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• H3K27ac ChIP-seq in a selected group of AML patients

  ChIP-seq data were generated for a number of selected patients to investigate changes in enhancer and promoter regions. ChIP was performed as described previously with slight modifications27. Briefly, cells were crosslinked with 1% formaldehyde for 10 minutes at room temperature and the reaction was quenched with glycine at a final concentration of 0.125 M. Chromatin was sheared using the Covaris S220 focused-ultrasonicator to an average size of 250–350 bp. A total of 2.5 µg of antibody against H3K27ac (Abcam, ab4729) was added to sonicated chromatin of 2 × 106 cells and incubated overnight at 4 °C. Protein A sepharose beads (GE healthcare) were added to the ChIP reactions and incubated for 2 h at 4 °C. Beads were washed and chromatin was eluted. After crosslink reversal, RNase A and proteinase K treatment, DNA was extracted with the Monarch PCR & DNA Cleanup kit (NEB). Sequencing libraries were prepared with the NEBNext Ultra II DNA Library Prep Kit for Illumina (NEB) according to the manufacturer’s instructions. The quality of dsDNA libraries was analyzed using the High Sensitivity D1000 ScreenTape Kit (Agilent) and concentrations were assessed with the Qubit dsDNA HS Kit (Thermo Fisher Scientific). Libraries were single-end sequenced on a HiSeq 4000 (Illumina). ChIP-seq reads were aligned to the human reference genome build hg19 with bowtie

  Dataset EGAD00001007582

• SARS-CoV-2 host genetics and COVID-19 outcomes in admixed Brazilians with extreme phenotypes

  COVID-19 comprises clinical outcomes of SARS-CoV-2 infection and is highly heterogeneous, ranging from asymptomatic individuals to deceased young adults without comorbidities. There is growing evidence that host genetics play an important role in COVID-19 severity, including inborn errors of immunity, age-related inflammation and immunosenescence. This study proposes a strategy of subject’s ascertainment based on phenotypic extremes to take part in genomic studies and elucidate intrinsic risk factors involved in COVID-19 severe outcomes. Different cohorts were collected and submitted to Next-Generation Sequencing (Whole exome and whole genome sequencing).

  Study EGAS00001006376

• Whole Exome Data for two affected individuals in a family with severe congenital neutropenia (SCN).

  Raw Whole Exome Sequencing data from Blood samples drawn from related Female participants presenting severe congenital neutropenia.

  Dataset EGAD00001005937

• A spatiotemporal organ-wide gene expression and cell atlas of the developing human heart

  Dataset includes 2 scRNA-seq samples from a 6.5-7 post-conception weeks human embryonic heart and 19 samples from 4.5-9 post-conception weeks human embryonic hearts analyzed with the Spatial Transcriptomics method. H&E stains can be sent if requested.

  Dataset EGAD00001005468

• Epigenomic analysis of human dopaminergic neuron differentiation reveals LBX1, NHLH1 and NR2F1/2 as necessary for lineage specification

  Sample information: The 56 samples produced in this project come from the human iPSC line GM17602 (Coriell) where a tyrosine hydroxylase-T2A-mCherry reporter was inserted. A combination of epigenetic analysis (ATAC/ChIP) along transcriptomics.

  Dataset EGAD00001009288

• The Oral Microbiome and Head and Neck Cancer

  Oral microbiota may influence head and neck squamous cell carcinoma (HNSCC) development, potentially related to carcinogen metabolism. The human oral cavity hosts a diverse microbiota, including bacteria and fungi. We performed shotgun sequencing and ITS1 sequencing on 236 HNSCC case participants who developed HNSCC during a mean follow-up of 5.1 years and 458 matched controls who remained HNSCC-free. Oral samples were obtained from a prospective nested case-control study within three epidemiological cohorts: the American Cancer Society Cancer Prevention Study II Nutrition Cohort (ACS CPS-II), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), and the Southern Community Cohort Study (SCCS). Control participants were selected using 2:1 frequency matching based on cohort, age, sex, race and ethnicity, and time since oral sample collection.

  Study phs004018

• GCparagon: Evaluation and correction of GC biases in cell-free DNA at the fragment level

  We present GCparagon, a two-stage algorithm for computing and correcting GC biases in cell-free DNA (cfDNA) samples. The length of the highly fragmented cfDNAs and the number of GC bases are essential parameters in the calculations. Regions of low mappability, known reference genome assembly errors and regions surrounding assembly gaps are excluded from the bias computation. GCparagon outputs a bias matrix and an optional tagged BAM file with GC bias balance weights as alignment tags. Parallelization allows calculation of a GC bias estimate in less than 2 minutes per sample with between 99.0% and 99.9% of fragments already corrected. We propose that GCparagon can help standardize cfDNA applications and evaluate the impact of GC bias on algorithms used in the analysis of liquid biopsy data.

  Study EGAS00001006963

• Starting Treatment with Agonist Replacement Therapies (START): A Randomized Trial of Methadone vs Buprenorphine/Naloxone for the Treatment of Opioid Dependence

  The Starting Treatment with Agonist Replacement Therapy (START) study was a 24-week, open-label, randomized trial of methadone versus Suboxone (buprenorphine/naloxone) for the treatment of opioid dependence. Patients were over the age of 18 and met DSM-IV qualifications for opioid dependence. The primary goal of the study was to determine if either medicine was associated with liver toxicity issues in this vulnerable patient population. Liver enzymes were measured at four time points. Urinalysis for opioids, cocaine, cannabis, benzodiazepines, and methamphetamine were performed on a weekly basis. A flexible dosing scheme was used during which physicians could alter medication dose based on withdrawal symptoms and urinalysis results. Neither medication was found to be associated with liver enzyme levels. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001135

• Multi-omics identify falling LRRC15 as a COVID-19 severity marker and persistent pro-thrombotic signals in convalescence

  Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we perform longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identify transcriptomic and proteomic signatures of COVID-19 severity, and find distinct temporal molecular profiles in patients with severe disease. Supervised learning reveals that the plasma proteome is a superior indicator of clinical severity than the PBMC transcriptome. We show that a decreasing trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, is associated with a more severe clinical course. Strikingly, we observe that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.

  Study EGAS00001006778

• Comprehensive cancer predisposition gene testing in an adult multiple primary tumor series shows a broad range of deleterious variants and atypical tumor phenotypes

  Multiple primary tumors (MPT) affect a substantial proportion of cancer survivors and may result from various causes including inherited predisposition. Currently, germline genetic testing of MPT cases for cancer predisposition gene (CPG) variants is mostly targeted by tumor type. We ascertained pre-assessed MPT cases from genetics centers (defined as ≥2 primaries by age 60 years or ≥3 by 70) and performed whole genome sequencing (WGS) on 460 individuals from 440 families. Despite previous negative genetic assessment/molecular investigations, pathogenic variants in moderate and high-risk CPGs were detected in 67/440 (15.2%) of probands. WGS detected variants that would not be (or were not) detected by targeted resequencing strategies including structural variants at low frequency (6/440 (1.4%) of probands). In most individuals with a germline variant assessed as pathogenic or likely pathogenic (P/LP), at least one of their tumor types was characteristic of variants in the relevant CPG. However, in 29 probands (42.2% of those with a P/LP variant) the tumor phenotype appeared discordant. The frequency of individuals with truncating or splice site CPG variants and at least one discordant tumor type was significantly higher than a control population (χ2=43.642 P=<0.0001). 2/67 (3%) of probands with P/LP variants had evidence of multiple inherited neoplasia allele syndrome (MINAS) with deleterious variants in two CPGs. Summing together variant detection rates from a similarly ascertained previous MPT case series, the present results suggest that first-line comprehensive CPG analysis in a clinical genetics referral-based MPT cohort would detect a deleterious variant in about a third of cases.

  Dataset EGAD00001004088

• WES profiles from the CheckMate-274 clinical trial

  The dataset contains WES profiles of 487 patients from the CA209-274 clinical trial. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. Normalized WES libraries were pooled and sequenced on Illumina NovaSeq 6000 at a plex level appropriate to the coverage of tumor: 2 × 100 bp PE 100 M reads, germline: 2 × 100 bp PE 25 M reads.

  Dataset EGAD50000000792

• Data Quality Control

  Data Quality Control High-throughput sequencing techniques have become the leading method to study, decode and discover the genomic origins of biological phenomenons. EGA provides a secure archival of such identifiable genomics data with the purpose of data-upcycling, i.e. to re-use these data for research. High-quality data standards are essential to ensure the quality and credibility of the research. Moreover, a quality check report can assure a researcher beforehand about the data that they will request access, therefore saving time and effort. The EGA has developed a File Quality Control Report (QC Report) to provide generic quality control reports for Fastq, SAM/BAM/CRAM, and VCF files deposited at EGA. This QC Report will allow users to get information regarding the files submitted within a specific dataset. The data requesters will obtain information such as the quality of reads, mapped reads, number of variants, and other features before starting the requesting process, which will save the efforts and time.Accessing file quality control reportsIn each dataset page, the user can explore the files that it contains by clicking the "files" tab. The Quality Control report of a file has two sections. The first one, contains general information about the file, such as the inferred assembly, total reads, the dataset or study where it comes from, etc. The second section contains plots that summarise interesting information about the file, for example, the base coverage distribution, base quality or mapped reads. The description of each plot is accessible by clicking the "i" button at the top-right corner of each plot box. Technical Description For analysing the fastq, SAM/BAM/CRAM and VCF files, the EGA applies a set of tools widely used in the bioinformatics community. FASTQ: FastQC, recognised as the gold standard tool by the community.Per base sequence quality, per sequence quality scores, per base sequence content, per sequence GC content, sequence duplication levels, etc.SAM/BAM/CRAM: samtools, also the gold standard, generates results plots useful to get an overall idea of the quality of the file.base coverage distribution, base quality, % of mapped reads, % of both mates mapped, singletons, duplicates, etc.VCF: vcftools and bcftools, combined with a custom script to infer the genome assembly.site frequency distribution, Ts/Tv, base changes, indel distribution, etc.

  Documentation access/request-data/quality-control-reports

• Whole genome sequencing of neuroendocrine tumors of the small intestine

  This dataset contains whole genome sequences for 13 patients with neuroendocrine (unique/multiple) tumor(s) of the small intestine. There are in total 25 tumor and 12 matched normal genomes. Libraries were prepared using a Illumina DNA PCR Free kit following the manufacturer’s recommendations and sequencing was performed on Illumina Novaseq6000 machine with a 2x151bp paired-end fashion. It contains data for : - 1 patient with 4 tumors and 1 matched normal - 1 patient with 3 tumors and 1 matched normal - 1 patient with 2 tumors, 1 liver metastasis and 1 matched normal - 2 patients with 1 tumor, 1 mesenteric nodule and 1 matched normal - 7 patients with 1 tumor and 1 matched normal - 1 patient with 3 tumors and 1 mesenteric nodule

  Dataset EGAD50000000907

• Single-cell RNA sequencing of human IL-18R supported CAR T cells targeting oncofetal Tenascin C

  C.TNC-CAR.Zip18R CAR-T cells are from 2 donors and multiplexed 10x Genomics scRNA-seq were performed with a hashtag to label each sample. For tumor and CAR-T cell cocluture samples, CAR-T cells were extracted from 3 time points. The raw data are fastq format for total 20 samples considering sequencing lanes. The multiplexing information, CAR and Zip18R sequences are deposited in analyses.

  Study EGAS50000000772

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__BRCA_Carriers__Targeted_

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer.

  Study EGAS00001003315

• Intercellular nanotube-mediated mitochondrial transfer enhances T-cell metabolic fitness and antitumor efficacy

  We found that bone marrow-derived mesenchymal stromal cells (MSC) establish nanotubular connections with T cells in a Talin 2 (TLN2)-dependent manner and leveraged these intercellular highways to supply new mitochondria to CD8+ T cells. In this experiment we analyzed the transcriptional profile of T cells co-cultured with MSC containing MSC derived Mitochondria (MitoPositive), T cells co-cultured with MSC not containing MSC derived Mitochondria and control T cells.

  Study EGAS00001007356

• WGS and WES of 78 pairs Chinese gastric cancer

  Gastric Cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with 3 primary tumours and 2 matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC).

  Study EGAS00001001056

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__BRCA_Carriers__Exome_

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer.

  Study EGAS00001003316

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Cancer_Mastectomy__Targeted_

  Sequencing of LCM-derived microbiopsies from 30 women who mastectomies due to Breast Cancer. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations.

  Study EGAS00001003318

• Genetic regulation of RNA splicing in human pancreatic islets

  Genetic variants that influence transcriptional regulation in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D). For many susceptibility loci, however, the mechanisms are unknown. To this end, we examined splicing and gene expression QTLs (sQTLs and eQTLs) in pancreatic islets from 399 human donors from publicly available cohorts and in-house data. Here we provide newly generated RNA-seq data and genotyping array data from 101 donors.

  Study EGAS00001006440

• Characterizing Individual Cells Obtained from Bone Marrow Biopsies of MPN Patients

  We profiled the transcriptomes of individual cells obtained from bone marrow aspirates of 7 treatment-naïve newly diagnosed JAK2-mutant myeloproliferative neoplasm (MPN) patients (3 polycythemia vera and 4 essential thrombocythemia patients), and 2 healthy controls. The submitted data corresponds to sequencing reads mapped to the human reference genome GhRC38 build using CellRanger for a total of 9 samples (one per patient). In addition, to reconstruct the lineage histories of single cells in MPN patients, we performed whole-genome sequencing of single-cell-derived colonies of hematopoietic stem and progenitor cells from 2 essential thrombocythemia (ET) patients: 22 JAK2-mutant colonies and 20 WT colonies for patient ET 1; and 13 JAK2-mutant colonies and 21 WT colonies for patient ET 2. The submitted data consists of sequencing reads aligned to the human reference genome GhRC38 build using bwa-mem. Each file corresponds to the whole-genome sequencing data for one colony.

  Study phs002308

• EGA file encryption types

  EGA file encryption The European Genome-Phenome Archive (EGA) stands as a significant initiative in the field of genomics, facilitating the secure storage and sharing of vast amounts of genomic data. Jointly hosted by the Centre for Genomic Regulation (CRG) and the European Bioinformatics Institute (EMBL-EBI), the EGA offers a robust infrastructure for managing encrypted data, ensuring the privacy and integrity of sensitive genomic information. Both CRG and EMBL-EBI play pivotal roles in the EGA, each institution bringing unique expertise in managing different types of encryptions. EMBL-EBI EGACryptor encryption system, while CRG utilises Crypt4GH, resulting in two distinct encryption file types: cip and c4gh, respectively. How can I check the file encryption? To access your dataset of interest on the European Genome-Phenome Archive (EGA) and determine the corresponding encryption file extension, please follow these step-by-step instructions: Utilise the search or navigation features provided on the EGA website to locate the dataset you are interested in. Once you find the dataset webpage, click on the "Files" tab, typically located on the dataset's webpage. Upon reaching the "Files" tab, you will be presented with a table containing comprehensive information about the files associated with the dataset. This table will include various columns, such as "File Name," "Size," and "Location." The "Location" column is particularly relevant for determining the encryption file extension. Figure 1: File table showing all the information available for the files in a dataset. This table is specific for each dataset. To identify the encryption file extension corresponding to a specific file, locate the "Location" column in the table. If the file is archived in Spain, the file will have the .c4gh extension, indicating that it is encrypted using Crypt4gh. Conversely, if the file is archived in the UK, the encrypted file extension will be .cip, indicating the usage of EGACryptor for encryption. It is worth noting that a file can be available in both locations, meaning it will be accessible with both file extensions (.c4gh and .cip). This allows users to choose the encryption method that aligns with their preferred platform or analysis tools.

  Documentation check-encryption-type

• Environmental Arsenic and Diabetes Mellitus (Chihuahua Cohort)

  The Chihuahua Cohort was established as part of a larger NIEHS-funded project that used laboratory models (tissue culture and mice) and human subjects to examine the association between exposure to arsenic and diabetes, including identification of mechanisms underlying this association. All procedures involving human subjects were approved by institutional review boards at the University of North Carolina at Chapel Hill and Cinvestav-IPN (Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico City, Mexico). All participants provided signed informed consent. A total of 1,160 adults (≥ 18 years old) with a minimum 5-year uninterrupted residency in the Chihuahua study area were recruited between 2008 and 2012. Samples of drinking water were obtained from the participants' households. Data on residency, occupation, drinking-water sources and use, smoking, alcohol consumption, and medical history were recorded by a study questionnaire. Spot urine and fasting venous blood were collected during medical examination that included an oral glucose tolerance test (OGTT) with blood drawn 2 hr after a 75-g glucose dose. Plasma from both fasting and 2-hr blood samples was collected. Body mass index (BMI) of each participant was calculated from body weight and height. BMI cutoffs of ≥ 25.0, ≥ 30, and < 18.5 kg/m2 were used to define overweight, obese, and underweight individuals, respectively. Participants' waist circumference was also measured. Blood pressure was assessed using a manual sphygmomanometer. Three measurements were taken at intervals of at least 1 min, with a 5-min rest before obtaining the first reading; the mean of the last two measurements was used. The concentrations of arsenic in drinking water and arsenic species in urine were measured by hydride generation-atomic absorption spectrometry. The limit of detection for As in water as well as for As species in urine was 0.01 µg As/L. Creatinine concentration in urine was determined using an established colorimetric assay. DNA was isolated from blood for genotyping analysis.The following measures were taken: glucose concentration in fasting blood (FBG) and in blood collected 2 hours into OGTT (2HBG); concentrations of triglycerides, HDL and total cholesterol (TC) in fasting plasma; and LDL was calculated using the Friedewald equation. Diabetes was classified by FPG ≥ 126 mg/dL, 2HPG ≥ 200 mg/dL, or self-reported diabetes diagnosis or medication use (WHO/International Diabetes Federation 2006). Prediabetes was defined as the absence of diabetes with FPG ≥ 110 mg/ dL or 2HPG ≥ 140 mg/dL. Elevated fasting levels of each lipid were defined as plasma TG ≥ 150 mg/dL, TC ≥ 200 mg/dL, and LDL ≥ 130 mg/dL. Fasting HDL < 40 mg/dL in men and < 50 mg/dL in women were designated as low. Hypertension was defined by systolic blood pressure (SBP) > 140 mm Hg, diastolic blood pressure (DBP) > 90 mmHg, or self-reported use of anti-hypertensive medication. Genotyping analysis, which will be available in version 2 of this study, was carried out in a subset of ~600 subjects with focus on enzymes involved in the metabolism of arsenic, including AS3MT, GSTs.All data collected during the medical exams or generated by the above-described chemical and biochemical analysis of water, urine and blood/plasma, as well as results of the genotyping analysis are included in dbGaP. Data generated by metabolomics and epigenetic analyses in small subsets of the Chihuahua cohort are not included, but are available in published articles.

  Study phs002139

• Epigenetic and metabolomic data from type 2 diabetes adolescents

  Objective: Rates of type 2 diabetes (T2D) among adolescents are on the rise. Epigenetic changes could be associated with the metabolic alterations in adolescents with T2D. Methods: We performed a cross-sectional integrated analysis of DNA methylation data from peripheral blood mononuclear cells with serum metabolomic data from First Nation adolescents with T2D and controls participating in the Improving Renal Complications in Adolescents with type 2 diabetes through REsearch (iCARE) cohort study, to explore the molecular changes in adolescents with T2D. Results: Our analysis showed that 43 serum metabolites and 36 differentially methylated regions (DMR) were associated with T2D. Several DMRs were located near the transcriptional start site of genes with established roles in metabolic disease and associated with altered serum metabolites (e.g. glucose, leucine, and gamma-glutamylisoleucine). These included the free fatty acid receptor-1 (FFAR1), upstream transcription factor-2 (USF2), and tumor necrosis factor-related protein-9 (C1QTNF9), among others. Conclusions: We identified DMRs and metabolites that merit further investigation to determine their significance in controlling gene expression and metabolism which could define T2D risk in adolescents.

  Study EGAS00001003816

• University of Zurich (UZH) - Snedeker lab

  Authorised Personnel: The individuals at the User Institution to whom University of Zurich (UZH) grants access to the Data. This includes the User, the individuals listed in Appendix II and any other individuals for whom the User Institution subsequently requests access to the Data. Details of the initial Authorised Personnel are set out in Appendix II. Data: The managed access datasets to which the User Institution has requested access. Data Producers: UZH and the collaborators listed in Appendix I responsible for the development, organisation, and oversight of these Data. External Collaborator: A collaborator of the User, working for an institution other than the User Institution. Project: The project for which the User Institution has requested access to these Data. A description of the Project is set out in Appendix II. Publications: Includes, without limitation, articles published in print journals, electronic journals, reviews, books, posters and other written and verbal presentations of research. Research Participant: An individual whose data form part of these Data. Research Purposes: Shall mean research that is seeking to advance the understanding of genetics and genomics, including the treatment of disorders, and work on statistical methods that may be applied to such research. User: The principal investigator for the Project. User Institution(s): The Institution that has requested access to the Data. UZH: University of Zurich, Raemistrasse 71, 8001 Zurich, Switzerland

  Dac EGAC50000000817