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• Identifying causative mutations for Thrombocytopenia with Absent Radii

  Thrombocytopenia with Absent Radii is an inherited disorder that manifests itself with major limb skeletal abnormalities and low platelet count (and therefore a bleeding diathesis). The syndrome is well-characterised and defined phenotypically and there is a well-established database of UK-based families affected with ths disorder. The causative mutation for the disorder is yet to be identified. If known, it would allow for pre-natal screening and counselling avoiding life-long care for patients who are affected and are therefore severely disabled. We postulate that exon sequencing of 4 unrelated affected individuals would give enough power to narrow down potential candidate mutations which would thereafter be confirmed using DNA from other affected families.

  Study EGAS00001000054

• A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy

  The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and non-canonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in-silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens and high-confidence tumor-specific antigens.

  Study EGAS50000000228

• Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia - Acute myeloid leukemia

  The advent of high-throughput next generation sequencing (NGS) technologies that are revolutionizing genomics and transcriptomics by providing a single base resolution tool for a unified deep analysis of diseases complexity allows a fast and cost-efficient fine-scale assessment of the genetic variability hidden within cohorts of patients affected by the same leukemia. That being so, by potentially highlighting inter-individual differences that may play a role in the differential success of diverse therapeutic interventions, they promise to be crucial for selecting the most appropriate medical treatments. The project aims at the identification of novel prognostic biomarkers for acute myeloid leukemia (AML) and studied the molecular differences between aneuploid and euploid AML.

  Study EGAS00001005464

• A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

  Study EGAS00001008051

• Star2xml: metadata converter into XML

  Star2xml: metadata converter into XML Welcome to the landing page for star2xml - a tool developed by the European Genome-phenome Archive (EGA) that enables users to convert metadata into XML format that is compliant with EGA's programmatic submission system. For starters, if you are not sure what metadata is in this context, you may want to explore our brief metadata introduction. . Star2xml is useful for users who have already submitted their data to the EGA and want to also submit their metadata programmatically without having to create the XML files manually. The need for these XMLs containing metadata is explained in the EGA's metadata schemas and programmatic submission guidelines. In summary, star2xml allows for users to deposit metadata in a tabular format (e.g. excel spreadsheet) and transform it into a compliant XML format. This saves time in large submissions, where the sheer size of metadata makes it difficult to manage. For smaller submissions, it is recommended to use EGA's Submitter Portal (SP) instead. The installation of the tool is straightforward, and it contains detailed documentation on how to use it in its GitHub repository . While star2xml can help users convert metadata formats, it does not validate the resulting metadata against EGA's schemas. Therefore, after creating your XMLs, you should still validate your metadata before submitting it to EGA, as described in the documentation for programmatic metadata validation.

  Documentation tools/star2xml

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• National Cancer Institute (NCI) Prostate Cancer Genome-Wide Association Study for Uncommon Susceptibility Loci (PEGASUS)

  This genome-wide association study was funded by the National Cancer Institute (NCI) to identify uncommon susceptibility loci for prostate cancer. A total of 4,600 prostate cancer cases and 2,840 controls of European ancestry from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were genotyped using the Illumina HumanOmni2.5 and passed rigorous quality control filters. Additional genotype data (available in dbGap under other accession numbers) from 101 independent controls of European ancestry scanned with the HumanOmni2.5 were also included, resulting in a total of 4,600 cases and 2,941 controls for the published analysis. SNPs from the most promising regions, as determined by rank p-value, under multiple different models as well as select candidate genes were taken forward for replication using a custom Iselect chip in 6,575 cases and 6,392 controls of European ancestry. Results from the primary scan after imputation were then meta-analyzed with the Iselect results as well as results from previous GWAS. In a combined meta-analysis of the primary scan together with the custom Iselect replication and a previous GWAS, thirteen loci reached genome-wide significance (P < 5 x 10-8) for prostate cancer overall; however, each of them confirmed a previously reported locus. Although they did not reach genome-wide significance, we found evidence for two new suggestive loci at chromosome 16q22.2 (PKD1L3, rs12597458, P = 9.67 x 10-8) and 6p22.3 (CDKAL1, rs12198220, P = 2.13 x 10-7). In a combined case-only analysis of 12,518 prostate cancer cases, we identified two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49x10-9) and rs78943174 at 3q26.31 (NAALADL2, P=4.18x10-8). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85x10-5) with no association for non-aggressive prostate cancer compared to controls (P=0.57). Only the cases and controls genotyped on the HumanOmni2.5 specifically for this study are included under this accession number. Controls (n=101) genotyped with the HumanOmni2.5 for another study are posted under a different accession number. Please note that the majority of prostate cancer cases and controls genotyped in CGEMS (and posted under a different accession number) are included in this study.

  Study phs000882

• Genetic Components of Knee Osteoarthritis (GeCKO) Study: The Osteoarthritis Initiative

  The Osteoarthritis Initiative (OAI) is a publicly and privately funded prospective longitudinal cohort with a primary objective of identifying risk factors for incidence and progression of tibiofemoral knee OA. The OAI utilized a focused population-based recruitment to enroll 4,674 men and women between the ages of 45-79 years who either had radiographic symptomatic knee OA or who were without radiographic symptomatic OA in both knees but were considered high risk for OA because they had two or more known risk factors for knee OA. Subjects were recruited into the baseline phase of the OAI at multiple sites throughout the US between 2004 and 2006. All subjects were invited back for follow-up examinations to assess incidence or progression of OA annually, for up to 5 years. Phenotype data from the baseline and follow-up examinations are available for public access from the Osteoarthritis Initiative (OAI) database at http://www.oai.ucsf.edu/. The Genetic Components of Knee Osteoarthritis (GeCKO) Study was initiated in 2009 as a genetic ancillary study to perform a genome-wide association study to identify genetic variants associated with radiographic osteoarthritis. This study included 4,482 individuals participating in the parent OAI study. Following sample cleaning (e.g., removal of duplicates, sex mismatches, poor sample quality, etc.), the final sample set included 4,129 individuals.

  Study phs000955

• Symptom Clusters in Oncology Patients Receiving Chemotherapy

  The parent longitudinal study evaluated the symptom experience of oncology outpatients receiving chemotherapy. Patients completed questionnaires in their homes a total of six times (assessments 1 through 6). The questionnaires were timed to evaluate symptoms associated with the receipt of two cycles of chemotherapy that were administered approximately a month apart. Assessments 1 and 4 evaluated symptoms prior to the receipt of chemotherapy. Assessments 2 and 5 evaluated symptoms in the week following the administration of chemotherapy. Assessments 3 and 6 evaluated symptoms two weeks following the administration of chemotherapy. For this analysis, morning and evening fatigue data from the enrollment assessment (i.e., prior to the second or third cycle of chemotherapy) and the assessment that was done approximately 1 week after administration of chemotherapy were evaluated. Patients completed the Lee Fatigue Scale to obtain information on morning and evening fatigue severity. For the morning fatigue assessment, patients were asked to describe how they “felt over the past week when they woke up in the morning”. For the evening fatigue assessment, they were asked to describe how they felt over the past week “before they went to bed at night”. Medical records were reviewed for disease and treatment information. Epigenome assays (microarray) were completed for 1170 patients. Whole transcriptome sequencing (bulk RNA-Seq) was completed for 651 patients.

  Study phs003863

• Targeted de-methylation of the FOXP3-TSDR

  CD4+ regulatory T cells (Tregs) are key mediators of immunological tolerance and promising effector cells for immuno-suppressive adoptive cellular therapy to fight autoimmunity and chronic inflammation. Their functional stability is critical for their clinical utility and has been correlated to the demethylated state of the TSDR/CNS2 enhancer element in the Treg lineage transcription factor FOXP3. However, proof for a causal contribution of the TSDR de-methylation to FOXP3 stability and Treg induction is so far lacking. We here established a powerful transient-transfection CRISPR-Cas9-based epigenetic-editing method for the selective de-methylation of the TSDR within the endogenous chromatin environment of a living cell. The induced de-methylated state was stable over weeks in clonal T cell proliferation cultures even after expression of the editing complex had ceased. Epigenetic editing of the TSDR resulted in FOXP3 expression, even in its physiological isoform distribution, proving a causal role for the de-methylated TSDR in FOXP3 regulation. However, successful FOXP3 induction was not associated with a switch towards a functional Treg phenotype, in contrast to what has been reported from FOXP3 overexpression approaches. Thus, TSDR de-methylation is required, but not sufficient for a stable Treg phenotype induction. Therefore, targeted demethylation of the TSDR may be a critical addition to published in vitro Treg induction protocols which so far lack FOXP3 stability.

  Study EGAS00001004867

• Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

  The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

  Study phs001801

• Susceptibility loci for tanning ability in Japanese population identified by genome-wide association study

  We performed genome-wide association studies of Japanese Skin Type for Japanese individuals from a cohort study by the Tohoku Medical Megabank Project in order to identify variants related to tanning ability and skin pigmentation. We used imputed genotype data of 9,187 Japanese individuals, of which 4,475 individuals are from Miyagi prefecture and 4,712 individuals are from Iwate prefecture. Skin Type information was obtained from the questionnaire for cohort participants.

  Study JGAS000160

• Mutational landscape of the transcriptome offers putative targets for immunotherapy of myeloproliferative neoplasms

  In this study, we aimed to comprehensively characterize in 113 myeloproliferative neoplasms (MPN) patients the mutational landscape of the granulocyte transcriptome using RNA sequencing data. We implemented workflows for fusion and variant calling, and differential splicing analysis for patients with hotspot SF3B1 mutations. Finally, we characterized the neoantigen landscape on individualized level taking each patient's HLA genotype (derived from the same RNA-seq dataset) into account.

  Study EGAS00001003486

• Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment

  Samples was collected at the Mayo Clinic. MM tumor samples were enriched using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). DNA from CD138+ MM cell (tumor) or peripheral blood samples (germline control) at Mayo Clinic (Rochester or Arizona) underwent WGS. For samples collected at Mayo Clinic Rochester, library preparation was completed using the NEB Ultra II (New England Biolabs, Ipswich, MA) and the Nextera Flex systems (Illumina, San Diego, CA) and sequenced at the Mayo Clinic Genome Analysis Core with an approximate depth of 30X for tumor samples and 60X for the germline control. For samples collected at Mayo Clinic Arizona, Novogene was used for WGS following random shearing of the DNA, end-repairs, A-tailed and ligated with Illumina adapters. Sequencing was performed on the Illumina Novaseq 6000 sequencer Reference Genome: GRCh38.

  Dataset EGAD50000002132

• Whole exome sequencing for clarification of rare causes of axonal Charcot-Marie-Tooth disease (2017-08-16)

  The project is focused on the axonal forms of Charcot-Marie-Tooth (CMT) disease. We have selected 13 families (7 from Spain and 6 from Czech Republic) that have been indepth clinically assessed and previously tested for mutations in known CMT genes without causal variants characterised. In these patients we expect to discover several CMT2 genes. Thus, we requested for exome sequencing of 45 DNAs:27 exomes in families from Spain and 18 exomes in the families from Czech Republic. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ This dataset contains all the data available for this study on 2017-08-16.

  Dataset EGAD00001003565

• Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals

  Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals. Additional associated phenotype information is available for all individuals included in this study directly from CIBMTR. Data are available under controlled access release upon reasonable request and execution of a data use agreement. Requests should be submitted to CIBMTR at info-request@mcw.edu and include the study reference IB17-04.

  Study EGAS00001006033

• Saliba Lab Data Access Committee

  DAC for data generated by Saliba Lab at Helmholtz institute for RNA-based Infection Research, Würzburg, Germany

  Dac EGAC50000000152

• Screening for abnormal CGI methylation in primary colorectal tumours

  Screening for abnormal CGI methylation in primary colorectal tumours

  Dataset EGAD00001000213

• RNA-Seq data for Juvenile Pilocytic Astrocytomas

  RNA-Seq data for 9 JPA samples.

  Dataset EGAD00001009043

• Whole exome sequencing of ATCWGS42 primary tumour and PDX

  Genomic DNA was isolated from snap-frozen tissue and subjected to whole genome sequencing at The Center for Applied Genomics (Hospital for Sick Children, Toronto, ON) or at Beijing Genomic Institute (BGI). High-coverage whole exome-sequencing was performed at GeneSeeq Inc. (Toronto, Ontario, Canada) using IDT xGen exome panel.

  Study EGAS50000001490

• Whole exome sequencing of Parkinson's disease patients from the United Kingdom

  As part of the International Parkinson's Disease Genomics Consortium, exomes of Parkinson's disease (PD) patients and healthy controls were sequenced to study the genetic etiology of PD. This UK cohort consists of 70 PD patients. Researchers can apply for access to fastq, vcf and binary plink files for this cohort.

  Study EGAS00001002156

• RNA Sequencing of AD OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from individuals diagnosed with Alzheimer's disease exposed to traffic-related ultrafine particles (UFPs) for 24-h and 72-h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Study EGAS50000000448

• Bulk 3' mRNA-Seq of dome and suspension tubuloids

  Bulk 3' mRNA-sequencing of human kidney tubuloids grown in dome and suspension culture for the identification of transcriptional differences associated with culture method, passage, and donor. Tubuloids were generated from 4 separate donors and collected for sequencing at day 7 of passage 3, 4, and 5 in dome and suspension culture.

  Study EGAS50000001629

• Validation_of_AML_Mutational_Screening

  We recently worked-up a pulldown protocol for studying 21 genes recurrently mutated in AML (Study1770). Our manuscript is currently under revision and to address the reviewers' comments we need to validate some mutations by re-sequencing. In this add-on study we will be using PCR followed by MiSeq for this purpose.

  Study EGAS00001000430

• Single cell RNA sequencing of CD19 CAR T-cell infusion products

  We performed single cell RNA sequencing of remnants from CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma. Libraries were prepared using 10X 5’ GEX chemistry and sequenced on an Illumina HiSeq 4000 to obtain >50,000 reads per cell.

  Study EGAS00001004576

• WES for 45 patients with pleural mesothelioma (Matched)

  The dataset contains WES data (bam files) for 45 pleural mesothelioma samples. Nextera Flex for Enrichment solution (Illumina, San Diego, CA) in combination with SureSelect Human All Exon V7 probes (Agilent, Santa Clara, CA) was used for library preparation and generated libraries were sequenced on NovaSeq 6000 (Illumina, San Diego, CA) in 150 pair-end mode. Quality control of the raw data was conducted using fastQC (v. 0.11.8) (https://www.bioinformatics. babraham.ac.uk/projects/fastqc/). WES data were then analyzed with the DRAGEN Bio IT platform 49 (version 4.2.4) and the human GRCh38 as reference genome.

  Dataset EGAD50000002128

• WES for 42 patients with pleural mesothelioma (Not matched)

  The dataset contains WES data (bam files) for 42 pleural mesothelioma samples. Nextera Flex for Enrichment solution (Illumina, San Diego, CA) in combination with SureSelect Human All Exon V7 probes (Agilent, Santa Clara, CA) was used for library preparation and generated libraries were sequenced on NovaSeq 6000 (Illumina, San Diego, CA) in 150 pair-end mode. Quality control of the raw data was conducted using fastQC (v. 0.11.8) (https://www.bioinformatics. babraham.ac.uk/projects/fastqc/). WES data were then analyzed with the DRAGEN Bio IT platform 49 (version 4.2.4) and the human GRCh38 as reference genome.

  Dataset EGAD50000002127

• Comprehensive molecular phenotyping of ARID1A-deficient gastric cancer reveals pervasive epigenomic reprogramming and therapeutic opportunities

  This dataset includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset.

  Dataset EGAD50000000660

• BELLINI clinical trial single-cell RNA-Seq and TCR data: cohorts A & B

  Single-cell RNA-Seq data and TCR sequencing data (both by 10X Genomics) of 51 TNBC primary tumors obtained from 29 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (16 patients, 28 samples) received nivolumab for 4 weeks, patients in cohort B (13 patients, 23 samples) received nivolumab + ipilimumab for 4 weeks. The included sequencing data was generated from frozen material for cohort A and from fresh material for cohort B.

  Dataset EGAD50000000807

• Dataset for whole exome sequencing of 49 tumor-blood pairs and transcriptome sequencing of 44 tumors for adrenocortical tumors

  Dataset for whole exome sequencing of 49 tumor-blood pairs and transcriptome sequencing of 44 tumors for adrenocortical tumors

  Dataset EGAD00001000810

• ChIP-seq and 4C-seq datasets in megakaryocytes and granulocytes from individuals with QPD and unaffected controls

  ChIP-seq was performed for the following histone modifications in both megakaryocytes and granulocytes: H3K27ac, H3K4me2, and H3K36me3. ChIP-seq was performed for H3K27me3 and CTCF in megakaryocytes only. All ChIP experiments consist of n=3 replicates for each of QPD and Control, with the exception of control granulocyte H3K4me2 for which only n=2 replicates were performed. 4C-seq datasets consist of 2 viewpoints (PLAU promoter and an intergenic enhancer), profiled in megakaryocytes from n=2 controls and n=4 QPD.

  Dataset EGAD00001006048

• Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset EGAD00001015373

• SGCC GASCAD-II dataset

  The GASCAD-II dataset from the Singapore Gastric Cancer Consortium includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset

  Dataset EGAD00001015433

• Genotyping NIGMS Chromosomal Aberration and Inherited Disorder Samples

  As part of an effort to correlate molecular copy number variation determinations with state of the art karyotype analyses, 716 samples derived from 697 individuals from the Chromosomal Aberrations and Inherited Disorders collections of the NIGMS Human Genetic Cell Repository were genotyped and analyzed for CNV determination by the Microarray Center at the Coriell Institute for Medical Research. Karyotyping is performed on all cell cultures in the Repository with reported chromosome abnormalities. The samples chosen for genotyping in this study are intended to represent a diverse set of copy number variants, but the selection was also weighted to over-sample commonly manifested types of aberrations. When available, the ISCN description of the sample based on G-banding and FISH analysis is included in the phenotypic data. Karyotypes for these cells can be viewed in the online Repository catalog (http://ccr.coriell.org/Sections/Collections/NIGMS/?SsId=8).

  Study phs000269

• Validation of Gene Array to Predict Bacterial Co-infection In Adults Hospitalized with Viral Lower Respiratory Tract Infections (LRTI)

  Accurate tests for microbiologic diagnosis of lower respiratory tract infections (LRTI) are needed. Gene expression profiling of whole blood represents a powerful new approach for analysis of the host response during respiratory infection that can be used to supplement pathogen detection testing. Using qPCR, we prospectively validated the differential expression of 10 genes previously shown to discriminate bacterial and non-bacterial LRTI confirming the utility of this approach. In addition, a novel approach using RNAseq analysis identified 141 genes differentially expressed in LRTI subjects with bacterial infection. Using "pathway-informed" dimension reduction, we identified a novel 11 gene set (selected from lymphocyte, α-linoleic acid metabolism, and IGF regulation pathways) and demonstrated a predictive accuracy for bacterial LRTI (nested CV-AUC=0.87). RNAseq represents a new and an unbiased tool to evaluate host gene expression for the diagnosis of LRTI.

  Study phs001248

• The CHOP Pediatric Genetic Sequencing (PediSeq) Project : Applying Genomic Sequencing in Pediatrics

  The purpose of this research study is to learn more about newer types of genetic testing called whole exome sequencing and whole genome sequencing. Current genetic testing usually examines one gene or a few genes at a time. Exome and genome sequencing allow us to test most of a person's genes at one time with a single test. This testing might identify the reason for a person's unexplained condition or diagnosis. We hope this study will help us identify the best methods for: Educating patients and families about exome and genome sequencing Analyzing exome and genome sequencing data to identify results relevant to patients Giving results to families in a clear, appropriate, and informative manner The current data only includes WES for 159 samples. The WGS samples for 20 samples will be uploaded in the near future.

  Study phs000935

• PLCO - Limited Use Pilot Test Data

  This is a sample of Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial data for limited use in a pilot test for remote data access. The PLCO is a randomized, controlled trial of screening tests for prostate, lung, colorectal and ovarian cancers. Approximately 155,000 participants were enrolled between November 1993 and July 2001. Participants were individually randomized to the control arm or intervention arm in equal proportions. Participants assigned to the control arm received usual care, whereas participants assigned to the intervention arm were invited to receive screening exams for prostate, lung, colorectal and ovarian cancers as outlined in the study protocol. The goal of the study was to assess whether these screening exams reduce mortality from prostate, lung, colorectal and ovarian cancers. Data were collected on cancer diagnoses and deaths from all causes that occurred through December 31, 2009. Median follow-up time was 12.4 years.

  Study phs002011

• The Genetic Evolution of Acral Melanoma

  Acral melanoma is a rare melanoma subtype arising on the sole, palm, or nail apparatus. We performed whole-exome sequencing (WES) for a cohort of 35 acral melanoma patients. For each patient, we sequenced multiple tumor areas representing different tumor stages, including the in situ and invasive portions of the primary tumor and available regional or distant metastases. Normal areas were included for all except one patient. We identified distinct evolutional trajectory compared to melanomas arising on the sun-exposed skin. Whole-genome sequencing and targeted sequencing were additionally performed for a subset of the samples. Particularly, in acral melanomas, complex genomic aberrations, characterized by clustered copy number transitions and focal amplifications, and telomerase reverse transcriptase (TERT) activating alterations occur very early during evolution, while MAP-kinase pathway mutations, such as BRAF V600E and NRAS hotspot mutations, can occur late and often result in striking intra-tumor heterogeneity.

  Study phs003451

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program - Neuroblastoma

  The goal of NCI's Pediatric In Vivo Testing Consortium (PIVOT) is to advance the development of effective treatments for pediatric cancers through preclinical in vivo testing of novel therapeutic agents. To design impactful experiments that can be rapidly translated to the clinic, PIVOT investigators require comprehensive genomic characterization of the patient-derived xenograft (PDX) models used across the consortium. This robust experimental design enhances collaboration with industry partners by providing proof-of-concept data for drugs in development. As part of this effort, neuroblastoma PDX models are being molecularly characterized to identify promising therapeutic candidates. The molecular profiling includes whole exome sequencing (WES), RNA-seq, MethylEPIC array, CytoSNP array, and DNA fingerprinting for quality control. Additionally, demographic and clinical data (e.g., diagnosis, disease site, disease status) are shared. These characterized PDX models, matched with patient tumors, guide model selection for preclinical drug testing.

  Study phs003163

• APOL1 Risk Variants Induce Metabolic Reprogramming of Podocytes in Patient-Derived Kidney Organoids

  Apolipoprotein L1 (APOL1) high-risk genotypes G1 and G2 are responsible for the increased risk of chronic kidney disease (CKD) in the African-American population, especially in the presence of interferon gamma (IFN-γ). Here, we applied single cell transcriptomics on kidney organoids generated from patient-derived induced pluripotent stem cells (iPSCs) to model human APOL1 nephropathy. iPSCs were generated from fibroblasts of two patients with APOL1 nephropathy homozygous for G1 or G2 risk variants, and an isogenic control (G0) was created by gene correction. Kidney organoids were generated according to previously published protocol (Takasato M et al. Nat. Protoc. 2016) and treated with IFN-γ for two days to induce APOL1. Twenty-four hours after IFN-γ removal, treated organoids from all three lines that were cultured in parallel were harvested for single cell transcriptomics.

  Study EGAS50000001223

• Measuring the level of relatedness between NGS datasets

  Sequencing technologies are providing increasingly detailed insight in genetic makeup are paving their way into molecular diagnostics. The field will benefit from rigorous and bias-free measures for the quality of sequence data and for the proper representation of the complexity of the original samples. While current methodologies rely on the availability of a well-characterized reference genome, we propose kMer profiling for alignment-free assessment of the quality, comparability, and complexity of sequencing datasets. We show that kMer detects technical artefacts such as high duplication rates, library chimaeras, and differences in library preparation protocols in whole-genome, whole-exome, and RNA sequencing data. Additionally, it successfully captures the complexity and diversity of microbiomes. Thus, kMer allows for a robust evaluation of the quality and complexity of sequencing data without relying on any prior information and opens the way to a more reliable biological reasoning.

  Study EGAS00001000600

• Exploring Extracellular Vesicle microRNAs in Usher Syndrome Type 1B: Tear-Derived EVs as Indicators of Retinal Health

  The goal of this study was to explore extracellular vesicles (EVs) from human tears and iPSC-derived RPE cells as biomarkers for Usher syndrome type 1B (USH1B), a rare inherited disorder causing deafness and retinitis pigmentosa. Researchers found that tear EVs showed higher levels and diversity of miRNAs, making them a promising non-invasive source for diagnosing USH1B. In contrast to patient-derived RPE cells, which did not express MYO7A protein despite similar expression levels in controls, the study identified specific microRNA signatures associated with retinal degeneration in both tear EVs and RPE-derived EVs. The findings suggest that tear EVs can serve as a useful biomarker for USH1B diagnosis, monitoring, and therapeutic development. Overall, this research aims to contribute to our understanding of disease mechanisms and identify potential targets for treatment in patients with Usher syndrome type 1B.

  Study EGAS50000001200

• Determining genome-wide binding of ETS2 by CUT&RUN in primary human macrophages

  This dataset consists of sequencing data from an ETS2 CUT&RUN experiment in primary inflammatory (TPP) macrophages (n = 2). Pre-cultured TPP macrophages were harvested and processed immediately using the CUT&RUN Assay kit (Cell Signaling) according to the manufacturer’s instructions with the following modifications (essentially, avoiding the use of ConA-coated beads). Anti-ETS2 (ThermoFisher) or IgG control (Cell Signaling) antibodies were used for targeted digestion of chromatin. For each donor, 5x10^5 cells were pelleted, washed in Wash Buffer, and resuspended in Antibody Binding buffer. Cells were incubated with antibodies (1:100 dilution for anti-ETS2) for 2h at 4°C. After washing in Digitonin Buffer, cells were incubated with pA/G-MNase for 1h at 4°C. Cells were washed twice in Digitonin Buffer, resuspended in the same buffer and cooled for 5 minutes on ice. Calcium chloride was added to activate pA/G-MNase digestion and cells were incubated for 30 minutes at 4°C before Stop Buffer was added, and cells were incubated for 10 min at 37°C to release cleaved chromatin fragments. Supernatants were collected by centrifugation and DNA extracted using DNA Purification Buffers and Spin Columns (Cell Signaling). Library preparation was performed according to a protocols.IO protocol (dx.doi.org/10.17504/protocols.io.bagaibse) using the NEBNext Ultra II DNA Library Prep Kit. Size selection was performed using AMPure XP beads (Beckman Coulter) and fragment sizes were determined using an Agilent 2100 Bioanalyzer (High Sensitivity DNA kit). Equimolar pools of indexed libraries were sequenced on an Illumina NovaSeq 6000 (100bp PE reads). Raw data are provided as 100 bp paired-end Illumina reads.

  Dataset EGAD00001011349

• Asian Genome Project(BioBank Japan genotype data)

  Biobank Japan registrants sequenced for Asian Genome Project

  Study JGAS000647

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• Heart

  Whole-Exome-Sequencing of 5 pooled patients for SNP-based demultiplexing

  Study EGAS50000000655

• Identifying causative mutations for Thrombocytopenia with Absent Radii

  Identifying causative mutations for Thrombocytopenia with Absent Radii

  Dataset EGAD00001000018

• snv calls for subclonal reconstruction

  single nucleotide variant calls from somatic sniper, vcf format. input for subclonal reconstruction

  Dataset EGAD00001003753

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000695

• DATA FILES FOR SJEPD

  DATA FILES FOR SJEPD

  Dataset EGAD00001000854

• Oxford Nanopore sequencing for APL

  Raw fast5 file of Oxford Nanopore sequencing for an APL patient sample

  Dataset EGAD00001008151

• Novel genes for Intellectual Disability identified using whole genome sequence and pathway analysis

  Intellectual Disability (ID) is one of the most common global disorders. However for ~30% of patients with ID no cause is identified, despite a clinical diagnostic odyssey that includes genome wide clinical microarray (CMA). We carefully selected 8 trios, each composed of a child with ID and brain structural defect, and both normal parents for whole genome sequencing (WGS). We conducted WGS on the trio and filtered out de novo single nucleotide variants (SNVs) and then used a pathway-based refinement to select candidates. We confirmed a de novo pathogenic SNV in ARID1B, and likely pathogenic SNVs in CACNB3, SPRY4, PHF6, SQSTM1 and UPF1 in 5 of the 8 children. All genes except ARID1B and PHF6 are previously unreported for ID. We analysed our WGS data using 4 independent algorthims for copy number and structural variation including using de novo whole genome assembly. We confirmed one likely contributory 165kb de novo CNV (missed by CMA). We conducted a validation study of over 2000 exomes for our novel candidate genes and also present a strategy to analyze the non-coding sequence space. This study provides an extensive analysis of WGS in the context of ID and yielded causative variants in >60% of cases.

  Study EGAS00001001386

• Mucociliary Clearance Consortium (MCC) Longitudinal Study of Primary Ciliary Dyskinesia: Participants 5-18 Years of Age

  The purpose of this longitudinal study protocol is to define age-related prevalence of phenotypic characteristics and the progression of key features of lung disease in participants with one of these disorders, Primary Ciliary Dyskinesia (PCD). In PCD, the abnormal structure and function of cilia results in impaired clearance of secretions and consequent obstruction and chronic recurrent infection in the airways, sinuses and middle ears. Although it seems likely that the onset of PCD airway disease occurs early in childhood, as has been reported for cystic fibrosis (CF), the clinical course of PCD lung disease is not well defined, nor, is the time course of emergence of specific microbial pathogens, or the age of onset and rate of progression of airway disease and bronchiectasis. This longitudinal study is designed to define the rate of progression of PCD lung function in participants between 5-18 years of age using spirometry which tracks well with lung impairment and prognosis in other disorders of the airways such as cystic fibrosis. This longitudinal protocol will also systematically track other specific outcomes, including pathogens infecting the airways (assessed by respiratory cultures), and age at onset and progression of airway damage and bronchiectasis (assessed by high-resolution computerized tomography, HRCT, of the chest). Blood will be collected for DNA to test for genetic mutations. The blood samples will be processed to establish a cell line (lymphocyte transformation) for a source of DNA for future genetic studies, in participants with disease. For participants unable to provide a blood sample, a buccal sample will be obtained for DNA.

  Study phs000596

• Epigenetic Profiling of Human Colorectal Cancer

  DNA methylation, together with chromatin modifications, constitute the epigenome that functions to regulate gene expression and genome integrity. DNA methylation alterations are ubiquitous in human cancers, as many genes acquire DNA methylation in a cancer-specific manner. DNA methylation at these sites in the genome of cancer cells not only serves as a marker for tumor identification, but together with gene mutation and gene expression data, can also be used to describe subsets of tumors of the same organ source. We have previously shown distinct human colorectal cancer subtypes based on DNA methylation differences. Correlating these DNA methylation differences with clinical co-variates will serve to further understand how these distinct subtypes are generated. We have collected 100 colorectal tumor tissues (for which clinical information is known) and have obtained (unprotected) genome-wide DNA methylation and chromatin modification information for each sample for the purposes of identifying and classifying unique tumor subtypes of colorectal cancers. In addition, we have determined mutations of key genes relevant to colorectal cancer as well as gene expression profiles. We will use the clinical data for each de-identified sample to correlate with the DNA methylation, mutation and gene expression information so as to understand the driving forces behind these distinct colorectal subtypes. We have selected the most promising tumors for whole-genome bisulfite sequencing using next-generation sequencing technology to obtain complete maps of colon cancer methylomes. Researchers will be unable to identify the subjects because the samples and associated information have been de-identified and anonymized by the tissue source site. In addition, upon receipt by the USC Epigenome Center, we have assigned new random identifiers for each sample. The data generated using these new codes are not traceable to the patient identity.

  Study phs000385

• Genetic Neuroscience: How Human Genes and Alleles Shape Neuronal Phenotypes

  The goal of this collaborative, interdisciplinary project is to develop powerful, generalizable approaches for discovering how risk variants for psychiatric disorders shape neurobiological processes at multiple levels of analysis, and to identify the processes whose dysregulation underlies disease.Induced pluripotent stem cells (iPSCs) were used towards the development of these new experimental and inferential systems bridging gaps between human genetics and experimental biology. The largest publicly available collection of iPSCs (2607 lines) has been generated from 2184 donors by the California Institute for Regenerative Medicine (CIRM). To expand our donor collection, an additional 44 iPSC donors from the McLean_Levy cohort were identified. We wish to share the available SNP data for 2167 CIRM lines and whole genome sequence data generated at the Broad Institute for 473 of the CIRM and 44 McLean_Levy iPSC donors. These data can be used to identify (for experiments) lines with specific genotypes of interest and lines from donors with high or low polygenic risk scores for phenotypes of interest. The data can also be used to identify acquired mutations in the iPSC lines. The CIRM iPSC lines are available through Fujifilm Cellular Dynamics iPSC Repository (https://www.fujifilmcdi.com/cirm-ipsc-products/). The McLean_Levy lines are available through the NIMH Repository & Genomics Resource (https://www.nimhgenetics.org/).Additional project data registered with the study includes data from an iPSC line derived from an SMA patient (n=1), as well as single-cell RNA sequence data and supplemental processed genomic datasets in support of project publications.Molecular DatasetsSingle-cell RNA-seq: 10X Genomics, Illumina NovaSeqSupplemental "cell village" pooled genomic sequence data: Illumina NextSeqWhole Genome Genotyping: Infinium Global Screening Array-24 Kit, Illumina HumanCore chipWhole Genome Sequencing: Illumina NovaSeq

  Study phs002032

• HeLa Cell Genome Sequencing Studies

  HeLa is a human epithelial adenocarcinoma cell line that was derived from biopsy specimens of a 31-year old patient named Henrietta Lacks who was being treated for cervical cancer at The Johns Hopkins University Hospital in 1951. The specimens were obtained without her knowledge or consent just before her death in 1951. HeLa is the oldest and most widely used human cell line and has been an extraordinarily important resource for researchers throughout the world. HeLa cells have served as a standard for understanding many fundamental biological processes, such as testing the polio vaccine, establishing basic techniques for cloning and in vitro fertilization, identifying the cause of cervical cancer (HPV), and advancing the development of anti-cancer drugs.This study contains all authorized whole genome sequence data of the HeLa cell line from datasets currently in dbGaP. These data have been approved for health, medical, and/or biomedical research purposes. Access to these data can be granted for one year. Accessible data will include the studies listed on this page and any additional authorized datasets that become available during this one-year period. The HeLa Genome Data Access Working Group of the Advisory Committee to the Director (ACD) will review requests from the research community for access to these datasets and assess whether the requests align with the terms of use defined in the HeLa Genome Data Use Agreement. The Working Group's findings will be reported to the ACD, and the ACD will make recommendations to the NIH Director about whether a request should be approved or disapproved. The NIH Director will decide whether access to the data will be granted.

  Study phs000640

• Systems biology of Colorectal Cancer

  Colorectal cancer (CRC) is one of the most common cancers in both males and females, and it is perhaps the best understood of all epithelial tumors in terms of its molecular origin. Yet, despite large amount of work that has concentrated on understanding of colon tumorigenesis, we still do not know the full complement of molecular lesions that are individually necessary – and together sufficient – to cause colorectal cancer. Neither do we understand why some specific mutations that are relatively rare in other tumors (e.g. loss of the APC tumor suppressor) are extremely common in colorectal cancer. We propose here to use the tools of systems biology to develop a quantitative and comprehensive model of colorectal tumorigenesis. The model will include identification of cell-type specific and oncogenic pathways that contribute to colon tumorigenesis, and explain in molecular detail how a genotype of an individual CRC leads to activation of downstream genes that drive uncontrolled cell growth. This model will subsequently be used to find novel therapeutic targets, to guide genetic screening to identify individuals with elevated risk for developing CRC, and to classify patients into molecular subgroups to select the treatment combination that is optimal for each patient (personalized medicine). The specific objectives of the SYSCOL project are: 1. Identify genetic markers for individual risk using genotyping and sequencing of constitutional DNA from sporadic and familial CRC cases and controls 2. Identify genes and regulatory elements that contribute to colorectal cancer cell growth 3. Use data from Aims 1-2 to develop a quantitative model for colorectal tumorigenesis 4. Apply the model for identification of high-risk individuals, for molecular classification of the disease, and for identification of novel molecular treatment targets

  Study EGAS00001000854

• Whole exome sequencing of small cell neuroendocrine cancer of the cervix

  In order to improve treatment selection for high grade neuroendocrine carcinomas of the cervix (NECC), we performed a comparative genomic analysis between this rare tumor type and other cervical cancer types, as well as extra-cervical neuroendocrine small cell carcinomas of the lung and bladder. We performed whole exome sequencing on fresh-frozen tissue from 15 NECCs and matched normal tissue. We then identified mutations and copy number variants using standard analysis pipelines. Published mutation tables from cervical cancers and extra-cervical small cell carcinomas were used for comparative analysis. Descriptive statistical methods were used and a two-sided threshold of P < .05 was used for significance. In the NECC cohort, we detected a median of 1.7 somatic mutations per megabase (range 1.0-20.9). PIK3CA p.E545K mutations were the most frequency observed oncogenic mutation (4/15 tumors, 27%). Activating MAPK pathway mutations in KRAS (p.G12D) and GNAS (p.R201C) co-occurred in two tumors (13%). In total we identified PI3-kinase or MAPK pathway activating mutations in 67% of NECC. When compared to NECC, lung and bladder small cell carcinomas exhibited a statistically significant higher rate of coding mutations (P < .001 for lung; P = .001 for bladder). Mutation of TP53 was uncommon in NECC (13%) and was more frequent in both lung (103 of 110 tumors [94%], P < .001) and bladder (18 of 19 tumors [95%], P < .001) small cell carcinoma. These comparative genomics data suggest that NECC may be genetically more similar to common cervical cancer subtypes than to extra-cervical small cell neuroendocrine carcinomas of the lung and bladder. These results may have implications for the selection of cytotoxic and targeted therapy regimens for this rare disease.

  Study EGAS00001003142

• DAC for CTOS colorectal cancer organoids

  This Data Access Committee (DAC) is responsible for reviewing and approving access requests to controlled-access human sequencing data generated from colorectal cancer patient-derived organoids established using the CTOS method. The dataset includes whole-exome sequencing (WES) and RNA sequencing (RNA-seq) data. Access requests are evaluated for consistency with the original informed consent and the approved research purposes.

  Dac EGAC50000000915

• WTCCC2 case-control study for Ulcerative Colitis

  WTCCC2 project genome-wide case-control association study for Ulcerative Colitis (UC) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000084

• WES used for direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry

  We performed whole exome sequencing of tumor- as well as PBMC-derived DNA of five melanoma patients for identification of naturally presented patient-specific neoepitopes.

  Study EGAS00001002050

• Data from Shea et al Can Research 2025

  This dataset contains single cell RNA sequencing (192 fastq files for 59 samples), whole exome sequencing (20 BAM files -hg38- for 20 samples) and bulk RNA sequencing (138 paired-end fastq files and 17 single-end fastq files for 8 samples)

  Dataset EGAD50000001334

• FLT3 is genetically essential for ITD-mutated leukemic stem cells but dispensable for human HSCs

  bulk RNA sequencing of AML patients It contains 18 samples from primary AML patients. Half of the samples are control samples and half of the samples are FLT3-ITD knock-out (edited for the FLT3-ITD mutation). It is using Illumina high-throughput technology

  Dataset EGAD50000000636

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002915

• BLUEPRINT September 2016, ATAC-seq for class switched memory B cell from venous blood, on Genome GRCh38

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

  Dataset EGAD00001002908

• Exome and RNA sequencing data for Diffuse Large B Cell Lymphomas

  Exome sequencing data for 1001 DLBCL patients and RNA sequencing data for 775 DLBCL patients

  Dataset EGAD00001003600

• Dataset-linking-WGS-via-README-for-EGAS00001004884

  This dataset contains 139 Tumor and Control WGS files for samples for Gerhauser et al.,Cancer Cell, 2018, 34:996-1011. WGS and sequencing protocol was earlier described in Weischenfeldt et al, Cancer Cell, 2013.

  Dataset EGAD00001007669

• Demultiplexed FASTQs for each volunteer

  This submission consists of 15 volunteer FASTQs, split by chemistry: Chemistry v1.1: 7 FASTQ sets, one set for each volunteer (RA1-7) Chemistry v2: 16 FASTQ sets, two for each volunteer (RA8-15; FASTQ set 1: Gene Expression (GEX); FASTQ set 2: TCR enrichment (VDJ))

  Dataset EGAD00001007586

• PPGL RNA-Seq dataset

  Dataset includes fastq files for RNA-Seq experiments for tumor samples of PPGL patients. Single end reads fastq files are available for 102 different samples

  Dataset EGAD00001008578

• Data Access Committee for the DNA sequencing data included in the study "A generalizable machine learning framework for classifying DNA repair defects using ctDNA exomes”

  Dac EGAC00001003111

• PBMC

  Whole-Exome-Sequencing of 5 pooled patients for SNP-based demultiplexing

  Study EGAS50000000654

• SNP Array Data for EGAS00001004666

  SNP Array Data for EGAS00001004666

  Dataset EGAD00010002257

• DATA FILES FOR SJAMLM7

  DATA FILES FOR SJAMLM7

  Dataset EGAD00001000259

• "Usage of small amounts of DNA for Illumina sequencing"

  "Usage of small amounts of DNA for Illumina sequencing"

  Dataset EGAD00001000034

• WGS and WXS files for Dyer ATRX study

  WGS and WXS files for Dyer ATRX study

  Dataset EGAD00001003389

• DATA FILES FOR Histone Capture bams

  DATA FILES FOR Histone Capture bams

  Dataset EGAD00001000657

• DATA FILES FOR SJEWS-WGS

  DATA FILES FOR SJEWS-WGS

  Dataset EGAD00001001020

• DATA FILES FOR PCGP SJETP WXS

  DATA FILES FOR PCGP SJETP WXS

  Dataset EGAD00001001248

• Australian genomes

  Mapped data (bam files) for high-throughput whole genome sequence data for 83 modern Aboriginal Australians

  Dataset EGAD00001002001

• Treatment of Pulmonary Hypertension and Sickle Cell Disease with Sildenafil Therapy (Walk-PHaSST)

  Pulmonary arterial hypertension (PAH) is a progressive condition characterized by narrowing or stiffening pulmonary arterioles resulting in increased pulmonary blood pressure and reduced delivery of oxygenated blood to the body. It is a common complication of sickle cell disease and initially presents with the symptom of shortness of breath (dyspnea) on exertion. As the condition worsens, other symptoms such as dizziness, lower extremity edema, and chest pain can develop. The drug, sildenafil, works by relaxing blood vessels in the lungs which reduces pulmonary blood pressure and allows more oxygenated blood to circulate. Increased levels of oxygenated blood allows individuals with PAH to tolerate more activity, but guidelines for using sildenafil in patients with PAH and sickle cell disease were unavailable at the time of the Walk-PHaSST trial.Participants were screened for the existence of pulmonary hypertension with a six minute walk test and a Doppler echocardiogram that assessed TRV, diastolic function, and valvular and systolic function. Subjects with TRV ≥ 2.7 m/s received further clinical evaluation for possible causes of pulmonary hypertension. Other screening data included medical history, a physical exam, and standard laboratory testing. For individuals with moderate to severe pulmonary hypertension (TRV ≥ 3.0), a cardiac catheterization was done at the baseline and week 16 data collection periods.Subjects eligible for the main intervention trial based on screening results were randomized in a 1:1 double blind fashion to receive sildenafil or placebo for 16 weeks. Subjects received 20 mg of oral sildenafil or matching placebo 3 times daily for 6 weeks, followed by 40 mg 3 times daily for 4 weeks, followed by 80 mg 3 times daily for 6 weeks, as tolerated. Participants could also receive other therapies as needed to manage sickle cell and related complications. The primary outcome measure of the trial was change in the six minute walk test, a standard indicator of a person's heart and lung function and exercise capacity, from baseline to week 16. After completing the study treatment (or placebo), participants could choose to be part of the open-label follow-up phase of the study and continue to be assessed for up to one year.The study was intended to screen about 1000 subjects and randomize 132 subjects, however it was terminated early due to the unforeseen increase in adverse events in participants treated with sildenafil as compared to placebo. When the study was stopped, 33 participants had completed the trial. Subjects continued to be monitored, but were instructed to taper sildenafil treatment over three to seven days.There was no evidence that treatment with sildenafil impacted the six minute walk distance from baseline to week 16. In addition, treatment with sildenafil appeared to increase rates of hospitalization due to sickle cell disease pain.Due to in part to the early termination of the trial, the majority of subject data was collected from the screening phase of the study (n=720), as opposed to the main intervention trial (n=74).Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002383

• Germline DNA Methylation Associated with Breast Cancer Predisposition

  Understanding and explaining hereditary predisposition to cancer has focused on the genetic etiology of the disease. However, mutations in known genes associated with breast cancer such as BRCA1 and BRCA2 account for less than 25% of familial cases of breast cancer. Heritable epigenetic modifications, in the form of hypermethylated MLH1 promoter alleles, have recently been shown to promote hereditary nonpolyposis colorectal cancer. We investigated the potential for an epigenetic basis for hereditary breast cancer by performing deep bisulfite sequencing of CpG islands and known promoter regions in germline DNA from 100 familial or early-onset breast or ovarian cancer patients.

  Study phs001699

• dbGaP Collection: Psychiatric Genomics Consortium (PGC) dbGaP Datasets

  This dbGaP Collection includes cases and controls used in the GWAS meta-analysis of neuropsychiatric phenotypes studied by investigators in the Psychiatric Genomics Consortium including major depression, bipolar disorder, attention deficit and hyperactivity disorder, schizophrenia, Tourette Syndrome, and obsessive-compulsive disorder. The consent type for data sets includes general research use as well as phenotype-specific restricted usage. This dbGaP collection was created to facilitate identification of datasets used in PGC analyses in order to expedite the application and ascertainment process for PGC members wishing to access data within the consortium. Non-PGC members may also apply for this dbGaP collection.

  Study phs001254

• Japanese Reference Genome JG1

  The complete human genome sequence is used as a reference for next-generation sequencing analyses. However, some ethnic ancestries are under-represented in the reference genome (e.g., GRCh37) due to its bias toward European and African ancestries. Here, we perform de novo assembly of three Japanese male genomes using >100�� Pacific Biosciences long reads and Bionano Genomics optical maps per sample. We integrate the genomes using the major allele for consensus and anchor the scaffolds using genetic and radiation hybrid maps to reconstruct each chromosome. The resulting genome sequence, JG1, is contiguous, accurate, and carries the major allele for a Japanese population.

  Study JGAS000259

• Mutation of FOXL2 in granulosa cell tumors of the ovary

  We generated paired-end RNA-Seq data using the Illumina Genome Analyzer II platform for four adult granulosa cell tumours (GCTs) of the ovary (1 primary, 3 recurrent). We screened this data for the presence of GCT specific sequence variants and detected a non-synonymous mutation in the FOXL2 gene that was found to be recurrent in 97% of 89 additional GCTs. To measure genomic stability of the four index cases, we generated Affmetrix SNP 6.0 data and analysed these data for copy number changes. Raw sequence reads as well as Affymetrix CEL files are available to applicants.

  Study EGAS00000000040

• WES analysis of paired tumor and non-tumoral DNA of 4 patients with non-muscle-invasive bladder cancer

  We performed WES of tumor DNA and non-tumoral DNA (extracted from PBMC) of 4 patients with non-muscle invasive bladder cancer, who after the tumor resection went on to receive BCG treatment as they had high-risk disease. In order to identify tumor-specific mutations that could give rise to patient-specific neo-epitopes, we performed paired WES of tumor and non-tumoral DNA for each patient. For patient UC2, 3 different tumors were resected at the same time and DNA from these 3 tumors were sent separately for WES.

  Study EGAS50000001382

• Non-invasive prenatal diagnosis by genome-wide haplotyping of maternal cell-free plasma DNA

  Whereas non-invasive prenatal testing for aneuploidies (NIPT-A) is widely implemented, non-invasive prenatal testing for monogenic diseases (NIPT-M) is lagging. By capturing and targeted sequencing of 250000 polymorphic SNP loci from maternal plasma circulating cell-free DNA (cfDNA) and DNA from relatives, the fetal haplotype and chromosomal copy numbers are deduced. In all families tested, the cfDNA derived haplotypes are on average 97% concordant with the neonatal and embryo haplotype. This generic non-invasive prenatal diagnostic approach allows cost efficient scrutinizing the fetal genome for the presence of any inherited monogenic disease or trait.

  Study EGAS00001003634

• Novel Epigenetic Markers for Toxicity after Intraoperative and Conventional Radiotherapy for Breast Cancer

  Ionizing radiation is a common treatment option for cancer but its use is limited by the unpredictable and highly heterogeneous onset of late side effects, especially radiation-induced fibrosis. Clinically applicable biomarkers and effective treatments for radiation fibrosis are currently unavailable. In order to identify novel markers we ran a genome-wide DNA methylation screen in primary dermal fibroblasts obtained from breast cancer patients before intraoperative radiotherapy. Cells from patients developing fibrosis within a three-year follow up were compared to those without fibrosis (12 individuals per group). Illumina Infinium HumanMethylation450 BeadChip Technology was used.

  Study EGAS00001001279

• The_Causes_of_Clonal_Blood_Cell_Disorders_Study___SCOR

  We will take a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We will grow these up into colonies, then whole genome sequence each colony. Somatic mutations will act as a unique barcode for each clone. We will then design a panel for targeted resequencing of the mutations that we find. It will then be possible to look for these mutations in the peripheral blood over several years, to see the dynamics of how HSCs contribute to the peripheral blood in health.

  Study EGAS00001002132

• scRNA seq and scTCR seq data from 5 melanoma patients

  The Chromium Controller and Chromium X platfor of 10X Genomics were used for single cell partitioning and barcoding. Each cell's transcriptome was barcoded during reverse transcription, pooled cDNA was amplified and Single Cell 5' Gene Expression (GEX), V(D)J and Feature Barcode (FB) Libraries were prepared according to the manufacturer's protocols (CG000330 and CG000331, 10X Genomics). All libraries were quantified and normalized on library QC data generated on the Bioanalyzer system according to manufacturer's protocols (G2938-90321 and G2938-90024, Agilent Technologies). Based on the expected target cell counts, a balanced library sub-pool of samples was compsed for SC5'GEX, V(D)J and FB libraries. Library sub-pools were quantified by qPCR, accodring to the KAPA Library Quantification Kit Illumina(R) Platforms protocol (KR0405, KAPA Biosystems). Based on qPCR results a final sequencing pool was composed. Paired end sequencing was performed on a NovaSeq 6000 Instrument (Illumina) using NovaSeq 6000 Reagent Kits v1.5 100 cycles (cat. no. 20028401, 20028319, 20028316 Illumina), using 28 cycles for Read 1, 10 cycles for Read i7, 10 cycles for Read i5 and 90 cycles for Read 2.

  Dataset EGAD50000001155

• sc-DECISION

  Data derived from PBMC and blood samples for the single cell and bulk RNAseq analysis for the sc-DECISION paper. https://doi.org/10.1101/2025.02.04.25321370

  Dac EGAC50000000642

• Pulldown_DNA_methylation_study_v2

  Pilot study to set up sequencing protocols for targeted pulldown methylation profiling

  Study EGAS00001000979

• Preeclampsia InterPregGen Consortium: GWAS meta-analysis summary statistics for European fetal preeclampsia cases versus controls and GWAS genotype data for European fetal preeclampsia cases

  Study EGAS00001001048

• PBMC_dual_10X_kit

  Dual snRNAseq and ATACseq of replicate PBMC samples for 10X beta testing.

  Study EGAS00001004834

• Dataset for TIX

  All files for TIX individuals

  Dataset EGAD50000000426

• RNAseq for 4 pdx and 1 cell-line

  RNAseq for #1049, #111, #1217, #206, COV362

  Dataset EGAD50000000032

• DATA FILES FOR SJEPD

  DATA FILES FOR SJEPD

  Dataset EGAD00001000853

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000352

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000353

• Dataset for "Genomic landscape of oral cancers" (CGI WGS)

  Dataset for "Genomic landscape of oral cancers" (CGI WGS)

  Dataset EGAD00001004339

• Dataset for "Genomic landscape of oral cancers" (Illumina WGS)

  Dataset for "Genomic landscape of oral cancers" (Illumina WGS)

  Dataset EGAD00001004356