Search Results - EGA European Genome-Phenome Archive

Dataset for whole exome sequencing of 113 pairs of tumor and normal DNA samples along with 8 cell lines

Dataset for whole exome sequencing of 113 pairs of tumor and normal DNA samples along with 8 cell lines.

Dataset EGAD00001001006

McGill EMC Release 4 for assay "ATAC-seq"

McGill EMC Release 4 for assay "ATAC-seq": Sequencing of transposase-accessible chromatin as described by Buenrostro et al. (Nature Methods 10, 1213?1218 (2013) doi:10.1038/nmeth.2688)

Dataset EGAD00001001300

GBM-ZEB1: RNA sequencing of parental tumors used for cell line generation

This dataset contains RNA sequencing raw data from four parental tumors that were used for classification of gene expression subtypes (Verhaak, Cancer Cell 2010) using ssGSEA.

Dataset EGAD00001001627

BLUEPRINT: WGBS-seq for monocytes and neutrophils

WGBS-seq for monocytes and neutrophils

Dataset EGAD00001000673

Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

The TARGET Study consists of 200 BAM files, for the 100 patients discussed in the publication. Each patient has a normal control BAM file and a ctDNA BAM file.

Dataset EGAD00001004796

Single Cell RNA Seq GBM

Single Cell RNA sequencing for 4 high grade glioma samples. NovaSeq6000 was used for snRNA Seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005369

Single Cell RNA Seq LGG

Single Cell RNA sequencing for 5 low grade glioma samples. NovaSeq6000 was used for scRNA Seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005368

WGS files for Mullighan_GL_reALL

WGS files for Mullighan_GL_reALL paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005506

WXS files for Mullighan_GL_reALL

WXS files for Mullighan_GL_reALL paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005509

Hospital for Sick Children 2020 Pediatric Low-Grade Glioma RNA and Targeted DNA Sequencing

Whole transcriptome and targeted dna sequencing (Ampliseq) of pediatric low-grade glioma samples at the Hospital for Sick Children

Dataset EGAD00001005987

sWGS for genome-wide copy number profiling

Shallow whole-genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of metastatic colorectal cancer patients (mCRC).

Dataset EGAD00001006384

RNA-seq data from paired tumour and germline samples from mesothelioma patients for study EGAS00001005196

Dataset EGAD00001007874

Hi-C for Junvenile Pilocytic Astrocytomas

5 Hi-C datasets (4 JPA and 1 LGG). Hi-C data for the remaining 5 JPAs used in our paper as well as all controls have been uploaded to EGA under EGAS00001005476.

Dataset EGAD00001009044

Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

Dataset EGAD00001011123

Amplicon Sequencing for 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

BAMs from deep sequencing using a custom panel for the study 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

Dataset EGAD00001015012

Dataset for transcriptome sequencing of forebrain organoids from Lissencephaly patients

This dataset contains transcriptome sequencing for 16 samples of forebrain organoids from Lissencephaly patients. The sequencing was performed on Illumina NextSeq 6000 . The sequencing was always paired.

Dataset EGAD00001015688

Center for Common Disease Genomics [CCDG] - Autoimmune: Inflammatory Bowel Disease (IBD) Exomes and Genomes

The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of: undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases; understanding how best to design rare variant studies for common disease; developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The overarching aim of the Inflammatory Bowel Disease (IBD) program is to define the full allelic spectrum of protein-altering variation in genes associated to IBD, and assess their role in both Crohn's Disease (CD) and Ulcerative Colitis (UC) risk. The whole genome sequencing data generated here is comprised of samples from US-based diverse populations including African American, Puerto-Rican, Caribean and Cuban origins.

Study phs001642

National Human Genome Research Institute (NHGRI) Clinical Sequencing Exploratory Research (CSER) The MedSeq Project: Integration of Whole Genome Sequencing into Clinical Medicine (HG006500)

Whole genome sequencing (WGS) and whole exome sequencing (WES) services are currently available to and being utilized by physicians and their patients in both research and clinical settings, and recently to anyone in the general public via direct-to-consumer companies. But the widespread availability and use of WGS and WES in the practice of clinical medicine is imminent. In the very near future, sequencing of individual genomes will be inexpensive and ubiquitous, and patients will be looking to the medical establishment for interpretations, insight and advice to improve their health. Developing standards and procedures for the use of WGS information in clinical medicine is an urgent need, but there are numerous obstacles related to integrity and storage of WGS data, interpretation and responsible clinical integration. The MedSeq Project is an exploratory trial of WGS in clinical medicine. At the conclusion of this study, we will have helped create innovative protocols and novel outcome measures that can be applied safely in future large-scale multi-site randomized clinical trials with larger numbers of physicians from broad specialties and with more economically and ethnically diverse patients. Together with our colleagues from across the nation through the U01 consortium formed as a result of this funding from the NIH, we will have invented a process of implementation and evaluation whereby the fruits of the Human Genome Project can be applied for the first time to the daily practice of medicine for the betterment of human health. The objectives of the MedSeq Project are to: Recruit, consent and enroll 2 study groups: 10 primary care physicians and 100 of their healthy middle-aged patients 10 cardiologists and 100 of their patients with cardiomyopathy. Randomize each study group to receive standard of care versus standard of care plus WGS. Monitor the entire protocol for subject safety. Only half the enrolled patients were selected for sequencing. Fifty subjects were selected from the primary care cohort and fifty were selected from the cardiomyopathy cohort. Whole genome sequencing was performed at 30x coverage in Illumina's CLIA-certified laboratory on these 100 individuals. Generate and optimize an algorithm for interpreting WGS data covering the spectrum of human genetic variation, in terms of both previously reported and novel variants likely to influence the health of patients. Create patient reports and provide an interface for communicating clinically relevant genomic information to practicing physicians. Describe physicians' and patients' attitudes toward, and preferences for, the disclosure of WGS results at the start of the study. Evaluate physicians' experiences with receiving and interpreting patients' genetic test results and how they communicate these results to their patients. Explore how patients respond to and use WGS results by administering validated scales of psychological impact, personal utility, and behavioral responses, as well as economic and health outcomes. Although we do not have a large enough sample size for statistical comparisons of outcomes, we will conduct exploratory comparisons: Exploratory Hypotheses: Patients who receive WGS results will show equivalent levels of distress compared to patients who receive family history only. Patients with higher genetic literacy and better understanding will report greater satisfaction and less decisional regret. Patients who receive WGS will (a) be more likely to change health behaviors and (b) utilize more health care resources than those who do not receive WGS.

Study phs000958

HTAN MCL Pre-Cancer Atlas Pilot Project - Targeted Sequencing Development Study

The HTAN-MCL Pre-Cancer Atlas Pilot Project (PCAPP) is the result of a collaboration between the seven members of the MCL consortium. Across four organ types, PCAPP's goal is to collect and profile pre-malignant lesions for gene expression, DNA mutations, single-cell gene expression and immune-environment. Most PML are small in size and only available come from formalin fixed paraffin embedded archived tissue. The primary goal of PCAPP is to 1) understand the logistical challenges of PML specimen collection, 2) document technical limitations of the assays that are specific to the PML and 3) overcome them to support the generation of a more comprehensive Pre-Cancer Atlas in the future. The current upload provides RNA and DNA sequencing from participants with DCIS who were studied at the University of San Diego and the University of Vermont. Description of the overall study: A. Background/Significance One of the critical barriers to developing new approaches for cancer detection and prevention is the lack of understanding of the key molecular and cellular changes that cause cancer initiation and progression. Unlike the extensive work that has been done profiling advanced stage tumors, few studies have comprehensively profiled the molecular alterations found in precancerous tissues. Premalignant lesions are currently characterized by histologic changes that precede the development of invasive carcinoma1,2.These lesions can often be identified in regions surrounding an invasive tumor or in biopsies taken from patients undergoing diagnostic evaluation for suspicion of cancer. Currently, limited metrics exist to identify lesions that will likely progress to carcinoma and require intervention from those that will naturally regress or remain stable3,4. Characterization of the molecular alterations in premalignant lesions and the corresponding changes in the microenvironment would hasten the development of biomarkers for early detection and risk stratification as well as suggest preventive interventions to reverse or delay the development of cancer. Our pilot study will establish the feasibility of transcriptomic, genomic and immune profiling of FFPE premalignant lesions from multiple organ sites, collected and profiled with uniform SOPs across multiple institutions within the MCL consortium. We will characterize the molecular alterations in precancerous lesions and the corresponding microenvironment in four major organ sites, in order to uncover the molecular and cellular determinants of premalignancy, and establish standardized sequencing and immunohistochemistry protocols on FFPE precancerous tissue. We will also evaluate the technical feasibility of single nuclei sequencing of small FFPE pre-cancer lesions. Successful completion of the proposed pilot study will set the stage for expansion and development of a comprehensive Pre-Cancer Atlas (PCA) as part of the NCI's moonshot.B. Specific Aims Aim 1: Collect premalignant lesions (PML) and their associated microenvironment via LCM from FFPE tissue across four organ sites (breast, lung, pancreas & prostate). Aim 2: Perform bulk RNA and DNA seq on premalignant FFPE samples (and flash frozen tissue where available) and compare the genomic/transcriptomic alterations within and across organ sites. C. ApproachAim 1: Collect premalignant lesions (PML) and their associated microenvironment via LCM from FFPE tissue across four organ sites (breast, lung, pancreas & prostate). MethodsI. Patient Population/Sample Collection: Overview of the sites collecting PML tissue from the respective organs is provided in Table 1 and a full description of the biospecimens to be obtained is described in detail for each organ type below. Table 1. Breakdown of cohort by tissue type and collection site.Organ siteBreastLungPancreasProstateType of PMLDCISAAH, Squamous Dysplasia/CISIPMNsPINCollection of PatientsUCSF/UCSDUVMBU*/UCLAVanderbilt/MoffittMDACC*JHUStanford*# of Patients201920 (10 of each type)20 (10 of each type)242020Total patients per Organ39402440Note: single nuclei/cell RNA-Seq will be performed on 4-5 FFPE samples from each of the organ types 1. DCIS lesions from breast tissue: DCIS lesions will be collected from 39 patients (20 from UCSF/UCSD & 19 from UVM) with primary low or high-grade DCIS diagnosed from a breast core biopsy. Subsequent resected lumpectomy or mastectomy tissues will be prospectively sampled in the vicinity of the prior biopsy site using multiple approaches: 1) Live cells (heterogeneous mix) will be obtained as a cell scrape slurry from the lesion surface or by fine needle aspirate (FNA); 2) For a subset of specimens where size is sufficient, a block of breast tissue with DCIS will be fresh-frozen; 3) The remainder of the specimen will be taken for routine formalin-fixation and paraffin-embedding (FFPE). The FFPE sample will be annotated to identify the matched FFPE tissue block adjacent to the fresh-frozen sample and will be sectioned for use in bulk and single nuclei sequencing . We will dissect DCIS, adjacent normal and when available, associated carcinoma. In addition, when possible, normal tissue will be collected from a tissue block lacking lesions as well as collection of blood. A subset of patients (n = 5 | FFPE, flash frozen and fresh) will be sent to the Broad Institute for single nuclei/cell sequencing.2. AAH and squamous dysplastic/CIS lesions from airway and lung tissue: For squamous cell lung cancer, we will collect endobronchial biopsies from abnormal airway regions identified on autofluroscence bronchoscopy or identify PMLs in the margins of resected lung tissue. We will study 20 patients (5 each from BU/UCLA/Vanderbilt/Moffitt) with pre-invasive squamous lesions (moderate-severe dysplasia or carcinoma in situ (CIS)) identified on pathologic examination. LCM of the premalignant region and adjacent normal epithelium will be performed as well as the invasive tumor for those collected from the resection margin (n=5 from UCLA). On a subset of lesions collected at bronchoscopy (n=5), we will collect additional biopsies that will be flash frozen and fresh for single nuclei and cell sequencing, respectively, performed at the Broad Institute. In parallel to the work at the Broad, BU will perform single cell RNA-seq on these freshly cell sorted tissues (n = 5). Blood will be collected on all patients for genomic studies. For lung adenocarcinoma, we will collect resected FFPE lung tissues from 20 patients (10 from UCLA and 10 from Vanderbilt/Moffitt) with early stage lung adenocarcinoma that harbor atypical adenomatous (AAH) premalignant lesions in the resection margin. We will LCM multiple AAH regions (3-5 per patient) as well as adjacent regions of normal epithelium and invasive adenocarcinoma. In addition, blood will be collected on all patients for genomic studies. 3. IPMNs from pancreatic tissue: For pancreatic cancer PML, we will collect low and high grade lesions from 24 patients representing macroscopic Intraductal Papillary Mucinous Neoplasms (IPMN) (n=24) from surgically resected specimens along with blood samples. Archival FFPE specimens of microscopic PanIN lesions, occurring multi-focally adjacent to invasive PDAC, and archival IPMN lesions (with or without associated invasive cancer), along with the adjacent normal tissue, will undergo LCM and utilized for bulk DNA and RNA sequencing. If matched frozen tissues are available for a subset of these FFPE samples, we will bank for comparison of profiles. Because IPMNs are macroscopic lesions, they provide an opportunity for obtaining the samples fresh and therefore can be used for single cell sequencing (in contrast to PanINs). Therefore, 5 freshly obtained IPMNs will be used for the single cell RNA sequencing studies performed at both the Broad Institute and MDACC, and the matched FFPE and/or frozen sections from these lesions (obtained from the adjacent PML) will be sent to Broad Institute as a pilot to assess "single nuclei" RNA sequencing.4. PINs from prostate tissue: For prostate cancer PML, there will be 40 samples of Prostatic Intraepithelial Neoplasia (PIN) collected between the Stanford and JHU sites (20 cases per site). At the Stanford site, 20 prostate specimens detected by PSA screening who have/will undergo surgery (radical prostatectomy) for clinically localized disease will make up the final cohort. The age range of the participants would be 40-75, and we anticipate that 18 will be Caucasian, 1 Asian and 1 Latino or African American based on the practice demographics practice at Stanford. Clinical and MRI data will also be collected for these samples. We will collect low grade (e.g. Gleason score of 6/Grade group 1; n=10) and high grade (Gleason score 4+3=7 or higher/Grade group 3 or higher; n=10) PINs from FFPE samples that have prostate carcinoma. In addition to obtaining LCM archival samples of low and high grade PIN, we will also obtain normal prostatic epithelial from the peripheral, central and transition zones as well as multiple samples of prostate carcinoma in order to obtain the spectrum of Gleason grades in the carcinoma as needed. LCM samples will be used for bulk DNA and RNA sequencing. In addition, single cells will be dissected from FFPE samples to prepare single cell RNA seq libraries using techniques developed at Stanford, and FFPE tissue will be sent to the Broad for single nuclei sequencing. When available, flash frozen and fresh samples from these prostates will be archived and prepared for single nuclei and cell sequencing, respectively, at the Broad Institute and at Stanford (single cell only). JHU will also capture 10 cases (5 grade group 1 and 5 grade group 2) of high grade PIN, normal and invasive adenocarcinoma using frozen sections from fresh frozen tissues. When possible these will be from the same patients as the FFPE samples. Since frozen sections can be quite challenging to morphologically determine high grade PIN from normal epithelium, for these samples we will perform a number of additional tissue-based characterizations. These will include a multicolor combined basal cells (p63 and CK903) and PIN/carcinoma markers (AMACR) referred to in the cocktail as "PIN4", c-MYC (referred to as MYC) protein5, by IHC and mRNA by in situ hybridization (AM De Marzo, Q Zheng unpublished observations), telomere length by in situ hybridization6 and the 5'ETS/45S rRNA7. For these slides, the whole slides will be scanned with a Hammamatsu Nanozoomer with a 40x objective and regions of interest will be annotated as a guide for LCM.II. Laser-capture microdissection (LCM): FFPE tissue blocks will be sectioned at 7μm thickness and serial sections will be stained with H&E. LCM will be performed utilizing standard LCM systems, such as Leica LMD7000 and ArcturusXT at each site. Regions of premalignancy will be dissected and RNA/DNA will be extracted from microdissected cells using the Qiagen All Prep DNA/RNA FFPE Kit. Aim 2: Perform bulk RNA and DNA seq on premalignant FFPE samples and compare the genomic/transcriptomic alterations within and across organ sites. Rationale: There have been limited studies characterizing the genomic and transcriptomic landscape of premalignant lesions associated with breast, pancreatic, lung or prostate cancers. Characterizing the molecular determinants of premalignant disease that are unique and shared across multiple organs will enable new candidate biomarkers for early detection and novel therapeutic strategies for early intervention. MethodsBulk RNA-seq of LCM FFPE tissue: All participating sites will perform bulk RNA-seq in accordance with SOPs developed at BU. In brief, total RNA will be isolated from LCM'd lesion and associated microenvironment tissue using the Qiagen All Prep DNA/RNA FFPE Kit and quality will be assessed with the Agilent Bioanalyzer. Libraries will be generated with the Illumina TruSeq Access kit (for FFPE samples). They will be sequenced on the Illumina HiSeq2500 with 75base-pair paired-end reads. Quality of FASTQ files will be assessed with FastQC. Reads will be aligned to the human genome with STAR and gene-level and isoform-level expression will be quantified with RSEM. Splice junction saturation, transcript integrity, and biotype distributions will be calculated for each sample with RSeQC. DESeq2 and EdgeR will be used to identify associations between gene expression profiles and clinical variables while controlling for confounding covariates. BU will serve as an RNA-seq Core to assess reproducibility of FFPE RNA-seq methods across sites. We will perform RNA-seq according to the SOP listed above on a subset of samples for each organ type (total n ~ 20). Bulk seq of DNA from FFPE tissue: All participating sites will perform targeted or whole exome-seq (WES) in accordance with SOPs. In brief, DNA from laser captured material will be isolated using the Qiagen All Prep DNA/RNA FFPE Kit and undergo stringent quality control to ensure high quality input material for genomic profiling. Purified DNA (ideally 100-200 ng) will be used for library preparation and amplification, followed by next generation sequencing using standard protocols distributed by CDMG. Exome-seq methods are considered standardized, thus we will not need a DNA-seq Core to assess reproducibility across sites. We anticipate local centers will use Illumina paired end reads, following the following general approach. 1) DNA library preparation: Paired-end libraries will be prepared following the manufacturer's protocols (Illumina and Agilent), fragmented to 150-200 bp 2) Capture of targeted exome: Whole exome capture will be carried out using the protocol for Agilent's SureSelect Human All Exon kit. Purified capture products will be amplified using the SureSelect GA PCR primers (Agilent) for 12 cycles. 3) Sequencing will be carried out for the captured libraries using at least 100 bp paired-end reads. To achieve high level sensitivity and accuracy for detecting all the mutations in the whole exome, each sample will be sequenced at 200X mean depth. 4) Read mapping and alignment and variant analysis: Sequence short reads will be aligned to a reference genome (NCBI human genome assembly build 38) using BWA-MEM. Local realignment of aligned reads will be performed using Genome Analysis Toolkit (GATK).Data QC: To ensure scientific rigor and consistency among sites in RNA and DNA processing we will include a preliminary analysis of steps in processing and analysis. Protocols for extraction of high quality RNA and DNA from formalin fixed paraffin embedded (FFPE) tissues, which will be used extensively in these studies continue to improve and may have variable implementation among the sites participating in this study. To evaluate consistency of preliminary steps in processing and downstream analyses, we will initially distribute slides from one large FFPE fixed cancer of origin from prostate, breast, lung and pancreatic cancer. Analysis of these samples will allow us to review the DNA and RNA characteristics (yield, purity and strand length) among sites. Downstream analysis of these same samples will also allow us to compare among sites the consistency of variant calls among centers. We will be able to identify if there are some times of calls (such as small insertion deletions) that are more variable among centers versus other types of calls (such as relative gene expression or single base pair substitutions) that we expect to be less variable and to characterize the reliability of findings across sites. We are also including a 5% blind duplicate analysis of RNA sequencing. Samples will be analysed by the participating genomics cores without knowledge of the phenotype. RNA seq and CNA analyses are normalized for batch effects. We will also compare the observed sex to the self-reported sex as based on RNA profiles and exome sequencing of X chromosome genes as another check for processing accuracy and sample management. D. References 1. Wacholder, S. Precursors in Cancer Epidemiology: Aligning Definition and Function. Cancer Epidemiol. Prev. Biomark. 22, 521-527 (2013). PMID: 23549395.2. Berman, J. J. Precancer: The Beginning and the End of Cancer. (Jones & Bartlett Learning, 2011).3. Nasiell, K., Nasiell, M. & Vaćlavinková, V. Behavior of moderate cervical dysplasia during long-term follow-up. Obstet. Gynecol. 61, 609-614 (1983). PMID: 6835614.4. Merrick, D. T. et al. Persistence of Bronchial Dysplasia Is Associated with Development of Invasive Squamous Cell Carcinoma. Cancer Prev. Res. (Phila. Pa.) 9, 96-104 (2016). PMID: 26542061.5. Gurel, B. et al. Nuclear MYC protein overexpression is an early alteration in human prostate carcinogenesis. Mod. Pathol. Off. J. U. S. Can. Acad. Pathol. Inc 21, 1156-1167 (2008). PMID: 18567993.6. Meeker, A. K. et al. Telomere shortening is an early somatic DNA alteration in human prostate tumorigenesis. Cancer Res. 62, 6405-6409 (2002). PMID: 12438224.7. Guner, G. et al. Novel Assay to Detect RNA Polymerase I Activity In Vivo. Mol. Cancer Res. MCR 15, 577-584 (2017). PMID: 28119429.

Study phs002225

Center for Common Disease Genomics [CCDG] - Cardiovascular: TexGen

Cardiovascular disease (CVD), especially coronary heart disease, heart failure and cerebrovascular disease remain the leading causes of death in men and women across all race groups in the United States. Substantial evidence exists for genetic factors underlying CVD risk, and their discovery offers an opportunity to enhance understanding of disease mechanisms, to provide specific diagnostic and prognostic indicators, and to identify novel therapeutic targets. The Centers for Common Disease Genomics (CCDG) are a large-scale genome sequencing effort undertaken as a collaboration to identify rare risk and protective alleles for common chronic diseases, with a current focus on early onset heart disease, hemorrhagic stroke, and autism. In this study, whole genome sequencing (WGS) was performed in 6,146 individuals with any personal or family history of CVD from the TexGen study who were recruited from several institutions in the Texas Medical Center located in Houston, Texas. The participants included patients who were admitted with a variety of diagnoses including acute coronary syndromes, strokes, and transient ischemic attacks, or who underwent percutaneous coronary interventions or coronary artery bypass grafting (CABG) (Virani SS et al. Am J Cardiology 107:1504-1509, 2011). Patients in the TexGen cohort with a confirmed diagnosis of acute coronary syndrome (ACS) or CABG when discharged from the hospital between 2001-2008 were eligible for a follow-up study of recurrent myocardial infarction (Virani SS et al. Circulation J 76:950-956, 2012), while those presenting with ACS beginning in 2007 were recruited for an investigation of the role of depressive symptoms in the risk of major adverse coronary events (Sanner J et al. Biol Res Nurs 20:168-176, 2018). In addition, the initial criterion for enrollment in a third TexGen sub-study undertaken between 2007 and 2013 was the occurrence of premature acute myocardial infarction in men ≤ 50 years and women ≤ 55 years in order to establish a blood sample collection resource with the intention of localizing genes that contribute to disease risk. This definition was later expanded to include individuals with a clinical history of premature coronary heart disease such as CABG or percutaneous coronary interventions.

Study phs003010

Effectiveness and Safety of Intermittent Antimicrobial Therapy for the Treatment of New Onset Pseudomonas Aeruginosa Airway Infection in Young Patients With Cystic Fibrosis (EPIC-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To investigate the efficacy and safety of 4 antipseudomonal treatments in children with cystic fibrosis (CF) with recently acquired Pseudomonas aeruginosa (PA) infection.Background: CF is an inherited disease that causes mucus to build up in the lungs and digestive tract, which can cause lung infections and digestive problems. It is the most common type of chronic lung disease in children and young adults and may result in early death. There is no cure for this disease. The primary cause of death in individuals with CF is progressive obstructive pulmonary disease associated with chronic Pseudomonas aeruginosa (PA) infection. PA infection can occur early in life and can become highly resistant to antibiotics. Once an individual has been diagnosed with chronic PA infection, it is almost impossible to manage effectively. The need exists for an effective treatment to control and eliminate PA infection. Past research has shown that if PA infection is treated early, there is a greater likelihood that it may be eliminated completely.Participants: There were 304 participants.Design: Participants were randomized to 1 of 4 antibiotic regimens for 18 months (six 12-week quarters) between December 2004 and June 2009. Participants randomized to cycled therapy received tobramycin inhalation solution (300 mg twice a day) for 28 days, with oral ciprofloxacin (15-20 mg/kg twice a day) or oral placebo for 14 days every quarter, while participants randomized to culture-based therapy received the same treatments only during quarters with positive P aeruginosa cultures. The primary end points were time to pulmonary exacerbation requiring intravenous antibiotics and proportion of PA - positive cultures.Conclusions: No difference in the rate of exacerbation or prevalence of PA positivity was detected between cycled and culture-based therapies. Adding ciprofloxacin produced no benefits (Arch Pediatr Adolesc Med 2011; 165(9):847-856).

Study phs004067

Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and &gt;124,000 in silico alterations and evaluated the methodology in &gt;2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) &gt;97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p &lt; 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) &gt;99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of &lt;5% and average PPA &gt;99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited &gt;98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

Study EGAS00001005556

Professors Colin Palmer and Ewan Pearson, from University of Dundee, are both members of the Access Group panel for the GoDARTS bioresource, which provided the data for the current study. The current Study used genotypes (EGAD00010000282) generated by the WTCCC2 (EGAS00000000121), on which both Colin and Ewan are also DAC panel members.

Dac EGAC00001000504

DAC for "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients."

This is the DAC for the study "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients." of Andreas Trumpp (a.trumpp@dkfz.de), Roberto Würth (r.wuerth@dkfz.de) and Martin Sprick (Martin.Sprick@hi-stem.de).

Dac EGAC50000000371

NGS-based targeted exome sequencing of osteosarcoma

The present study aimed to identify potential genomic markers for the prediction of chemosensitivity in patients with OS using a genomic approach.

Study JGAS000282

Clinical and neuroimaging study on preclinical Alzheimer's disease.

This clinical study aims to discriminate MCI individuals at risk for development of Alzheimer dementia, as well as preclinical AD without clinical manifestations.

Study JGAS000272

Zimbabwe Mendelian Disorders Genomics DAC

Data Access Committee responsible for reviewing and approving access requests to human genomic data generated from individuals with suspected Mendelian disorders. The DAC ensures ethical use of genomic data in accordance with institutional, national, and international guidelines, protecting participant privacy while enabling responsible data sharing for research purposes.

Dac EGAC50000000963

WGS of ecDNA neuroblastoma cell lines

ecDNA reconstruction for MYCN-amplified neuroblastoma cell lines using shallow long-read whole-genome sequencing (MinION platform, WGS mean-coverage 5-10X).

Study EGAS50000000349

scRNA-seq for 4 reactive lymph node and 12 high grade B cell lymphoma samples

Dataset includes count matrices, barcode tsvs, and features tsv for each sample, generated using Cell Ranger.

Dataset EGAD50000001386

miRNA

miRNA Sequencing of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.

Dataset EGAD50000001532

Dataset for "HPV integration induces gene fusions" (pacBio)

pacBio whole-genome sequencing data for "HPV integration induces gene fusions" We performed long read whole-genome sequencing on four HPV+ head and neck cancer samples using pacBio HiFi. The sequence reads were submitted in fastq format.

Dataset EGAD50000001304

WGS dataset for two NUP98-Rearranged Acute Myeloid Leukemia PDX samples

This dataset includes whole genome sequencing of two patient-derived xenograft (PDX) samples with NUP98-Rearranged Acute Myeloid Leukemia. Bam files are provided for each sample.

Dataset EGAD50000001563

Dataset for WGS and RNA melanoma samples

This dataset contains WGS and RNA sequencing data for 4 melanoma samples. Sequencing was performed on Illumina Novaseq 6000 and Illumina HiSeq X. The sequencing was always paired.

Dataset EGAD50000000093

Exome_sequencing_of_Non_syndromic_Congenital_Heart_Defects

Exome sequencing of ~1,800 patients with non-syndromic Congenical Heart Defects (CHD) to identify genes enriched for damaging rare variants that increase risk of CHD

Study EGAS00001002522

WTCCC2 Bacteraemia Susceptibility (BS) samples

A WTCCC2 project genome-wide association study for bacteraemia susceptibility in 4924 individuals from Kenya, genotyped on the Affymetrix 6.0 array.

Study EGAS00001001756

Whole exome sequencing data for patients with Bosma arhinia microphthalmia syndrome (BAMS)

Whole exome sequencing data for patients with Bosma arhinia microphthalmia syndrome (BAMS). The dataset includes 21 samples from 7 families with BAMS; see Gordon et al, Nature Genetics, 2017.

Dataset EGAD00001003130

Transcriptomic profiles of neuroblastoma PDXs and primary tumors

This dataset contains bam files for RNA-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft) and 3 pairs of neuroblastoma tumors at diagnosis and at relapse.

Dataset EGAD00001003393

Whole Genome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

Dataset EGAD00001003435

Exome and Transcriptome for pan-cancer gene-drug analysis

Total of 584 tumor specimens and/or patient-derived cells across 14 cancer types were subjected for whole-exome/targeted-exome and/or whole-transcriptome sequencing.

Dataset EGAD00001003441

Exome sequencing of patients with acute promyelocytic leukemia

The dataset consists in 64 fastq files from 23 patients with acute promyelocytic leukemia. Exome sequencing was conducted on several stages (Diagnosis, Remission, Relapse) for each patient. For 5 patients, only Diagnosis and Relapse samples are available.

Dataset EGAD00001004043

A Hematogenous Route for Medulloblastoma Leptomeningeal Metastases

Dataset EGAD00001003907

Discordant_Monozygotic_Twins_ALS (Epigenetics)

We conducted a multi-omics study on a monozygotic twin pair discordant for amyotrophic lateral sclerosis. Here, we submit epigenetic data from EPIC array.

Study EGAS00001008053

Glioblastoma stem cell lines WGS data

WGS data for 20 Glioblastoma stem cell (GSC) lines and matched blood samples. Fastq files are available. For 10 GSC samples and the 10 matched blood samples the reads are on 3 fastq files per sample

Dataset EGAD00001006488

Cram files for study entitled Compound heterozygous variants in LAMC3 in association with posterior periventricular nodular heterotopia

This dataset contains three cram files for paired end sequencing of a trio, sequenced with Illumina Hiseq 2500

Dataset EGAD00001006578

BLUEPRINT release January 2015, DNase-Hypersensitivity for monocyte

DNase-Hypersensitivity data for 2 monocyte sample(s). 4 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

Dataset EGAD00001001185

GENCORD2_GENOTYPES

204 individuals were genotyped with the Illumina 2.5M Omni chip. Filtered genotypes were imputed into the 1000 genomes project European panel SNPs. Beagle R2 is indicated in VCF files for further filtering. See Materials and Methods in publication for details.

Dataset EGAD00001000428

Whole Genome Sequencing (WGS) for St. Jude High Grade Glioma (HGG) study

Dataset EGAD00001000806

Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

Dataset EGAD00001000807

Whole exome sequencing of human and mouse sarcoma samples for personalized therapy

Whole exome sequencing of human and mouse sarcoma samples for creation of personalized therapy options. Tissues were sequenced directly; no interventions or alterations were made to the tissue samples

Dataset EGAD00001004885

BLUEPRINT September 2016, ATAC-seq for bone marrow, on Genome GRCh38

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

Dataset EGAD00001002710

Exome sequencing of Non-syndromic Congenital Heart Defects (2019-04-24)

Exome sequencing of ~1,800 patients with non-syndromic Congenical Heart Defects (CHD) to identify genes enriched for damaging rare variants that increase risk of CHD . This dataset contains all the data available for this study on 2019-04-24.

Dataset EGAD00001004975

RNAseq files for Mullighan_GL_reALL RNASEQ2

RNAseq files for Mullighan_GL_reALL RNASEQ2 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005510

RNASeq files for Mullighan_GL_reALL RNASEQ1

RNASeq files for Mullighan_GL_reALL RNASEQ1 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005511

Exome and Targeted sequencing of GZL

Tumor and matching normal exomes for 28 GZL cases (n=56) and targeted capture sequencing for 42 GZL cases with 3 matching normals and 2 pooled normals (n=47)

Dataset EGAD00001006328

Single cell karyotype sequencing of 7 samples from colorectal cancer (CRC) patients

Contains data for all cells sequenced for this study. Data is organized as one bam-file per sample. Individual cells can be identified through the CB tag in the bam-files.

Dataset EGAD00001006438

Data for the genome‐wide association study of cutaneous leishmaniasis in Brazil

DNAs were genotyped on Illumina Infinium HumanCoreExome Beadchips (Illumina Inc., San Diego, CA, USA) with probes for 551,004 single nucleotide variants (SNVs): 282,373 informative across ancestries; 268,631 exome-focused. Human genome build 37 (hg19) was used.

Dataset EGAD00001006681

Reference exome data for a Northern Brazilian population

Here we provide a catalogue of variants called after sequencing the exomes of 45 babies from the State of Rio Grande do Nord in Brazil. Our data set provides a useful reference point for diagnosis of rare diseases in Brazil.

Dataset EGAD00001006407

A95646B

Whole genome sequencing for single cells for library A95646B 507 cells; filetype=bam

Dataset EGAD00001007306

PPIL4 is essential for brain angiogenesis and implicated in intracranial aneurysms in humans

Patients in IA cohort with PPIL4 mutations (Please see Supplementary Table 3 for clinical characteristics of the patients)

Dataset EGAD00001008106

KiCS WGS data for academic use only

Data from samples that are marked for academic use only

Dataset EGAD00001009698

RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

Dataset EGAD00001009799

Transcriptomic data for Human proximal tubular epithelial cell interleukin-1 receptor signalling triggers cell cycle arrest during hypoxic kidney injury

Transcriptomic data for manuscript titled: Human proximal tubular epithelial cell interleukin-1 receptor signalling triggers cell cycle arrest during hypoxic kidney injury.

Dataset EGAD00001015460

CUTRUN files for Klco-NUP98 data

CUTRUN files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia"

Dataset EGAD00001015478

Profiling Chromatin Accessibility in Humans Using Adenine Methylation and Long-Read Sequencing

This dataset includes raw nanopore, base-called, and 6mA frequency data for EcoGII-treated NA12878 and MCF7 chromatin samples. It also includes raw nanopore data for the HG002 EcoGII-treated DNA.

Dataset EGAD00001015374

DNA WGS Long Read Sequence (PromethION) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

Dataset EGAD00001015400

Illumina genome sequencing data for HICF2 craniosynostosis families (Genome Medicine)

BAM files for two families recruited to the HICF2 genome sequencing project due to craniosynostosis. One family is a singleton and the other is an affected mother-daughter duo.

Dataset EGAD00001011373

Dataset for "CutNRun" sequencing of 12 samples of patients with colorectal cancer

This dataset contains 12 "CutNRun" sequencing samples of patients with colorectal cancer. The sequencing was performed on Illumina NextSeq 550 using Cell Signaling TechnologyDNA Library Prep _Kit for Illumina Systems. The sequencing was always paired.

Dataset EGAD00001015694

Thymic epithelial transplantation for complete DiGeorge syndrome Spatial (2026-01-19)

Spatial transcriptome analysis of thymic cells from children with syndromic diseases such as Trisomy 21 and inflammatory/autoimmune diseases such as myasthenia gravis. . This dataset contains all the data available for this study on 2026-01-19.

Dataset EGAD00001015798

Dataset for transcriptome sequencing of chordoma cells

This dataset contains transcriptome sequencing for 15 samples from chordoma cells. The sequencing was performed on Illumina HiSeq 4000 and Illumina NovaSeq 6000. The sequencing was always paired.

Dataset EGAD00001015642

Development of actionable molecular targets and/or biomarkers for prognostication and patient stratification in gynecological cancer based on whole-exome sequencing and epigenomic analysis

We collected 92 endometrial hyperplasia lesions (48 non-atypical from 30 cases and 44 atypical from 24 cases) and matched normal tissues/whole blood. The purpose of this study is to develop actionable molecular targets and/or biomarkers for prognostication and patient stratification.

Study JGAS000642

Emirati Haploid Single-Sample-Assemblies (30 Individuals, 60 Assemblies)

This dataset provides 27 phased diploid genome assemblies for Emirati trios, delivered in FASTA format. Assemblies were built with hifiasm (trio mode) from PacBio HiFi reads at ≥25× coverage for each parent and offspring, then scaffolded with NTLink and reference-guided merging using RagTag against CHM13v2. As part of the same program, a complementary set of single-sample diploid assemblies for 30 individuals (yielding 60 haplotypes) is being generated from deep PacBio HiFi data to expand a population-matched pangenome reference. Together, these resources capture Emirati genomic diversity and support downstream variant discovery and annotation.

Dataset EGAD50000001753

Genetically unique biospecimens derived from individuals with or without Type 1 Diabetes

In this dataset, samples correspond to pools of genetically unique biospecimens derived from individuals with or without Type 1 Diabetes. Each sample alias contains all the DNA test numbers for that pool. Each experiment corresponds to scmxGEX (multiome RNA gene expression), scmxATAC (multiome ATAC sequencing), scRNA (single cell RNA sequencing), scATAC (single cell ATAC sequencing) for each pool. Runs link the appropriate fastq files to each experiment. Deconvolution using genetic information is required for single sample-based testing.

Dataset EGAD50000001257

Development of a rapid and comprehensive genomic profiling test supporting diagnosis and research for gliomas

Targeted sequencing dataset used for the paper entitled "Development of a rapid and comprehensive genomic profiling test supporting diagnosis and research for gliomas". The cohort includes 53 cases of targeted DNA squencing, 15 of them have matched control sequences. The capture panel was made by Agilent SureSelect and the sequence was performed using DNBSEQ or Illumina sequencer.

Dataset EGAD50000000979

RNA-Seq Brest Patient-derived Tumor Organoids

This dataset includes 14 RNASeq samples from 8 patients. For some patients, organoids at different passages have been profiled. They can be identified by their alias, composed of the following structure: <subjectId>_O<organoid_number>_<passage>_RNA. For example, ICSBCS002_O1_1_RNA indicates the earlier passage of organoid 1 for subject ICSBCS002, and ICSBCS002_O1_2_RNA indicates the later passage. Additionally, WCM2137_O1_RNA and WCM2137_O2_RNA indicate two organoids (O1 and O2) derived from different tissues. More information about the passages and tissues can be found in the sample information table.

Dataset EGAD50000000960

BELLINI clinical trial bulk RNA-Seq data: cohorts A, B & С

RNA-Seq data of 78 breast cancer primary tumors obtained from 45 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (15 patients, 25 samples) received nivolumab for 4 weeks, patients in cohort B (15 patients, 28 samples) received nivolumab + ipilimumab for 4 weeks, and patients in cohort C (15 patients, 25 samples) received nivolumab + ipilimumab for 6 weeks. The included raw transcriptome sequencing data in fastq format was generated using Illumina NovaSeq 6000.

Dataset EGAD50000000808

Exploiting evolutionary steering in cancer therapy

This dataset contains 9 bam files of exome sequencing for an experiment of evolved resistance. Here a barcoded cell line (HCC827 - POT) has been treated under high concentrations of gefitinib (GEF) and trametinib (TRM) until resistance has evolved, as well as under control conditions (DMSO). The dataset contains exome sequencing of confluent cells for three replicates for each anti-cancer drug as well as two replicates of growth under DMSO conditions. The original barcoded cell line (POT) was also exome sequenced and is included in the cohort. Sequencing was performed on the Illumina NovaSeq platform.

Dataset EGAD00001005782

BLUEPRINT September 2016, ChIP-Seq for class switched memory B cell from venous blood, on Genome GRCh38

ChIP-Seq data for 1 sample(s) for class switched memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

Dataset EGAD00001002951

BLUEPRINT September 2016, ChIPmentation for effector memory CD8-positive, alpha-beta T cell, terminally differentiated from venous blood, on Genome GRCh38

ChIPmentation data for 1 sample(s) for effector memory CD8-positive, alpha-beta T cell, terminally differentiated from venous blood, on Genome GRCh38. 5 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002943

Transcriptomics of human olfactory mucosa

The olfactory gene repertoire is largely species-specific, shaped by the nature and necessity of chemosensory information for survival in each species' niche. We are intrigued by this interspecific variation and started to investigate the olfactory transcriptome in primates for evidence of selection at the level of receptor gene choice. Having collected this data from two primates, we now wish to extend the analysis to humans. 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/

Dataset EGAD00001003213

Exome sequencing of a cohort of Rett syndromelike patients (2017-08-16)

The aim of the project is the definition of the molecular defect in a cohort of Rett-like patients negative for mutations in known disease genes. To this aim, a number of unrelated trios (patients plus parents) will be analysed by exome sequencing. 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 EGAD00001003564

Molecular and phenotypic data for patients enrolled in the IMmotion150 trial

Tumor transcriptome and whole exome sequencing data (matched tumor/normal for somatic mutation calling) along with key phenotypic information are provided for patients enrolled in the phase 2 IMmotion150 trial, assessing efficacy of atezolizumab monotherapy or combination of atezolizumab and bevacizumab versus standard of care (sunitinib) in 1L renal cell carcinoma. This data set accompanies the respective Nature Medicine publication (PMID: 29867230).

Dataset EGAD00001004183

Comparison of fresh and slow-frozen cancer samples for different applications

Surplus tissues from multiple solid human cancers directly slow-frozen after resection can subsequently be used for different types of methods including the establishment of 2D, 3D, and ex vivo cultures as well as single cell RNA sequencing (scRNAseq) with similar results when compared to freshly analyzed material.

Study EGAS00001005891

Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

Study EGAS00001005066

Oxford Nanopore RNA sequencing for HLA typing

A targeted RNA-based method for typing of 12 classical HLA genes using Oxford Nanopore sequencing. In the method, were enriched HLA genes from cDNA of 50 individuals using gene-specific reverse primers. The library molecules were then barcoded, pooled into 2 separate gene pools, and sequenced on MinION R9.4 SpotON flow cells.

Study EGAS00001004918

MicroRNA profiling by next-generation sequencing for colorectal cancer screening

The study was conducted as the marker discovery phase to identify potential microRNA (miRNA) candidates for colorectal cancer (CRC) screening. Genome-wide profiling with next-generation sequencing (NGS) was performed using plasma samples from 20 newly diagnosed CRC cases and 20 controls free of colorectal neoplasms matched by age and sex.

Study EGAS00001005030

Transcriptome and Exome from longitudinal samples of human glioblastoma

We obtained paired longitudinal specimens from a total of 38 glioblastoma (GBM) patients (34 primary and 4 secondary GBM patients). Treatment-naive initial tumors were available for 35 cases; for the other 3 cases, we used the first available recurrent tumors in lieu of initial tumors. Tumor specimens were subjected to whole-exome sequencing (27 of 38 cases, with the matched normal/blood for 22 of the 27 cases) and transcriptome sequencing (30 of 38 cases).

Dataset EGAD00001001424

PKD1 capture-by-hybridization resequencing for genetic diagnostics of polycystic kidney disease

We established and validated a sequence capture based NGS testing approach for PKD1. The presence of six PKD1 pseudogenes and tremendous allelic heterogeneity make molecular genetic testing of PKD1 variants challenging. In the publication accompaying this dataset (An efficient and comprehensive strategy for genetic diagnostics of polycystic kidney disease, Eisenberger et.al., PLoS one), we demonstrate that the applied standard mapping algorithm specifically aligns reads to the PKD1 locus and overcomes the complication of unspecific capture of pseudogenes. This dataset contains the raw PKD1 reads of all patients from the publication.

Dataset EGAD00001001091

RNA sequencing data for Molecular Characterization of ETMRs

The dataset contains two samples from one patient. As a representative FFPE tissue sample, ET174 was histologically iden- tified, targeted and microdissected with a puncher for nucleic acid extraction. RNA was extracted using the automated Maxwell system with the Maxwell 16 LEV RNA FFPE Kit (Promega), according to the manufacturer’s instructions. To evaluate FFPE RNA quality, we used the percentage of RNA fragments >200 nt fragment determination value (DV200). Only RNA samples with DV200 > 70% were included for sequencing on a NextSeq 500 (Illumina). Eight lanes have been sequenced resulting in 16 Fastq files (paired end).

Dataset EGAD00001006209

scRNA-seq using 10X Genomics platform

Matrices of counts from single-cell RNA-seq data for 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert). Dissociated cells from each tumor sample have been sorted to isolate live cells from the 3 compartments: tumor, immune and stromal. Each of the compartments has been analyzed separately by scRNAseq, excluding some desert tumors for which cells from the stromal and immune compartments have been pooled. Sequencing was performed using 10X Genomics Chromium Single Cell platform (v2 Chemistry).

Dataset EGAD00001006974

cfMeDIP data for 72 VPC samples for validation

We analyzed the cell free DNA methylomes using 72 plasma samples from patients with mCRPC prostate cancer in the VPC project for validation. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology. Files from multiple lanes exists per sample.

Dataset EGAD00001008737

Sequencing data for oesophageal and related samples - Izadi et al (WGS, RNA)

Data supporting: "Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma" Izadi et al. WGS for tumour and normal samples. RNAseq for tumour samples.

Dataset EGAD00001007493

Endometrial Cancer Association Consortium - OncoArray Genotypes

The data come from 9 studies participating in the Endometrial Cancer Association Consortium (ECAC). ECAC data included in this dbGaP submission include OncoArray data from 4486 endometrial cancer cases genotyped at the Center for Inherited Disease Research (CIDR). Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in O'Mara et al, Identification of nine new susceptibility loci for endometrial cancer. Nature Communications (PMID:30093612).

Study phs001885

Pharmacogenomics of Mercaptopurine Intolerance in Children with Acute Lymphoblastic Leukemia (AALL03N1)

Mercaptopurine (MP) is the mainstay of curative therapy for acute lymphoblastic leukemia (ALL). We performed a genome-wide association study (GWAS) to comprehensively identify the genetic basis of MP intolerance in children with ALL in AALL03N1. MP dose intensity was defined as prescribed dose divided by the planned protocol dose during maintenance therapy.  Germline variants in NUDT15 and TPMT were found to be strongly associated with MP intolerance in childhood ALL, which may have implications for treatment individualization in this disease.

Study phs002846

NCT03343197: Clinical Biomarker Data

Patients with IDH1-mutated low-grade glioma were treated with AG-120 (ivosidenib), AG-881 (vorasidenib), or Placebo for 28 days before surgical resection. A portion of the surgical sample was submitted for exome capture-based transcriptome sequencing (Personalis ACE Whole Transcriptome). Following surgery, subjects had the option to continue (or initiate) treatment with AG-120 or AG-881.This dataset comprises next-generation sequencing data from biopsies obtained in the clinical trial: NCT03343197 (Study of AG-120 and AG-881 in Subjects with Low Grade Glioma).

Study phs003148

African American Adolescent Idiopathic Scoliosis Whole Genome and Whole Exome Study

Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. The causes of scoliosis are only now being discovered yet are important for predicting outcome and need for surgery. Prior studies have investigated the causes of scoliosis, including common and rare variant risk factors, but have mostly used populations consisting of Asian or European ancestry. It is essential that we determine what the risk factors are in all populations so that we can delivery equitable care to all individuals.

Study phs003136

Kids First: Genetic Basis of Fetal Alcohol Spectrum Disorders

Fetal Alcohol Spectrum Disorder (FASD) is estimated to occur in at least 1-5% of all children in the USA and is a major public health issue. However, in addition to alcohol, other susceptibility factors, such as maternal or fetal genetic variation, must play a role as not all children prenatally exposed to alcohol are similarly affected. The proposed study will examine the role of genetic susceptibility for FASD. This work will help to inform more effective intervention efforts for this common congenital disorder.

Study phs002594

Segmental Overgrowth/Vascular Anomalies/Dermatologic Disorders

This study was designed to determine the molecular etiology of disorders characterized by segmental overgrowth, vascular anomalies, or dermatologic conditions that are part of the diagnostic criteria for Proteus syndrome or PIK3CA-related overgrowth spectrum (PROS). Somatic variants in AKT1 or PIK3CA have been identified as causative for Proteus syndrome and PROS respectively, and this study aimed to determine the extent of allelic and genetic heterogeneity in individuals who fully met the diagnostic criteria, had some aspects of, or had isolated manifestations of either syndrome.

Study phs002006

Metatranscriptomic Sequencing of Pre-Transplant Bronchoalveolar Lavage in Pediatric Stem Cell Transplant Patients

Children with malignancies, immunodeficiencies, and other life-threatening diseases sometimes receive allogeneic hematopoietic cell transplantation (HCT) as a treatment for their disease. The HCT process can be complicated by the development of lung disease from infection, alloreactivity, or other causes. To identify patients at-risk for post-HCT lung disease, this study uses metatranscriptomic RNA sequencing of bronchoalveolar lavage (BAL) obtained prior to HCT. Sequencing results are associated with the development of post-HCT lung injury. 

Study phs002208

Ontario Familial Colon Cancer Registry Single Nucleotide Polymorphisms and CpG Methylation (OFCCR SNP-CpG)

We profiled the methylation landscape of ~2100 DNA samples (~1100 cases of colorectal cancer and ~1000 controls) from the Ontario Familial Colon Cancer Registry (OFCCR) using the HumanMethylation450 array from Illumina. DNA was extracted from lymphocyte pellets, except for 99 samples for which DNA was extracted from lymphoblastoid cell lines. Samples were genotyped on the Affymetrix Human Mapping 100k and 500k arrays. The aim the study was to evaluate the interplay between genetic variation and methylation, including long-range epigenetic regulation.

Study phs000779

CCG Multicentric Italian Lung Detection (MILD)

For the CCG-MILD project, NCI will utilize whole genome sequencing and/or whole exome sequencing in conjunction with transcriptome sequencing to try to identify recurrent genetic alterations (mutations, deletions, amplifications, rearrangements) and/or gene expression signatures that would be important to the hypothesis(es) submitted by the investigators. The samples will be processed and submitted for genomic characterization using the established NCI Genome Characterization Pipeline. Subsequent genomic and clinical data will be hosted at the NCI Genomic Data Commons (GDC).

Study phs002253

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