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• Profiling RNA Translation in Pediatric Medulloblastoma

  This study provides RNA-sequencing and ribosome profiling data for patient-derived cell lines and patient tissue samples for children with medulloblastoma. Ribosome profiling is a variant protocol of RNA-sequencing that directly sequences ribosome-bound RNA fragments only. Associated RNA-seq and Ribo-seq data obtained separately for some cancer cell lines can be found on the NCBI SRA as PRJNA957428. Samples were processed for poly-A mRNA sequencing using the Roche Kapa Kit. Ribosome profiling was performed as described in the manuscript referenced below (Hofman et al.) and based on the article by McGlincy et al., Methods (2017). Ribo-seq data were analyzed for sample quality using RiboseQC (Calviello, Nat Struct Mol Biol, 2020). These data were used to quantify P-sites of open reading frames. RNAseq and ribo-seq data were integrated and compared to determine translational efficiency values using TPM (Ribo-seq) over TPM (RNA-seq) as the metric. Ribo-seq data on 14 samples and RNAseq data on 21 samples derived from 16 fresh-frozen surgical samples for medulloblastoma and 5 autopsy samples are available through dbGaP. A second cohort of 4 medulloblastoma samples (RNAseq, Ribo-seq) related to this study can be found on the EGA at EGAS00001007426.

  Study phs003446

• 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

• Cell-free DNA methylation profiling for non-invasive detection and classification of lymphoma

  Compared with traditional tissue biopsies used for lymphoma diagnosis, cell-free DNA methylation profiling offers a minimally invasive approach capable of capturing lymphoma-specific epigenetic alterations. This study investigates genome-wide methylation patterns in plasma using cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq). Differential methylation analysis of discovery samples identified lymphoma-associated hypermethylated regions that were used to develop classification models for lymphoma detection. Validation analyses demonstrated high accuracy and strong associations between cfDNA methylation scores and independent measures of tumor burden and clinical outcome. These findings support cfDNA methylation profiling as a sensitive approach for non-invasive lymphoma diagnosis.

  Study EGAS50000001463

• 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

• 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

• 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

• 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

• 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

• 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

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

  ATAC-seq data for 3 sample(s) for naive B cell from tonsil, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002903

• Role of Genetic Factors in the Pathogenesis of Lung Disease

  Three individuals with lymphangioleiomyomatosis (LAM) underwent evaluation for Tuberous Sclerosis Complex (TSC)-associated mucocutaneous and internal findings. Next-generation sequencing (NGS) of cutaneous findings was used to confirm clinical suspicion for mosaic TSC in individuals with LAM. Mosaic mutations in TSC2 were found in these three individuals.

  Study phs003108

• Japanese Alzheimer's disease neuroimaging initiative

  Japanese ADNI aims to establish imaging and biofluid markers that can predict and monitor the progression of changes in the brains of elderly individuals with AD, mild cognitive impairment (MCI) or normal cognition, and eventually be used as a surrogate markers for the clinical trials of DMDs for AD.

  Study JGAS000051

• HCA_Genotyping_Adult_Teichmann_DNA

  This project involves a genotyping dataset generated using the UK Biobank Axiom™ Array Kit from donor samples provided by the Cambridge Biorepository for Translational Medicine (CBTM). The dataset includes high-quality genome-wide array data suitable for a broad range of research applications in genomics and translational medicine.

  Study EGAS00001008228

• Hybrid untargeted and targeted RNA sequencing facilitates genotype-phenotype associations at single-cell resolution

  Raw sequencing data for the manuscript "Hybrid untargeted and targeted RNA sequencing facilitates genotype-phenotype associations at single-cell resolution". It includes PacBio long-read scRNA-seq, illumina short-read scRNA-seq and Twist-based targeted scRNA-seq datasets for two adrenal samples.

  Study EGAS50000001537

• RNAseq of 12q-amplified osteosarcomas

  RNA-seq of 12q-amplified osteosarcomas for detection of gene fusions and gene expression analysis. RNA-seq was used to look for novel gene fusions and promoter swapping events, and study the expression levels of identified 3' partners. Additionally, global gene expression patterns were used to separate cases into clusters.

  Study EGAS50000000494

• Genotype variables of the 61 COVID-19 patient cohort used in the main project of data integration

  We selected SNPs with a minor allele frequency (MAF) higher than 10% in the Caucasian population from the Ensembl database. Specifically, we selected ACE2 (rs2285666), MX1 (rs469390), and TMPRSS2 (rs2070788) for the present analysis. For more information, please refer to:

  Study EGAS50000000589

• Genomic and clinical data from IMmotion010, a phase 3 randomised clinical trial testing adjuvant atezolizumab versus placebo for patients with renal cell carcinoma at increased risk of recurrence following resection

  778 patients were randomized in this study. Pre-treatment bulk RNAseq of primary tumors was conducted for 754 patients. For 80 patients, bulk RNAseq analysis of a metastastic biopsy was conducted. For these 80 pairs, DNA alterations were assessed in pre-treatment and at recurrence using FoundationOne.

  Dataset EGAD50000001827

• Microinjection_of_hIPSC_derived_intestinal_organoids_with_Salmonella_Typhimurium

  To generate an RNA-Seq dataset for organoids apically stimulated with Salmonella Typhimurium.These data are 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 EGAS00001001253

• Immunodeficiency_

  We are doing single-cell RNAseq from B cells from monozygotic twins discordant for common variable immunodeficiency 1) 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 please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002667

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• _Isotype_resolved_sequencing_of_B_cell_receptor__in_sorted_memory_populations

  Optimisation of ex vivo Memory B cell Expansion/Differentiation for Interrogation of Rare Peripheral Memory B Cell Subset Responses 1) 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 please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002633

• Korean Lung Cancer - 36 pair WES data

  This study includes 36 paired samples of Korean Lung Cancer paitients.36 Lung Cnacer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WES study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002843

• Whole-exome sequencing of the transposition of the great arteries

  Transposition of the great arteries (TGA) is one of the most severe types of congenital heart diseases. Understanding the pathogenesis of TGA is urgently needed for patient management of this severe disease. We sought to systematically examine thegenetic etiology for isolated nonsyndromic TGA using whole-exome sequencing.

  Study EGAS00001004175

• DNA methylation (RRBS) data for the validation the glioblastoma progression study (GBMatch).

  Genome-wide profiling of DNA methylation levels by RRBS in 150 glioblastoma tumor samples. Patients were selected to represent the general population of glioblastoma patients based on Austrian Brain Tumor Registry. These DNA methylation profiles were created for the validation of the glioblastoma progression study (GBMatch) and consist of 106 profiles from FFPE samples and 44 profiles from fresh-frozen samples. For the 44 fresh-frozen samples also WGS data (43 genomes) and RNA-seq data (37 transcriptomes) have been produced for validation purposes.

  Dataset EGAD00001004074

• January 2018 data update (bam/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.

  January 2018 data update (bam/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 EGAD00001003962

• The role of MALT1 in driving IBN resistance in MCL

  The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment.

  Study EGAS00001006832

• RNA-Seq on OCIAML-22 Fractions

  The donor AML patient (unsorted) that was used to generate OCI-AML22 was expanded for the indicated number of days (Donor: 0 day, 12d: 12 days, 2m: 2 months, 3m: 3 months), then sorted for the indicated fraction (CD34p: CD34+; CD34m: CD34-, CD38m: CD38-, CD38m: CD38-).

  Study EGAS00001006512

• Aligned whole genome bisulfite sequencing data 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.

  Aligned whole genome bisulfite sequencing data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001435

• Comparison of protocols for deriving pancreatic progenitors from hPSCs (ATAC-seq)

  This dataset contains 27 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared ATAC-seq libraries for the 27 samples, and sequenced them on Illumina HiSeq4000.

  Dataset EGAD00001004824

• Reference exome data for Australian Aboriginal populations from Western Australia and the Northern Territory

  Here we provide a catalogue of variants called after sequencing the exomes of 50 Aboriginal individuals from the Northern Territory (NT) of Australia and compare these to 72 previously published exomes from a Western Australian (WA) population of Martu origin. Sequence data for both NT and WA samples were processed using an ‘intersect-then-combine’ (ITC) approach, using GATK and SAMtools to call variants. The data is provided as 2 VCF files, one for the WA population and one for the NT population.

  Dataset EGAD00001005189

• February 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.

  February 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 EGAD00001006220

• FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

  28 patients. Cell-free DNA and leukocyte DNA, both from before any neoadjuvant treatment. Tumor FFPE tissue (plus metastasic tissue for some patients) from after any neoadjuvant treatment. Some cfDNA from follow-up time points (e.g. after neodj. treatment or in the clinical course). IDT xgen Pan-Cancer panel for hybridisation capture. Illumina TruSeq library prep for cfDNA and leukocyte DNA, Illumina DNA Prep for FFPE DNA. n=150 libraries in total.

  Dataset EGAD00001010081

• Compilation of Aggregate Genomic Data for General Research Use

  This study contains all authorized aggregate genomic data from datasets currently in dbGaP that are approved for general research use (GRU) and have no further limitations beyond those outlined in model Data Use Certification Agreement. Access to this study will be granted for one year and any additional authorized aggregate GRU datasets that become available during this one-year period. This study does not include individual-level data.

  Study phs000501