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• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

  Cohort DescriptionHispanic Community Health Study/Study of Latinos (HCHS/SOL) is an ongoing population-based prospective cohort study of 16,415 community dwelling Hispanic/Latino adults aged 18-74 years at baseline, recruited from four urban field centers with large populations of Hispanics/ Latinos (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA). The primary goals of the HCHS/SOL are to describe: (1) the prevalence and incidence of cardiovascular, pulmonary, and other major chronic conditions (2) the risk and/or protective factors associated with these conditions; and (3) the relationships between the initial sociodemographic and health profiles and future health events in the target population. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 9817 HCHS/SOL participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 7536 HCHS/SOL participants in C4R. Derived data includes 43 variables for up to 11182 HCHS/SOL participants in C4R. Phenotype data includes 113 variables for up to 11182 HCHS/SOL participants in C4R.

  Study phs002908

• 2014 sequenced Korean WES-Lung Cancer sample 36 pair

  This data is belong to WES-Lung Cancer patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 36 paired tumor/normal samples from Samsung Hospital. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001004027

• 2015 AML-ETO WGS additional analysis result

  This data is belong to additional 2015 AML-ETO patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 2 paired tumor/normal samples from SNUH. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001004012

• 2014 Lung squamous cell carcinoma WES analysis result

  This data is belong to 2014 Lung squamous patients' exome data which is aligned to human reference(human_g1k_v37.fasta). There are 104 paired tumor/normal samples from SMC. All samples has passed QC and re-calibration steps while aligning to reference.

  Dataset EGAD00001003960

• 2014 sequenced WGS-Lung Cancer sample 30 pair

  This data is belong to WGS-Lung Cancer patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 30 paired tumor/normal samples from Samsung Hospital. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001003978

• Combined gene expression and digital pathology identifies molecular mediators of T cell exclusion and immune suppression in ovarian cancer

  Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what determines the spatial distribution of T cells in the tumour microenvironment is not well understood. Coupling digital pathology and transcriptome analysis on a large ovarian tumour cohort, we develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFb and activated stroma. Furthermore, we identify TGFb as a key mediator of T cell exclusion. TGFb reduces MHC-I expression in ovarian cancer cells in vitro; TGFb also activates fibroblasts and induced extracellular matrix (ECM) production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFb may represent a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

  Study EGAS00001003487

• RA-Map, A multi-omic survey of whole blood and subsets in early rheumatoid arthritis and vaccine study controls

  Rheumatoid arthritis (RA) is a chronic inflammatory disorder of unknown aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the molecular heterogeneity and pathogenesis of RA, we performed a comprehensive clinical and molecular profile of 267 RA patients for up to 18 months to establish a high quality biobank of barcoded samples that included plasma, serum, peripheral blood cells, whole blood RNA, RNA from lymphocyte and monocyte subsets, genomic DNA and urine. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and auto-antibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource for the development and application of targeted therapies for RA and reveal further insights into disease pathogenesis and therapeutic response.

  Study EGAS00001004424

• A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  iPSC-derived corneal endothelial cell substitutes recover pathological corneal edema. No adverse reactions are observed after one year follow-up. Gene mutations may appear despite whole genome sequencing of the master cell bank. This study contains WGS data.

  Study EGAS50000000672

• Whole exome data from PMID27216186

  This dataset comprises complete exome data from from the study PMID27216186 (Harbst & Lauss et al, Cancer Research 2016). These data are from 49 samples (tumor and matched normal) from 8 patients representing multi-region sequencing of human melanoma. Files are in the BAM format and contain aligned and processed data used for e.g. somatic variant calling. The sequencing libraries were constructed using SureSelect target enrichment with Clinical Research Exome Panel (Agilent) and sequenced on a HiSeq2500 (Illumina).

  Dataset EGAD00001008149

• High-Throughput RNA Isoform Sequencing using Programmable cDNA Concatenation

  MAS-ISO-seq is a novel technique for programmably concatenating cDNAs into single molecules for optimal long-read sequencing. In practice, this boosts throughput >15 fold to nearly 40 million cDNA reads per run on the PacBio Sequel IIe sequencer. We have validated this method via application to synthetic RNA isoforms and single-cell sequencing of tumor-infiltrating T cells. Results demonstrated a >30 fold boosted discovery of differentially spliced genes and robust cell clustering, as well as canonical PTPRC splicing patterns across T cell subpopulations and the concerted expression of the associated hnRNPLL splicing factor.

  Study phs003200

• Test Study for EGA using data from 1000 Genomes Project - Big CRAM, BAM, VCF and BCF files used for testing

  This is a test study for EGA using data from 1000 Genomes Project, specifically created to add more diversity to the existing dataset EGAD00001003338. This Test Study should NOT be confused with the real study of 1000 Genomes Project - Phase 3. Specifically, this study encompasses 4 CRAM, 4 BAM, 2 VCF and 2 BCF files, of different sizes (all above 1 GB), used for testing downloads and monitoring services. It also contains their respective indexes: crai for crams, bai for bams, tbi for vcfs and csi for bcfs.

  Study EGAS00001006718

• The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis (CLEAR)

  The Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis (CLEAR) Registry and Repository, supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), was established in 2000 to provide a resource for the scientific community to explore genetic and non-genetic factors affecting rheumatoid arthritis (RA) occurrence and outcomes in African Americans. The long term objective is a database and a repository of 1,100 RA and 550 matched healthy African-American subjects. This CLEAR Registry and Repository has two arms: a longitudinal arm for subjects with early RA (enrollment from 2000 to 2005) and a cross-sectional arm for subjects with any disease duration (enrollment from 2006 to 2012). CLEAR has two components: a database and a repository. The database contains extensive demographic, socioeconomic, clinical and radiographic (radiographs of hands and feet) information and bone mineral density data from DEXA scans. The repository contains genomic DNA, plasma and serum on most of the participants. Participants in CLEAR II had RNA isolated from peripheral blood cells.

  Study phs001360

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation

  Induced Pluripotent Stem Cells (iPSC) derived from healthy individuals are important controls for disease modeling studies. To create a resource of genetically annotated iPSC, we reprogrammed footprint-free lines from four volunteers in the Personal Genome Project Canada (PGPC). Multilineage directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users further demonstrated line versatility by generating kidney organoids, T-cells and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited a hypertrophic phenotype as expected. WGS annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harboured at least one pre-existing or acquired variant with cardiac, neurological or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cell types found in six tissues for disease modelling, and clinical annotation highlighted variant-preferred lines for use as unaffected controls in specific disease settings.

  Study EGAS00001003684

• White blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

  Liquid biopsies are providing new opportunities for detection of residual disease in cell-free DNA (cfDNA) after surgery but may be confounded through identification of alterations arising from clonal hematopoiesis. Here, we identify circulating tumor-derived DNA alterations (ctDNA) through ultrasensitive targeted sequencing analyses of matched cfDNA and white blood cells from the same patient. We apply this approach to analyze samples from patients in the CRITICS trial, a phase III randomized controlled study of perioperative chemotherapy in patients with operable gastric cancer. After filtering alterations derived from matched white-blood cells, the presence of ctDNA predicts recurrence when analyzed within nine weeks after preoperative treatment and after surgery in patients eligible for multimodal treatment. These analyses provide a facile method for distinguishing ctDNA from other cfDNA alterations and highlight the utility of ctDNA as a predictive biomarker of patient outcome to perioperative cancer therapy and surgical resection in patients with gastric cancer.

  Study EGAS00001004114

• Multi-omics analysis of treated cancer samples

  We treated patient-derived cell lines with effective drug inhibitors that we discovered. To understand the mechanisms behind how the inhibitor can effectively inhibit tumor growth, we performed a series of RNA-Seq, Histone ChIP-Seq, TF ChIP-Seq and ATAC-Seq profiling for samples with and without treatment with the inhibitor. There are 18 RNA-Seq, 20 ATAC-Seq and 182 ChIP-Seq experiments performed. This includes 2 biological replicates. Novaseq 6000 was used to sequence the samples. Library preparation was performed in house for ChIP-Seq and ATAC-Seq, using NEB indexes, while libraries for RNA-Seq were constructed by the sequencing company hired. Total RNA was sequenced. Sequencing parameters used are PE150, bi-directional sequencing. For ATAC-Seq, sequencing was performed up to 40M reads, for ChIP-Seq, sequencing was performed up to 20M reads and for RNA-Seq, sequencing was performed up to 20M to 40M reads. Fastq files are uploaded here.

  Dataset EGAD50000000349

• WXS files for paper titled 'Genomic Landscape of Pediatric Myelodysplastic Syndromes'

  Paired whole exome sequencing for 32 primary MDS, 14 MDS/MPN, and 8 AML-MRC cases (total = 54). Normal comparator genomic DNA was extracted from lymphocytes purified by flow cytometry. Bulk myeloid cells were used as a source of tumor gDNA. Files uploaded are mapped BAM files.

  Dataset EGAD00001003781

• Genome_Diversity_in_Africa_Project__Uganda

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics

  Study EGAS00001002523

• Rare Diseases Clinical Research Network (RDCRN) Vasculitis Clinical Research Consortium (VCRC) Longitudinal Protocol for Polyarteritis Nodosa

  The development and validation of accurate biological markers and predictors of disease activity and outcome in Polyarteritis Nodosa (PAN), a form a idiopathic vasculitis, would have a major positive impact on the clinical care of patients with this rare disease, be an important advance in the design of clinical trials and feasibility of new drug development, and provide important insight into the pathogenesis of this condition. Current measures of disease activity, including erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), while helpful in selected settings, are mostly considered highly flawed and markers whose poor correlation with disease flares makes them inadequate to help guide therapy. Similarly, ESR and CRP are clearly unhelpful as diagnostic tests for vasculitis. The current state of clinical investigation for vasculitis relies heavily upon determination of disease status solely by clinical presentation and investigator opinion. Thus, discovery and validation of more precise markers that quantifiably measure activity, predict disease course, and correlate with an important biological process, would be of great importance. Knowledge to be gained from this study could potentially be highly important. Discovery of effective biomarkers of vasculitis and assessment of long term disease course and complications by the collection of clinical and diagnostic imaging studies proposed could lead to better care and less toxic treatment regimens. Furthermore, insight into the pathophysiology of vasculitis could be gained and this might lead to better treatments and improved outcomes in terms of reduction of vascular and treatment related complications. Ideally, excellent biomarkers reflect a sophisticated understanding of the pathophysiology of a disease.

  Study phs000590

• Field_effect_of_healthy_and_diseased_livers

  Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences).

  Study EGAS00001002382

• A National Translational Science Network of Precision-Based Immunotherapy for Primary Liver Cancer (PLC)

  The primary objective of the NCI-CLARITY study is to establish a biospecimen repository for genomic, genetic and epigenetic analysis to study the biology of primary liver cancer (PLC) development and progression. Secondary objectives include predicting overall and progression-free survival following immunotherapy. In the retrospective phase, anonymous archival tissue from PLC patients was obtained from five participating sites. Whole exome and transcriptome sequencing was generated and used to predict overall survival in response to immunotherapy.

  Study phs003074

• Genome-Wide Characterization of Pancreatic Adenocarcinoma Patients Using Next Generation Sequencing

  In this study, we whole genome sequenced tumor/normal pairs from three pancreatic adenocarcinoma patients to separately characterize each patient with respect to somatic alterations. For 2 patients for whom tumor RNA was available, we also performed RNA sequencing to evaluate gene expression changes. While additional sequencing is needed to improve our understanding of the disease, the information acquired from this study contributes to our knowledge base on pancreatic cancer and helps to establish a foundation for identifying and developing more efficacious treatments for patients.

  Study phs000550

• OMKar

  The whole genome karyotype refers to the sequence of large chromosomal segments that make up an individuals genotype. karyotype analysis, which includes descriptions of aneuploidies and other rearrangements is crucial for understanding genetic risk factors, for diagnosis, treatment decisions, and genetic counseling linked to constitutional disorders. The current karyotyping standard is based on microscopic examination of chromosomes, a complex process that requires high expertise and offers Mb scale resolution. Optical Genome Mapping (OGM) technology can identify large DNA lesions in a cost-effective manner. In this paper, we developed OMKar, a method that uses OGM data to create a virtual karyotype. OMKar processes Structural (SV) and Copy Number (CN) Variants as inputs and encodes them into a compact breakpoint graph. It recomputes copy numbers using Integer Linear Programming to maintain CN balance and then identifies constrained Eulerian paths representing entire donor chromosomes. In tests using 38 whole genome simulations of constitutional disorders, OMKar reconstructed the karyotype with 88% precision and 95% recall on SV concordance and 95% Jaccard score on CN concordance. We applied OMKar to 50 prenatal, 41 postnatal, and 63 parental samples from ten different sites. OMKar reconstructed the correct karyotype in 144 out of 154 samples, covering 25 of 25 aneuploidies, 32 of 32 balanced translocations, and 72 of 82 unbalanced variations. Detected constitutional disorders included Cri-du-chat, Wolf-Hirschhorn, Prader-Willi deletions, Down, and Turner syndromes. Importantly, it identified a plausible genetic mechanism for five cases of constitutional disorder that were not detected by other technologies. Together, these results demonstrate the robustness of OMKar for OGM-based karyotyping.

  Study EGAS00001008245

• IGNITE: Implementing GeNomics In practice: Genomic Medicine Implementation - The Personalized Medicine Program

  IGNITE is an NIH-funded network dedicated to supporting the implementation of genomics in healthcare. IGNITE was created to enhance the use of genomic medicine by supporting the development of methods for incorporating genomic information into clinical care and exploration of the methods for effective implementation, diffusion and sustainability in diverse clinical settings. As part of the IGNITE network, the University of Florida Health Personalized Medicine Program partners with health professionals and patients at UF Health and across the state to develop, implement, study and refine methods that allow genetic information to be used as a routine part of patient care. The program's initial focus is on pharmacogenetics. We also aimed to develop and implement innovative genomic medicine educational programs for health-care providers, health professions students, patients.

  Study phs001978

• GSCAN GWAS Meta-analysis of Tobacco and Alcohol use (GSCAN-GWAS)

  This study was a meta-analysis of genome-wide association study (GWAS) of substance use across 1.2 million total participants with European ancestry (some phenotypes are based on fewer participants). The phenotypes were chosen to represent different stages and kinds of substance use from initiation (age of smoking initiation) to regular use (cigarettes per day and drinks per week) to cessation (smoking cessation). For each of those phenotypes, collaborators shared their GWAS summary statistics, which were then meta-analyzed using a method that incorporates into the meta-analytic weighting the sample size, allele frequency and imputation quality score.

  Study phs001809