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• August 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001005335

• August 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001006383

• KiCS cancer panel data for academic and for-profit use

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009734

• Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19

  These data correspond to samples used in the following papers: 1. GWAS and meta-analysis identifies 49 genetic variants underlying critical Covid-19 2. Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19. 3. Identification of Genetic Determinants of Transcriptional Response to Metformin in Primary Human Monocytes. They are the raw RNA sequencing files as used in all downstream analysis.

  Dataset EGAD00001010176

• Drug Signatures for Prediction and Mitigation of Toxicity

  The overall goal of the drug signatures for prediction and mitigation of toxicity study is to use genomic and proteomic high-throughput measurements as the basis for computational analysis that integrates network analyses with structural constraints and dynamical models in multiple cell types to identify signatures that predict toxicity induced by 55 FDA-approved chemotherapeutic drugs and potential mitigation of this toxicity. Specifically, we have recruited and pre-screened healthy individuals to be included in our study. Ninety six male and female individuals that satisfied the initial pre-screening for the study and their sex, age, race/ethnicity recorded through an enrollment questionnaire were consented. Eighty five underwent a formal and thorough medical health screening. The evaluation involved assessment of all inclusion and exclusion criteria, a full medical history, measurement of weight, height, waist and hip circumference, heart rate, blood pressure, respiratory rate, and oxygen saturation, a physical exam and an electrocardiograph (ECG). Blood was drawn for analysis of clinical relevant parameters. A pregnancy test was included for female participants. All blood draws and pregnancy tests were sent to a certified clinical laboratory for clinical analysis. Of the 85 subjects that were screened 42 (48.3%) were deemed eligible for final inclusion. Of these 42, one declined to undergo skin biopsy and/or venesection and one subject didn’t show up for the scheduled biopsy, leaving 40 clinically healthy subjects on which a skin biopsy and venesection was performed. Fibroblast lines were established from the skin biopsies. Induced pluripotent cells (iPSC) were generated from the established fibroblast lines of these 40 clinically healthy racially diverse male and female study participants who ranged in age from 22 and 61 years through reprogramming using either the mRNA or Sendai-virus methods. One clone from each of the 40 iPSC line was fully characterized for normal karyotype, short-tandem repeat matching to the original fibroblast line (authentication), pluripotency by select pluripotent marker expression via immunocytochemistry and by mRNAseq-based PluriTest analysis, and whole-genome sequencing.

  Study phs002088

• Procardis study on novel susceptibility genes for coronary artery disease (CAD)

  An increased level of Lp(a) lipoprotein has been identified as a risk factor for coronary artery disease that is highly heritable. The genetic determinants of the Lp(a) lipoprotein level and their relevance for the risk of coronary disease are incompletely understood. METHODS: We used a novel gene chip containing 48,742 single-nucleotide polymorphisms (SNPs) in 2100 candidate genes to test for associations in 3145 case subjects with coronary disease and 3352 control subjects. Replication was tested in three independent populations involving 4846 additional case subjects with coronary disease and 4594 control subjects. RESULTS: Three chromosomal regions (6q26-27, 9p21, and 1p13) were strongly associated with the risk of coronary disease. The LPA locus on 6q26-27 encoding Lp(a) lipoprotein had the strongest association. We identified a common variant (rs10455872) at the LPA locus with an odds ratio for coronary disease of 1.70 (95% confidence interval [CI], 1.49 to 1.95) and another independent variant (rs3798220) with an odds ratio of 1.92 (95% CI, 1.48 to 2.49). Both variants were strongly associated with an increased level of Lp(a) lipoprotein, a reduced copy number in LPA (which determines the number of kringle IV-type 2 repeats), and a small Lp(a) lipoprotein size. Replication studies confirmed the effects of both variants on the Lp(a) lipoprotein level and the risk of coronary disease. A meta-analysis showed that with a genotype score involving both LPA SNPs, the odds ratios for coronary disease were 1.51 (95% CI, 1.38 to 1.66) for one variant and 2.57 (95% CI, 1.80 to 3.67) for two or more variants. After adjustment for the Lp(a) lipoprotein level, the association between the LPA genotype score and the risk of coronary disease was abolished. CONCLUSIONS: We identified two LPA variants that were strongly associated with both an increased level of Lp(a) lipoprotein and an increased risk of coronary disease. Our findings provide support for a causal role of Lp(a) lipoprotein in coronary disease.

  Study EGAS00000000055

• CATHeterization GENetics (CATHGEN)

  The CATHGEN biorepository consists of biological samples collected on 9334 sequential consenting individuals undergoing cardiac catheterization at Duke University Medical Center between 2001 and 2010 inclusive. The Institutional Review Board informed consent allowed for 50 mL of blood to be collected from fasting patients through the femoral arterial sheath during the catheterization procedure. Three 7.5 mL EDTA tubes for DNA extraction are stored at -80°C. The Duke Database for Cardiovascular Disease (DDCD) provides the bulk of the clinical data used for analysis. Follow-up includes mortality information gleaned from the National Death Index and Social Security Death Index plus follow-up phone calls and written questionnaires regarding MI, stroke, re-hospitalization, coronary re-vascularization procedures, smoking, exercise, and medication use.

  Study phs000703

• Fixation effects on variant-calling in a clinical resequencing panel

  Formalin fixation is the standard method for preservation of tissue for diagnostic purposes, including pathological review and molecular assays. However, this method is known to cause artifacts that can affect the accuracy of molecular genetic tests. We assessed the applicability of alternative fixatives to determine whether these perform significantly better on next-generation sequencing assays, and whether adequate morphology is retained for primary diagnosis, in a prospective study using a clinical-grade laboratory-developed targeted resequencing assay. We examined and quantified several parameters relating to sequencing quality and variant-calling from tumor and normal colon epithelial tissues. We identify one alterative fixative, Sakura Universal Molecular Fixative that suppresses many formalin-related artifacts while retaining adequate morphology for pathological review.

  Study EGAS00001003507

• single-cell RNA-seq Case-Control study of children progressing to Type1 diabetes

  Single-cell RNA sequencing was carried out on four selected PBMC samples of Finnish children at risk of developing Type 1 diabetes and their gender age and HLA matched control children using 10X genomic platform. All four Case children were positive for multiple islet specific autoantibodies and two of them also progressed to clinical disease during the follow up whereas the control children remain negative for all autoantibodies. Age at seroconversion for Case 2, 3, 5, and 9 children is 12, 18, 24, and 18 months, respectively. Age at sampling, in months, for the pairs was as follows (Case/Control): pair 2:24/24; pair 3: 12/18; pair 5: 12/12; pair 9:24/18.

  Study EGAS00001004070

• Deep amplicon sequencing to infer malignant clonal populations for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  A total of 192 positions per patient were deeply sequenced in each corresponding tumor sample (including 4 experimental controls and SNVs predicted to originate at each node of the sample phylogeny, see Zhang et al. for details). Genomic DNA templates were used as starting material to generate PCR products. PCR was set up using Phusion DNA polymerase according to the manufacturer’s specifications. The standard PCR conditions used were an initial denaturation at 98C for 30 seconds, followed by 35 cycles of 98C for 10 seconds, 60C for 15 seconds and 72C for 8 seconds, and a final extension at 72C for 10 minutes. PCR products were cleaned up using PCRClean DX beads. Amplicons were pooled by template for sequencing sample preparation. Sample preparation involved a second round of amplification using Phusion DNA polymerase with 6 PCR cycles, with primers specified in Zhang et al. DNA quality was assessed using the Caliper LabChip GX HighSensitivity Assay and DNA quantity was measured using a Qubit dsDNA HS assay kit on a Qubit fluorometer. The indexed libraries were pooled together and sequenced on the Illumina NextSeq500 platform with paired-end 150bp reads using v2 chemistry reagents.

  Dataset EGAD00001003986

• Exploring germline and somatic mutagenesis in the extended family with germline pathogenic variant in POLD1

  This study aimed to estimate the influence of POLD1 L474P on somatic and germline mutagenesis. We studied the mutation rate and spectra in germline and soma in an extended family harboring the POLD1 c.1421T>C p.(Leu474Pro) pathogenic variant. The study includes WGS data for DNA extracted from blood, fibroblasts or buccal swabs from the 16 family members, from DNA obtained single-cell derived colonies obtained from immortalized fibroblasts for 8 of 16 family members and from the same single-cell derived immortalized fibroblasts after approximately 40 passages for 6 out of 8 family members. Additionaly, study includes WXS sequencing for 1 tumor FFPE sample and adjacent normal tissue from the individual from one family member.

  Study EGAS00001006434

• The data access committee for "Validation of cfDNA fragmentome analyses for early detection of liver cancer"

  Dac EGAC00001003543

• Medulloblastoma WES

  WES for tumor and normal samples

  Study EGAS50000000261

• Deep_sequencing_of_melanoma_for_driver_mutations

  Deep sequencing of melanoma for driver mutations

  Study EGAS00001000857

• Towards standardized whole exome sequencing (WES) for cancer patients: lessons from a multicentric pilot study

  A growing number of druggable targets and national initiatives for precision oncology necessitate broader genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a sensitivity between 91-95% and a positive predictive value (PPV) of 82-95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Deviations were observed for cases with low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79-1, TMB: 0.97-0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.

  Study EGAS00001007363

• This study generated Oxford Nanopore long read sequencing data of cancer cell line mixtures for validating long-read variant calls in cancer genomics

  Long-read sequencing (LRS) improves genome alignment and facilitates resolving variants in complex genomic regions, making it a promising approach for cancer variant detection and biomarker discovery. Here, we evaluate the performance of LRS to detect somatic variants across different tumour purities and sequencing depths by comparing to somatic variants from short-read sequencing. We generated experimental mixtures of cancer cell lines and matched normal cell lines to simulate 10 tumour purities (ranging from 0 to 100% tumour content). This resulted in 22 samples which were sequenced using whole genome LRS to a targeted depth of 60x and somatic variants were identified. We downsampled sequencing data to explore the optimal read depth for somatic variant detection. Our results show that long-read variant calling tools achieve recall rates comparable to short-read gold standards. While a tumour sequencing depth of 30x to 60× is generally sufficient for detecting common variants, particularly structural variants (SVs), sequencing the matched normal sample at adequate depth is crucial for accuracy. Notably, we found variants unique to LRS that may represent real and previously undetected events. This study highlights key factors for optimising cancer genome sequencing with LRS and provides a comprehensive dataset of cell line mixtures for future research and tool development.

  Study EGAS00001008107

• Elucidating Mechanisms of the Graft versus Leukemia Effect of Hematopoietic Stem Cell Transplant for Acute Myeloid Leukemia

  Donor lymphocyte infusion (DLI) is an established mode of adoptive cellular therapy for treatment of relapsed disease after allogeneic hematopoietic stem cell transplantation (HSCT). For patients with acute myeloid leukemia (AML), the response rate to DLI is only 20%. Here we use next generation sequencing technologies to understand the transcriptomic and immunologic features associated with response or resistance to therapy.

  Study phs003630

• Single-cell transcriptome analysis of B-cell development in the ABO platform

  The dataset includes samples from four individual donors, pooled at each cell-harvesting time point (days 21, 28, and 35). Single-cell RNA sequencing was performed on the 10x Genomics Chromium platform using GEM-X Single Cell 5′ v3 and GEM-X Single Cell V(D)J v3 for BCR profiling. For each timepoint, paired libraries were constructed: a 5′ GEX library and a V(D)J-B library. Per reaction 350,000-400,000 cells were loaded, aiming for 60,000 cells per reaction. Pooled libraries were sequenced on an Illumina NovaSeq X sequencer. 50,000 read pairs per cell for GEX and 5,000 read pairs per cell for V(D)J were targeted.

  Dataset EGAD50000002433

• Normal brain controls for ICGC PedBrain DNA methylation sequencing

  DNA methylation profiling of 8 control samples from adult (4) and fetal brain (4) used, for example, for the following studies: Mack, Witt, et al. Epigenomic alterations define lethal CIMP-positive ependymomas of infancy. Nature 506(7489):445-450, 2014 (see EGAS00001000443) Hovestadt, et al. Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. 510(7506):537-541, 2014 (see EGAS00001000561)

  Study EGAS00001000909

• March 2019 data update for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2019 data update for cord blood CD34+CD38-, CMP, GMP, MEP, monocyte, erythroid precursor, B cell and primary AML total blasts reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium. This dataset contains data for samples: CEMT0158 CEMT0159 CEMT0160 CEMT0161 CEMT0162 CEMT0163 CEMT0164 CEMT0165 CEMT0166 CEMT0167 CEMT0168 CEMT0169 CEMT0170 CEMT0171 CEMT0172 CEMT0189

  Dataset EGAD00001004950

• DAC for study CMMRD–associated high-grade glioma

  This Data Access Committee (DAC) is responsible for de-identified, summarized somatic variant call data derived from paired tumor–blood Whole-exome sequencing of human samples in a glioma research study. Access requests are approved without additional restrictions and are granted solely for health-related research purposes.

  Dac EGAC50000000855

• Long-read whole genome sequencing as a tool for variant detection in inherited retinal dystrophies

  WGS sequencing using nanopore long reads sequencing. These data is used for the diagnosis of patients with inherited retinal dystrophies.

  Study EGAS50000000846

• Whole Genome Sequencing for Korean Diffuse Gastric Cancer

  Fastq files for the whole genome sequencing data (Illumina HiSeq 2500; 32.6-fold) for two diffuse gastric cancers revealing the fusion breakpoints. 2102T: CTNND1-ARHGAP26 gene fusion (g.chr11:57,578,103-g.chr5:142,358,707) 354T: ANXA2-MYO9A gene fusion (g.chr15:60,656,550-g.chr15:72,157,966)

  Dataset EGAD00001003953

• The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

  RNA-seq data for ALL patients as described in "The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001006335

• Hyperpolarized carbon-13 MRI for very early response assessment of neoadjuvant chemotherapy in breast cancer patients

  Transcriptomic data for five patients with breast cancer undergoing neoadjuvant chemotherapy and hyperpolarised 13C-MRI for early response assessment

  Dataset EGAD00001008141

• First genome-wide association study in an Australian Aboriginal population provides insights into genetic risk factors for Body Mass Index and Type 2 Diabetes

  A body mass index (BMI) >22kg/m2 is a risk factor for type 2 diabetes (T2D) in Aboriginal Australians. To identify loci associated with BMI and T2D we undertook a genome-wide association study using 1,355,133 quality-controlled single nucleotide polymorphisms (SNPs) genotyped (Illumina 2.5M Duo Beadchip) in 402 individuals in extended pedigrees from a Western Australian Aboriginal community. Imputation using the thousand genomes (1000G) reference panel extended the analysis to 6,724,284 post quality-control autosomal SNPs. No associations achieved genome-wide significance, commonly accepted as P<5x10-8. Nevertheless, genes/pathways in common with other ethnicities were identified despite the arrival of Aboriginal people in Australia >45,000 years ago. The top hit (rs10868204 Pgenotyped=1.50x10-6; rs11140653 Pimputed_1000G=2.90x10-7) for BMI lies 5’ of NTRK2, the type 2 neurotrophic tyrosine kinase receptor for brain-derived neurotrophic factor (BDNF) that regulates energy balance downstream of melanocortin-4 receptor (MC4R). PIK3C2G (rs12816270 Pgenotyped=8.06x10-6; rs10841048 Pimputed_1000G=6.28x10-7) was associated with BMI, but not with T2D as reported elsewhere. BMI also associated with CNTNAP2 (rs6960319 Pgenotyped=4.65x10-5; rs13225016 Pimputed_1000G=6.57x10-5), previously identified as the strongest gene-by-environment interaction for BMI in African-Americans. The top hit (rs11240074 Pgenotyped=5.59x10-6, Pimputed_1000G=5.73x10-6) for T2D lies 5’ of BCL9 that, along with TCFL2, promotes beta-catenin’s transcriptional activity in the WNT signaling pathway. Additional hits occurred in genes affecting pancreatic (KCNJ6, KCNA1) and/or GABA (GABRR1, KCNA1) functions. Notable associations observed for genes previously identified at genome-wide significance in other populations included MC4R (Pgenotyped=4.49x10-4) for BMI and IGF2BP2 Pimputed_1000G=2.55x10-6) for T2D. Our results may provide novel functional leads in understanding disease pathogenesis in this Australian Aboriginal population.

  Study EGAS00001001004

• This DAC takes care of requests for data for the Swiss epigenetic colorectal cancer cohort study, SWEPIC

  Dac EGAC00001003471

• Dataset for the spanish node

  Dataset for the spanish node

  Dataset EGAD50000000884

• PGRN/PAT: The genomic basis for susceptibility to drug-induced long QT syndrome (diLQTS)

  The goal of this study was to search for genetic variants that could be responsible for modifying the risk of drug-induced long QT syndrome (diLQTS). diLQTS is a relatively common adverse drug event and has been a leading cause for drug relabeling and withdrawal from the market. Our hypothesis, that variants in genes which regulate electrical properties in the heart modify the risk of diLQTS, was tested by sequencing approximately 225 patients of European descent using next-generation targeted captured or whole exome sequencing. Data from cases and controls (1:2) were analyzed to identify both rare and common genetic variation.

  Study phs000808

• DAC for present-day Central Asia genotype data at the Centre for GeoGenetics, Natural History Museum of Denmark.

  Dac EGAC00001000894

• DAC for "The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia"

  Dac EGAC00001001501

• Navarrabiomed DAC for XPAND project

  This DAC is created for the XPAND project by the Translational Bioinformatics unit.

  Dac EGAC50000000462

• Leukemia Data Access committee for the deposited data. The committee consists of the principal investigators for the data set.

  Dac EGAC00001003565

• University of Michigan Clinical Sequencing Exploratory Research (CSER)

  Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing & Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics & Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

  Study phs000673

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Multi-Ethnic Study of Atherosclerosis (MESA)

  Cohort Description The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (CVD) and the risk factors that predict progression to clinically overt CVD or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Participants of this study are limited to MESA Classic participants. MESA Family and MESA Air Pollution cohorts are excluded from C4R. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3119 MESA participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 1933 MESA participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1058 MESA participants in C4R. Derived data includes 43 variables for up to 3283 MESA participants in C4R. Phenotype data includes 113 variables for up to 3136 MESA participants in C4R.

  Study phs003017

• Resequencing (MIPS) of candidate genes for Keratoconus (2020)

  In this study, we selected 34 candidate genes for KC based on previous Whole Exome Sequencing (WES) and the literature, and resequenced them in 745 KC patients and 810 ethnically matched controls. Data analysis was performed using the single variant association test as well as gene-based mutation burden and variance components tests. In our study, we detected enrichment of genetic variation across multiple gene-based tests for the genes COL2A1, COL5A1, TNXB, ZEB1 and ZNF469. The top hit in the Fisher’s exact test was obtained for a common variant in the COL12A1 gene. Interestingly, COL5A1, TNXB, ZNF469 and COL12A1 are all known Ehlers-Danlos Syndrome (EDS) genes. Though the co-occurrence of KC and EDS has been reported previously, this study is the first to demonstrate a consistent role of genetic variants in EDS genes in the etiology of KC. In conclusion, our data show a shared genetic etiology between KC and EDS, and clearly confirm the currently disputed role of ZNF469 in disease susceptibility for KC. Besides the role for EDS genes, we also confirm the previously reported involvement of genetic variation in ZEB1 in KC.

  Study EGAS00001004267

• Data access committee for genomic and clinical data produced by the Institute for Biomedical Technology.

  Dac EGAC00001000110

• DAC for the BCTL

  DAC for submissions from the BCTL (Hopital Jules Bordet, Université LIbre de Bruxelles)

  Dac EGAC50000000323

• WGS minibam files for SJLIFE

  WGS minibam files for SJLIFE

  Dataset EGAD00001003396

• BiSeqS

  Runs that contain data for the sensitivity and specificity experiments for BiSeqS.

  Dataset EGAD00001003323

• dataset for BGI bladder cancer project

  dataset for BGI bladder cancer project

  Dataset EGAD00001000758

• International Standards for Cytogenomic Arrays

  The International Standards for Cytogenomic Arrays (ISCA) Consortium is a rapidly growing group of clinical cytogenetics and molecular genetics laboratories committed to improving quality of patient care related to clinical genetic testing using new molecular cytogenetic technologies including array comparative genomic hybridization (aCGH) and quantitative SNP analysis by microarrays or bead chip technology. The ISCA Consortium is now working with the sequencing community to extend the goals of standardization, collaboration, and data sharing. To reflect this combined effort, we are becoming ICCG, or the International Collaboration for Clinical Genomics. Efforts of the Consortium include: Clinical Utility: The ISCA Consortium has made recommendations regarding the appropriate clinical indications for cytogenetic array testing (Miller et al. AJHG 2010, PMID: 20466091). Currently, discussions are focused on pediatric applications for children with unexplained developmental delay, intellectual disability, autism and other developmental disabilities. A separate committee has been developed to address appropriate cancer genetic applications (http://www.urmc.rochester.edu/ccmc/). Evidence-based standards for cytogenomic array design: The Consortium will develop recommendations for standards for the design, resolution and content of cytogenomic arrays using an evidence-based process and an international panel of experts in clinical genetics, clinical laboratory genetics (cytogenetics and molecular genetics), genomics and bioinformatics. This design is intended to be platform and vendor-neutral (common denominator is genome sequence coordinates), and is a dynamic process with input from the broader genetics community and evidence-based review by the expert panel (a Steering Committee with international representation). Public Database for clinical and research community: It is essential that a publicly available database be created and maintained for cytogenetic array data generated in clinical testing laboratories. This will be integrated into the current dbGaP database at NCBI/NIH and released through dbVar, and curated by a committee of clinical genetics laboratory experts. The very high quality of copy number data (i.e., deletions and duplications) coming from clinical laboratories combined with expert curation will produce an invaluable resource to the clinical and research communities. Standards for interpretation of cytogenetic array results: Using the ISCA Database, along with other genomic and genetics databases, the Consortium will develop recommendations for the interpretation and reporting of pathogenic vs. benign copy number changes as well as imbalances of uncertain clinical significance. Membership in the ISCA Consortium is open to all individuals and laboratories involved in cytogenetic array testing who are committed to free data sharing and to participation in a process to develop evidence-based standards and guidelines to improve patient care. ISCA is available through dbVar: http://www.ncbi.nlm.nih.gov/dbvar/studies/nstd37/ http://www.ncbi.nlm.nih.gov/dbvar/studies/nstd75/ http://www.ncbi.nlm.nih.gov/dbvar/studies/nstd45/ http://www.ncbi.nlm.nih.gov/dbvar/studies/nstd101/

  Study phs000205

• DAC for "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas"

  This DAC will be created for sequencing data for the manuscript "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas." The dataset includes Illumina-based exome sequencing of tumor specimens, paired blood specimens, bulk RNA-seq, and Visium FFPE.

  Dac EGAC50000000579

• WTCCC case-control study for Hypertension

  WTCCC genome-wide case-control association study for Hypertension (HT) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000009

• Epigenomic dataset of Human Hepatocellular Carcinoma for EpiHK

  This dataset is generated for EpiHK. It contains Histone PTM ChIP-seq, WGBS, RNA-seq of Human Hepatocellular Carcinoma and tumor adjacent normal tissue sample.

  Study EGAS50000000039

• scRNA-seq and Amplicon data for MPN/HC samples

  This data set contains scRNA-seq data from MPN patients and healthy individuals. It is accompanied by amplicon data for the JAK2V617F mutation. For each individual an INFa treated and untreated sample is included.

  Dataset EGAD50000001321

• BLUEPRINT September 2016, ATAC-seq for osteoclast from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for osteoclast from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002907

• BLUEPRINT September 2016, ATAC-seq Multiple Myeloma for plasma cell from bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) Multiple Myeloma for plasma cell from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002920

• BLUEPRINT September 2016, ATAC-seq for plasma cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for plasma cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002912