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• Center for Common Disease Genomics [CCDG] - Cardiovascular: Cardiology Biobanking for Biomarker Discovery

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfThe BioHEART study is a multi-center, prospective, observational cohort study to identify new biomarkers in stable coronary artery disease (CAD) and acute myocardial infarction (MI) (ACTRN12618001322224). Participants are recruited at time of clinically indicated computed tomography (CT) coronary angiogram (CTCA). 1,950 of 5,000 planned participants have been recruited and serum/plasma/erythrocytes/monocytes stored, with follow-up ongoing. CTCA imaging studies provides volumetric quantification of total calcified and non-calcified plaque, which is assessed using established and novel scoring systems. Comprehensive molecular phenotyping is performed on blood samples using state-of-the-art genomic, transcriptomic, proteomics, metabolomic, lipidomic, and immunophenotyping. Outcome data will be used to build improved risk models for CAD.Reference: http://www.anzctr.org.au/ - ACTRN12618001322224

  Study phs002726

• Characterization of Structural Variants in Acute Myeloid Leukemia Patients

  Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and is expected to increase in frequency as the population ages. Most subtypes of AML are difficult to treat, in part due to a lack of understanding of possible molecular targets. Furthermore, the peak incidence of AML is in the sixth decade, and patients over the age of 65 do not tolerate chemotherapeutic regimens well. Moreover, AML has been highly studied as a model for other cancers. An RNA Biology Program is established aiming to develop comprehensive datasets through the profiling of all different classes of RNA expression, RNA editing, alternative splicing, and non-coding RNAs in CD34+ normal hematopoietic stem cells (HSC), their differentiated progeny, and AML clinical samples that could be utilized to understand leukemia. These datasets will allow us to computationally identify and characterize various RNA species and processes to enable the development of effective therapeutics to AML, leukemia and other types of cancers. Epigenetic factors such as methylation and histone modifications will also be characterized from these clinical samples allowing for integrated dataset analysis to look at the cross-talk between RNA and DNA/epigenomics in leukemia. The following is a subsidiary study of the above study description where whole genome sequencing was performed on two collected AML patients' samples using Illumina and Oxford Nanopore sequencing technologies. The aim is to characterize the roles of structural variants (SV) in RNA biology which are potentially important for AML development using our own established long-read SV characterization tool, NanoVar. The advent of Oxford Nanopore sequencing technologies has opened a new avenue for better SV characterization by having longer sequencing reads. NanoVar is an accurate and rapid SV characterization tool that utilizes low-depth Nanopore sequencing data. NanoVar makes use of split-reads and hard-clipped reads for SV discovery and employs a simulation-trained neural network classifier for true positive enrichment. NanoVar exhibited higher accuracy and faster computational speed amongst other long-read SV detection tools in simulated data. In AML patient data, NanoVar displayed excellent accuracy in SV characterization (16/16 SVs validated in two patients) by using only 4x depth sequencing data. In summary, NanoVar improves the accuracy and speed of SV characterization at a lower sequencing cost, an approach compatible with clinical studies.

  Study phs001847

• Prediction of HLA genotypes using NGS data

  High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate.

  Study EGAS00001005274

• Clinical and Genetic Evaluation of Individuals with Undiagnosed Disorders through the Undiagnosed Diseases Network (UDN)

  The National Human Genome Research Institute and the NIH Clinical Center established the intramural Undiagnosed Diseases Program (UDP) in 2008 to make progress in uncovering, understanding, and treating rare disorders. Based on the success of the UDP, the NIH Common Fund established the Undiagnosed Diseases Network (UDN) in FY 2013 (Phase I, 9/16/2015-8/31/2018) to achieve this type of cross-disciplinary approach to disease diagnosis in academic medical centers around the United States. The NIH Common Fund expanded the network in 2018 (Phase II, 9/1/2018-6/20/2023) to increase the availability of diagnostic services, foster opportunities for collaboration between laboratory and clinical investigators, provide resulting data and protocols to the broader community, and assess development of a sustainable national resource after Common Fund support ends. The UDN transitioned from Common Fund in 2023. The National Institute of Neurological Disorders and Stroke (NINDS) will oversee the Network in Phase III, which launched in July 2023, with help from 17 different NIH Institutes and Centers along with the NIH Office of the Director. With help from patients, family members, patient advocacy groups, a Data Management and Coordinating Center (DMCC), several Clinical Sites, and other stakeholders, the NIH envisions the UDN evolving into a larger, diverse, and self-sustained network that fosters scientific discovery and provides expert diagnostic services for undiagnosed patients across the nation. The overarching goals of the UDN in Phase III include: Continuing the proven success of the UDN in improving the clinical evaluation of difficult-to-diagnose patients using a collaborative team approach and investigating and validating promising new diagnostic technologies. Facilitating research into the etiology of undiagnosed diseases by collecting and sharing standardized, high-quality clinical and laboratory data including genotyping, phenotyping, and documentation of environmental exposures. Promoting a broader integrated and collaborative community across multiple Clinical Sites and among laboratory and clinical investigators prepared to investigate the genetic, pathophysiologic, cell biologic, and molecular mechanisms underpinning these difficult-to-diagnose conditions.

  Study phs001232

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001003063

• RNA-seq of Liver Cancer

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002879

• Whole Genome Sequencing of HCC

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002888

• Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

  DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

  Study EGAS00001001191

• Method to Assess Lung Water Accumulation During Exercise

  The goal of this non-significant risk medical device study is to test the initial technical feasibility of a 0.55T MRI in healthy volunteers by technical optimization of scanner protocols, and to test accuracy of standard MR measurements in adult patients with known stable disease. Exercise-induced lung water is a key feature in heart failure. Dynamic quantitative lung water imaging during exercise stress is therefore of interest to unmask latent heart failure. We developed a novel magnetic resonance imaging (MRI) method using a proton density weighted ultrashort echo time MRI sequence along with a time-resolved and respiratory motion compensated image reconstruction for exercise lung water imaging. We validated our method in a porcine model of dynamic lung water accumulation (n=5), and tested its feasibility for use in humans using 12 healthy subjects, 1 patient with heart failure with preserved ejection fraction, and 1 patient with heart failure with reduced ejection fraction. Data suggest the novel imaging method is capable of dynamically imaging lung water accumulation during exercise stress. Reference 1 (PMID: 37288601) contains the main results for this study.

  Study phs003346

• Urethral Microbiome of Adolescent Males

  Urethral microbiome of adolescent males is designed to characterize the microbial communities resident in the urethra of young men, to identify differences in these communities as a function of race/ethnicity, circumcision status, sexual exposures, and uro-genital symptoms. We collect detailed sexual behavior and symptoms data using cellular telephones with Internet access. Specimens are routinely collected at monthly intervals, and intermittently following reported symptoms, specific sexual exposures, or identification of a sexually transmitted infection. We also collect periodic samples from the penile coronal sulcus to better characterize its relationship to the urethral micriobial communities. Participants are ages 14 - 17 at enrollment, and prior history of sexual exposure is not required for participation. Parental permission is obtained for each participant. The planned duration of followup is up to 4 years allowing for prospective observation of both physical and behavioral maturation from middle adolescence into young adulthood. The overall objectives of the project are to better characterize the healthy male urethral microbiome, and to use this information to better understand acquisition of urethritis and sexually transmitted infections, as well as chronic genital pain and prostatitis syndromes that become common among young adults.

  Study phs000259

• CIDR Whole Exome Sequencing in Joubert Syndrome

  The purpose of this study is to identify new genetic causes of neurodevelopmental diseases (NDDs) in the Joubert syndrome (JS) spectrum. Joubert syndrome is a recessive disease characterized by cerebellar vermis hypoplasia. Our currently funded NINDS award entitled "Molecular characterization of Joubert syndrome" seeks to identify new genetic causes through a variety of molecular strategies. Although our previous strategies involved whole genome SNP-scans, followed by candidate gene sequencing to arrive at identification of new JS causes, we have recently moved to Whole Exome Sequencing (WES) as a highly efficient methodology that is optimized for recessive disease. In this pilot project, CIDR has sequenced DNA on probands from 20 inbred families with JS spectrum disorders in which known causes have been excluded, that have not previously undergone genome-wide SNP scans. These paired end reads will be subject to our established bioinformatics pipeline including HOMOZGYOSITY, SNP and INDEL callers in our lab to identify potentially deleterious sequence changes (PDSC). This is followed by analysis to include testing each PDSC for segregation in the whole pedigree, for occurrence in a ethnically-matched cohort, as well as a defined patient cohort patients, in order to validate new NDD genes.

  Study phs000382

• Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). 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 EGAS00001002643

• Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). 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 EGAS00001002642

• Genetic Modifiers of Huntington's Disease

  Huntington's disease (HD) is a neurodegenerative disorder typically diagnosed in mid-life that is caused by expansion of an otherwise polymorphic CAG trinucleotide repeat. The mutation causes a gain-of-function of the huntingtin protein to trigger a pathogenic process that produces detectable phenotypic differences many years before the traditional diagnosis, which is based upon characteristic motor symptoms. The prediagnosis phase of pathogenesis is now the subject of intense scrutiny by an NINDS-funded longitudinal study, PREDICT-HD, in which undiagnosed gene carriers are followed longitudinally and subjected to detailed phenotyping (PREDICT-HD Huntington Disease Study -- dbGaP Study Accession: phs000222). This powerful approach, which offers the potential for moving the focus of therapeutic development to the decades prior to neurological disease diagnosis, is enabled by the fact that all individuals with HD have the same type of mutation, which can be determined at any time in life by a single HD CAG repeat PCR amplification assay. The precise length of the HD CAG repeat differs between individuals. There is a strong negative correlation between the number of CAG repeats and the age at onset of diagnostic neurological abnormalities in HD, such that the CAG repeat accounts for ~50% of the variation in age at diagnosis. Analysis of the remaining variance not explained by the length of the CAG repeat has shown that it is highly heritable, being due to genetic variation, elsewhere in the genome. The intent of the Genetic Modifiers of Huntington's Disease study is to identify genetic modifiers of HD pathogenesis by using genomewide association techniques in diagnosed HD individuals to identify genetic factors associated with the residual variance in age at onset not explained by the CAG repeat, and to extend these analyses to pre-diagnosis phenotypes, for example, those defined in the PREDICT-HD study. Identification of modifier genes is a top priority for HD research (and an example of an approach that can be applied in other late-onset genetic disorders), as it could provide clues to developing rational treatments that delay or prevent the pathogenic process from causing the ravages of the disease that ensue in the ~15 years of inexorable decline to ultimate death that now follows clinical diagnosis. To further that goal, the release of study version 2 makes available whole exome sequencing data of n=221 study participants.

  Study phs000371

• The landscape of Usher syndrome-associated transcript isoforms in the human neural retina

  Usher syndrome is an autosomal recessively inherited disorder characterized by the combination of progressive loss of visual function due to retinitis pigmentosa, sensorineural hearing loss and vestibular dysfunction in a subset of cases. Usher syndrome is clinically and genetically heterogeneous. To date, eleven genes have been identified that are associated with Usher syndrome. It is known that these genes express multiple isoforms, however, for most of the known isoforms their relative importance in the human retina is unknown. To fill this gap, using PacBio long-read mRNA sequencing we aimed to provide an overview of the Usher syndrome transcripts in the human retina.

  Study EGAS50000000504

• Best Practices for DACs

  Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security.

  Documentation access/data-access-committee/best-practices

• ICGC PedBrain: Deep-sequencing of childhood brain tumors.

  Brain tumors constitute the childhood tumors with the highest mortality rates and survival is often associated with severe long-term sequelae due to intensive multimodal treatment regimens. Thus, the PedBrainTumor network aims at the identification of robust biomarkers for clinical management and novel molecular targets for therapeutic interventions. Using massively parallel whole-genome sequencing, and transcriptome and methylome sequencing for subsets of cases, we aim to decipher the molecular causes of medulloblastoma as well as low-grade astrocytoma, and to identify markers to stratify patients for specialized treatment. As the PedBrain network is affiliated with clinical trials in medulloblastoma and pilocytic astrocytoma, validation cohorts for the translation of key findings into clinical settings are readily available.

  Study EGAS00001000215

• CaBagE: a Cas9-Based Background Elimination Strategy for Targeted, Long-Read DNA Sequencing

  While repeat-expansion polymorphisms are known to underlie several developmental and neurological disorders, technological limitations have inhibited the ability to resolve accurate genotypes for these variants. A pertinent example is the (CCCCGG)n repeat expansion in C9orf72 that segregates with up to 40% of familial amyotrophic lateral sclerosis (ALS) cases. There is a clear relationship between this repeat expansion and neurodegeneration. However, widely-used short-read sequencing is ill-suited to characterize the C9orf72 repeat expansion due to polymerase slippage over low complexity sequences and the inherently limited mapping/haplotype resolution of redundant short sequences. Consequently, researchers and physicians must rely on crude variant characterization methods (e.g. Southern blots), which limit direct genotype-phenotype associations and create challenges for the diagnosis of disease in patients with atypical clinical presentation. In contrast, ultra-long (e.g., 10-150kb) sequencing reads generated by Oxford Nanopore Technologies (ONT) enable direct measurement of loci containing complex structures without being subject to amplification or alignment bias. We are therefore developed a molecular and computational framework for targeted sequencing and quantification of pathogenic repeat expansions by combining Cas9 and amplification-free sequence capture methods with Nanopore long-read sequencing technology. First, extracted high molecular weight DNA is bound by Cas9 on either side of a DNA target. Bound Cas9 protects the target DNA from challenge by processive exonucleases. Unprotected (off-target) DNA is degraded with exonucleases and the remaining sample is sequenced using the ONT MinION sequencer. Then, base-called reads are aligned to the target locus and repeat copy number genotypes are estimated using a Gaussian Mixture Model. We applied this molecular and computational framework to 2 ALS patients with C9orf72 repeat expansions with biospecimens available from the NINDS collection from Coriell. Genotype estimates produced with CaBagE were commensurate with genotypes derived from repeat-primed PCR for each individual.

  Study phs002368

• SEER Remote Access Pilot Test Data (2018)

  This is a limited use Surveillance, Epidemiology, and End Results (SEER) file for use in a pilot test of remote data access. The SEER Program of the National Cancer Institute (NCI) is an authoritative source of information on cancer incidence and survival in the United States. SEER currently collects and publishes cancer incidence and survival data from population-based cancer registries covering approximately 34.6 percent of the U.S. population. The SEER Program registries routinely collect data on patient demographics, primary tumor site, tumor morphology and stage at diagnosis, first course of treatment, and follow-up for vital status. The mortality data reported by SEER are provided by the National Center for Health Statistics. The population data used in calculating cancer rates is obtained periodically from the Census Bureau. The SEER research data files include SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas.

  Study phs002012

• Dual targeting of polyamine synthesis and uptake in diffuse intrinsic pontine gliomas

  Diffuse intrinsic pontine glioma (DIPG) is an incurable malignant childhood brain tumour, with no active systemic therapies and a 5-year survival of less than 1%. Polyamines are small organic polycations that are essential for DNA replication, translation and cell proliferation. Ornithine decarboxylase 1 (ODC1), the rate limiting enzyme in polyamine synthesis, is irreversibly inhibited by difluoromethylornithine (DFMO). Herein we show that polyamine synthesis is upregulated in DIPG, leading to sensitivity to DFMO. DIPG cells compensate for ODC1 inhibition by upregulation of the polyamine transporter SLC3A2. Treatment with the polyamine transporter inhibitor AMXT 1501 reduced uptake of polyamines in DIPG cells, and co-administration of AMXT 1501 and DFMO led to potent in vitro activity, and significant extension of survival in three aggressive DIPG orthotopic animal models. Collectively, these results demonstrate the potential of dual targeting of polyamine synthesis and uptake as a therapeutic strategy for incurable DIPG.

  Study EGAS00001004905

• Systematic comparative analysis of single-nucleotide variants detection methods from single-cell RNA sequencing data

  Systematic interrogation of single nucleotide variations (SNVs) is one of the most promising approaches to delineate the cellular heterogeneity and phylogenetic relationships at the single cell level. While SNV detection from abundant single cell RNA sequencing (scRNA-seq) data is applicable and cost-effective in identifying expressed variants, inferring sub-clones, and deciphering genotype-phenotype linkages, there is a lack of computational methods specifically developed for SNV calling in scRNA-seq. Although variant callers for bulk RNA-seq have been sporadically used in scRNA-seq, the performances of different tools have not been assessed. Here, we performed a systematic comparison of seven tools including SAMtools, the GATK pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, using both simulation and scRNA-seq datasets, and identified multiple elements influencing their performance. Our study provided the first benchmarking to evaluate the performances of different SNV detection tools for scRNA-seq data.

  Study EGAS00001003883

• Fixative optimisation study for BRITROC project

  The British Translational Research Ovarian Cancer Collaborative (BriTROC), spanning more than 10 centres across UK, is a prospective observational project focused on relapsed high-grade serous ovarian cancer (HGSOC). The first study, as a part of the project, is the Fixative optimisation study, which analyses the utility for next-generation sequencing of UMFIX samples compared to NBF-fixed and fresh frozen samples. Various DNA and sequencing quality analyses were performed to compare fixation methods in bulk tumour and biopsy samples.

  Study EGAS00001001433

• H3Africa - Stroke Investigative Research and Education Networks

  Although stroke is a discrete phenotype, it is the clinical culmination of several complex and interacting biological processes, precipitated by various genetic and environmental factors, thereby making ready analyses of its underlying mechanisms a challenge. However, the formulation of successful tailor-made prevention strategies for limiting the immense personal and societal burden of stroke in Sub-Saharan Africa (SSA) is contingent on a better understanding of the predisposing risk factors for stroke in the region, which may not necessarily match the nature of stroke risk factors described among other people on other continents. Indeed, the underlying risk factors for stroke in SSA have hitherto not been comprehensively characterized, and currently there is a paucity of expertise, experience, and infrastructure in genomics and environmental research in SSA, to initiate and sustain such investigation. We seek to establish the Stroke Investigative Research and Education Network (SIREN) as a multidisciplinary collaborative research network of investigators in SSA and the United States collectively focused on exploring ways to promote a better understanding of the genetic and environmental risk factors for stroke among people of African ancestry. SIREN will evaluate unique contributors to stroke in SSA and compare these findings with those in a cohort of African American stroke survivors, all while simultaneously building sustainable capacities in phenomics, biobanking, genomics, biostatistics and bioinformatics for future high-level investigation of stroke and other vascular disease entities in SSA.

  Study EGAS00001007331

• Million Veteran Program (MVP) Summary Results from Non-Sensitive Omics Studies

  MVP is an ongoing prospective cohort study and mega‐biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans. This is the accession to hold publicly available results. Results from sensitive phenotypes or MVP population subsets can be found at accession phs001672 and will require an application for access.

  Study phs002453

• Whole genome sequencing data of paediatric hyperdiploid acute lymphoblastic leukemia

  The hyperdiploid (HeH) subtype with 51–67 chromosomes is the most common subtype in childhood, presented in 25–30% of the cases, and is associated with excellent prognosis . The HeH subtype harbors relatively few additional genetic alterations, suggesting that extra chromosomes are the driving event for leukemia onset. Secondary hits usually affect the RAS signaling pathway and histone modifiers.

  Study EGAS50000001690