hidden within cohorts of patients affected by the same leukemia. That being so, by potentially highlighting inter-individual differences that may play a role in the differential success of diverse therapeutic interventions, they promise to be crucial for selecting the most appropriate medical treatments. The project aims at the identification of novel prognostic biomarkers for acute myeloid leukemia (AML) and studied the molecular differences between aneuploid and euploid AML.

  Study EGAS00001005464

• NINDS-Genome-Wide Genotyping in Parkinson's Disease: First Stage Analysis and Public Release of Data

  Epidemiological studies have estimated a cumulative prevalence of PD of greater than 1 per thousand. When prevalence is limited to senior populations, this proportion increases nearly 10-fold. The estimated genetic risk ratio for PD is approximately 1.7 (70% increased risk for PD if a sibling has PD) for all ages, and increases over 7-fold for those under age 66 years. The role for genes contributing to the risk of PD is therefore significant. This study utilized the well characterized collection of North American Caucasians with Parkinson's disease, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis. Genome-wide, single nucleotide polymorphism (SNP) genotyping of these publicly available samples was originally done in 267 Parkinson's disease patients and 270 controls, and this has been extended to include genome wide genotyping in 939 Parkinson's disease cases and 802 controls. The NINDS repository was established in 10-2001 towards the goal of developing standardized, broadly useful diagnostic and other clinical data and a collection of DNA and cell line samples to further advances in gene discovery of neurological disorders. All samples, phenotypic, and genotypic data are available to the research community including to academics and industry scientists. In addition, well characterized neurologically normal control subjects are a part of the collection. This collection formed the basis of this first stage study by Fung et al., and the expanded study by Simon-Sanchez et al. The genotyping data was generated and provided by the laboratory of Dr. Andrew Singleton NIA, and Dr. John Hardy NIA (NIH Intramural, funding from NIA and NINDS). Important links to apply for individual-level data Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Participant Protection Policy FAQ

  Study phs000089

• Population Architecture using Genomics and Epidemiology (PAGE): Multiethnic Cohort (MEC)

  The Multiethnic Cohort (MEC) has established a large biorepository of blood and urine (N=67,000) and cryopreserved lymphocytes (N=15,000) linked to extensive, prospectively collected risk factors (e.g., diet, smoking, physical activity), biomarkers and clinical data for five racial/ethnic groups. This cohort study of over 215,000 men and women in Hawaii and California is unique in that it is population-based and includes large representations of older adults (45-75 yrs at baseline) for five US racial/ethnic groups (Japanese Americans, African Americans, European Americans, Latinos and Native Hawaiians) at varying risks of chronic diseases. Within the PAGE investigation, the MEC proposes to study: 1) diseases for which we have DNA available for large numbers of cases and controls (breast, prostate, and colorectal cancer, diabetes, and obesity); 2) important cancers that are less common (e.g., lung, pancreas, endometrial cancers, NHL) but for which we propose to pool our data with other funded groups; 3) common traits that are risk factors for these diseases (e.g., body mass index/weight, waist-to-hip ratio, height) and 4) relevant disease-associated biomarkers (e.g., fasting insulin and lipids, steroid hormones). The specific aims are: 1) To determine the population-based epidemiologic profile (allele frequency, main effect, heterogeneity by disease characteristics) of putative causal variants in the five racial/ethnic groups in the MEC; 2) for variants displaying effect heterogeneity across ethnic/racial groups, we will utilize differences in LD to identify a more complete spectrum of associated variants at these loci; 3) investigate gene x gene and gene x environment interactions to identify modifiers; 4) examine the associations of putative causal variants with already measured intermediate phenotypes (e.g., plasma insulin, lipids, steroid hormones); and 5) for variants that do not fall within known genes, start to investigate their relationships with gene expression and epigenetic patterns in small genomic studies. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356.

  Study phs000220

• Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

  The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

  Study phs001801

• Susceptibility loci for tanning ability in Japanese population identified by genome-wide association study

  We performed genome-wide association studies of Japanese Skin Type for Japanese individuals from a cohort study by the Tohoku Medical Megabank Project in order to identify variants related to tanning ability and skin pigmentation. We used imputed genotype data of 9,187 Japanese individuals, of which 4,475 individuals are from Miyagi prefecture and 4,712 individuals are from Iwate prefecture. Skin Type information was obtained from the questionnaire for cohort participants.

  Study JGAS000160

• Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment

  Samples was collected at the Mayo Clinic. MM tumor samples were enriched using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). DNA from CD138+ MM cell (tumor) or peripheral blood samples (germline control) at Mayo Clinic (Rochester or Arizona) underwent WGS. For samples collected at Mayo Clinic Rochester, library preparation was completed using the NEB Ultra II (New England Biolabs, Ipswich, MA) and the Nextera Flex systems (Illumina, San Diego, CA) and sequenced at the Mayo Clinic Genome Analysis Core with an approximate depth of 30X for tumor samples and 60X for the germline control. For samples collected at Mayo Clinic Arizona, Novogene was used for WGS following random shearing of the DNA, end-repairs, A-tailed and ligated with Illumina adapters. Sequencing was performed on the Illumina Novaseq 6000 sequencer Reference Genome: GRCh38.

  Dataset EGAD50000002132

• Mutational landscape of the transcriptome offers putative targets for immunotherapy of myeloproliferative neoplasms

  In this study, we aimed to comprehensively characterize in 113 myeloproliferative neoplasms (MPN) patients the mutational landscape of the granulocyte transcriptome using RNA sequencing data. We implemented workflows for fusion and variant calling, and differential splicing analysis for patients with hotspot SF3B1 mutations. Finally, we characterized the neoantigen landscape on individualized level taking each patient's HLA genotype (derived from the same RNA-seq dataset) into account.

  Study EGAS00001003486

• Whole exome sequencing for clarification of rare causes of axonal Charcot-Marie-Tooth disease (2017-08-16)

  The project is focused on the axonal forms of Charcot-Marie-Tooth (CMT) disease. We have selected 13 families (7 from Spain and 6 from Czech Republic) that have been indepth clinically assessed and previously tested for mutations in known CMT genes without causal variants characterised. In these patients we expect to discover several CMT2 genes. Thus, we requested for exome sequencing of 45 DNAs:27 exomes in families from Spain and 18 exomes in the families from Czech Republic. 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/ This dataset contains all the data available for this study on 2017-08-16.

  Dataset EGAD00001003565

• Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals

  Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals. Additional associated phenotype information is available for all individuals included in this study directly from CIBMTR. Data are available under controlled access release upon reasonable request and execution of a data use agreement. Requests should be submitted to CIBMTR at info-request@mcw.edu and include the study reference IB17-04.

  Study EGAS00001006033