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• Genetics of Lymphatic Anomalies from Center of Applied Genomics (CAG) at CHOP

  Lymphatic anomaly, a rare and devastating disease spectrum of mostly unknown etiologies, is characterized by diffuse or multicentric proliferation of dilated lymphatic vessels, and includes a variety of diagnoses: lymphangiectasia, central conducting lymphatic anomaly, generalized lymphatic anomaly, kaposiform lymphangiomatosis, and Gorham Stout disease. Currently, most treatments are considered palliative; lymphatic anomalies are often chronic debilitating conditions that require multiple yearly outpatient visits and hospital admissions for procedures that ameliorate symptoms, but do not correct the underlying cause. Identifying the causal genes will be hugely informative for our understanding of diseases. This will also allow for the development of affordable and successful diagnostic tests and therapies in keeping with "precision medicine" implementation.

  Study phs001802

• Longitudinal Study of the Porphyrias

  This is an observational, longitudinal study of approximately 800 individuals with various types of porphyria. Those participants will be evaluated annually for 5 years, or longer if they agree. Participation in this project will include: Participating in annual visits or contacts. Providing samples, including blood, buccal cells (cells from inside of the mouth), saliva, and urine. The type of samples and amounts may vary from person to person, depending on the type of porphyria. Giving permission for samples to be stored and used for porphyrias research. Granting permission to obtain your medical records. Providing information about your medical history and family history. Completing a questionnaire about your porphyria symptoms and quality of life.

  Study phs001278

• The Diabetes Heart Study (DHS)

  The Diabetes Heart Study is a family based study enriched for type 2 diabetes (T2D). The cohort included 1220 self-reported European Americans from 475 families (Bowden et al 2010 Review of Diabetic Studies 7:188-201: PMID: 21409311; Bowden et al 2008 Annals of Human Genetics 72:598-601 PMID: 18460048) and included siblings concordant for T2D; where possible unaffected siblings were also recruited. The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery and abdominal aorta all determined from non-contrast computed tomography scans.

  Study phs001012

• Sequencing data of tumor tissue obtained from GANNET53 study patients

  The GANNET53 clinical trial evaulated novel treatment options for ovarian cancer patients with platinum-resistant relapse. Archival fresh-frozen paraffin embedded tissue was available from 131 of the 133 enrolled patients. NGS sequencing aimed at assessing the mutational spectrum of key ovarian cancer genes (with a focus on TP53), and their relevance for therapy resistance. From available FFPE samples, DNA was extracted and NGS sequenced using the SureSeq™ Ovarian Cancer Panel and the NGS Library Preparation kit covering all exons of 7 key ovarian cancer genes BRCA1, BRCA2,TP53, PTEN, ATM, ATR, NF1 for single nucleotide variants (SNV) and indels. Finally, sequence data from 118 individual FFPE tumor tissue samples were generated.

  Study EGAS50000000935

• Comparison of WGBS, EPIC array, EM-seq, and Nanopore sequencing in assessing DNA methylation marks

  Bisulfite sequencing has long been the default method for analyzing methylation marks due to its single base resolution. However, the associated DNA degradation poses a concern for fragmented samples. Although several methods have been proposed to circumvent this issue, there has yet to be a clear consensus on which method is best suited for detecting methylation. We present an overview of the two mostly used and two alternative approaches: whole-genome bisulfite sequencing (WGBS), Illumina methylation microarray (EPIC), Enzymatic Methyl-sequencing (EM-seq) and third-generation sequencing by Oxford Nanopore Technologies (ONT). We evaluated DNA methylation levels in three human genomes derived from tissue, cell line, and whole blood.

  Study EGAS00001008014

• bulk RNAseq analysis of tumor from 3 non-muscle-invasive bladder cancer patients

  We performed screenings of patient-specific neo-epitopes by tumor-infiltrating CD8+ T lymphocytes of 4 non-muscle invasive bladder cancer patients. After the tumor resection, these patients went on to receive BCG treatment as they had high-risk disease. In order to select the neo-epitopes, we performed bulk RNAseq of the bladder tumor to select the mutated genes that were expressed in the tumor (TPM >1). For patient UC2, 3 different tumors were resected at the same time and RNA from these 3 tumors were sent separately for RNAseq. For patient UC4, no RNA was available, so this patient is not included in this study.

  Study EGAS50000001383

• Whole_exome_sequencing_for_clarification_of_rare_causes_of_axonal_Charcot_Marie_Tooth_disease_

  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/

  Study EGAS00001002067

• MYOSEQ project

  The MYOSEQ project focuses on the application of next generation sequencing, in particular whole exome sequencing (WES), in a large cohort of patients with unexplained limb‐girdle weakness (LGW). Focusing on undiagnosed patients with a clearly defined clinical phenotype enables increased diagnostic rates for known genes (in particular Pompe disease, GNE related pathologies and other known LGMD subtypes) in this cohort, while the use of WES provides scope both for new gene discovery and for additional research into disease modifiers and genotype‐phenotype correlation with substantial cost effectiveness. The LGW patient cohort was collated by Newcastle University in collaboration with clinical centers across Europe. The sequencing was performed at the Broad Institute and jointly analyzed with Newcastle University.

  Study EGAS00001002069

• TRACERx 100: RRBS data from a subset of the first 100 TRACERx tumours

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). This study looks at multi-region RRBS data from the TRACERx100 cohort selected for quantity of material available and high tumour purity. RRBS data was collected for 122 tumour regions across 36 patients each with matched normal. A subset of this cohort was used in a sister study looking at tumour neo-antigen promoter methylation status in NSCLC (71 tumour regions across 28 patients for a total of 99 samples).

  Study EGAS00001003484

• The European Bank for Induced Pluripotent stem cells (EBiSC) is designed to address the increasing demand by iPSC researchers for quality-controlled, disease-relevant research grade iPSC lines, data and cell services.In this study Whole Genome Sequencing was performed on a selection of lines from the project.

  Induced pluripotent stem (iPS) cells have the potential to significantly advance drug development and health research, yet collections of stem cells are scattered across the world, their quality cannot always be guaranteed, and accessing them is often difficult. The goal of EBiSC is to establish a European iPS cell bank that will be the ‘go-to’ resource for the characterisation, storage and distribution of high quality iPS cells. Ultimately, EBiSC will become an independent organisation, distributing high quality iPS cells on a not-for-profit basis to scientists worldwide.

  Study EGAS00001002755

• Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION-BioLINCC)

  Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.ObjectivesThe HF-ACTION study examined whether exercise training reduces a composite endpoint of all-cause mortality or all-cause hospitalization for patients with left ventricular systolic dysfunction and heart failure symptoms. Background Heart failure (HF) is a major and growing cardiovascular syndrome that is the end result of many cardiovascular disorders. Although evidence-based drug and device therapies decrease mortality, hospitalizations, and HF symptoms and improve quality of life, many patients treated with these regimens often remain burdened by dyspnea and fatigue, diminished exercise tolerance, reduced quality of life, recurrent hospitalizations, and early mortality. Whereas rest was traditionally recommended for HF patients, there has been evidence that physical deconditioning may play a key role in the progression of symptoms and poor outcomes. Previous studies have shown positive effects of exercise training on exercise capacity, quality of life, and biomarkers and suggest that exercise training might improve survival and decrease HF hospitalizations. Nonetheless, there remains a safety concern regarding exercise training in HF and a large scale, multicenter, controlled clinical trial was needed to provide definitive clinical outcome data. Participants A total of 2,331 participants were randomized. 2,130 consented to share data with non-commercial entities, and 1,753 consented to share for commercial purposes. Design All participants underwent baseline cardiopulmonary exercise testing. Test results were reviewed by investigators to identify significant arrhythmias or ischemia that would prevent safe exercise training, to determine appropriate levels of exercise training, and to establish training heart rate ranges. Demographics, socioeconomic status, past medical history, current medications, physical exam, and the most recent laboratory tests were obtained prior to randomization. All participants received detailed self-management educational materials which included information on medications, fluid management, symptom exacerbation, sodium intake, and physical activity. Participants randomized to the exercise training arm first participated in a structured, group-based, supervised exercise program, with a goal of 3 sessions per week for a total of 36 sessions in 3 months. The primary exercises were walking, treadmill, or stationary cycling. Exercise was initiated at 15 to 30 minutes per session at a heart rate corresponding to 60% of heart rate reserve, and was increased after 6 sessions to 30 to 35 minutes duration and 70% of heart rate reserve. Participants began home-based exercise after completing 18 supervised sessions and were to fully transition to home exercise after 36 supervised sessions. The target training regimen for home exercise was 5 times per week for 40 minutes at a heart rate of 60% to 70% of heart rate reserve. Participants randomized to the usual care group were not provided with a formal exercise prescription. To provide comparable levels of attention from study personnel, all participants were called every 2 weeks for the first 9 months, monthly until 24 months of follow-up, and quarterly thereafter. Participants returned for clinic visits every 3 months for the first 2 years of participation and yearly thereafter for up to 4 years. Follow-up assessments included cardiopulmonary exercise testing, a 6-minute walk test, and a physical activity questionnaire. The primary end point was a composite of all-cause mortality or all-cause hospitalization. Secondary end points included all-cause mortality, the composite of cardiovascular mortality or cardiovascular hospitalization, and the composite of cardiovascular mortality or HF hospitalization. Conclusions After adjustment for highly prognostic predictors of the primary end point, exercise training was associated with modestly significant reductions for both all-cause mortality or hospitalization and cardiovascular mortality or heart failure hospitalization.

  Study phs003599

• Polygenic Risk Score for the Prediction of Breast Cancer Is Related to Lesser Terminal Duct Lobular Unit Involution of the Breast

  The Susan G. Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center is an annotated biobank, which has recruited healthy women who provided demographic, lifestyle, and cancer-related information via self-administered questionnaire, blood samples and normal breast tissues. H&E slides of the normal breast tissues were scanned for image analysis and a pathologist measured the number of terminal duct lobular units (TDLUs) ("TDLU count"). The acini count per TDLU was quantified using the TDLU analyzer software. In this analysis, we computed the recently developed polygenic risk score (PRS) based on 313 common variants for the prediction of breast cancer and related this PRS to TDLU count and acini count per TDLU. We did this for the overall PRS, the ER-positive PRS and the ER-negative PRS.

  Study phs002062

• Identification of four new susceptibility loci for testicular germ cell tumour, including variants near GAB2, GSPT1 and ZFPM1

  Genome wide association studies (GWAS) have identified multiple risk loci for testicular germ cell tumour (TGCT), revealing a polygenic model of disease susceptibility strongly influenced by common variation. To identify further SNPs associated with TGCT we conducted a multistage GWAS with a combined dataset of >25,000 individuals (6,059 cases and 19,094 controls). We identified new risk loci for TGCT at 3q23 (rs11705932, TFDP2, P = 1.5 x 10-9), 11q14.1 (rs7107174, GAB2, P = 9.7 x 10-11), 16p13.13 (rs4561483, GSPT1, P = 1.6 x 10-8) and 16q24.2 (rs55637647, ZFPM1, P = 3.4 x 10-9). We additionally present detailed functional analysis of these loci, identifying a statistically significant relationship between rs4561483 risk genotype and increased GSPT1 expression in TGCT patient samples. These findings provide additional support for a polygenic model of TGCT risk and further insight into the biological basis of disease development.

  Study EGAS00001001302

• ENOC WGS for the study Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

  For ENOC cohorts, OvCaRe cases were reviewed, including frozen material, by at least two expert gynecopathologists prior to inclusion in the sequencing cohort who provided the confirmation on final selected cohort. Frozen H&E from Tokyo were also used for evaluation along with representative H&E photos and review done at the Jikei School of Medicine. For ENOC, DAH985 and DG1288 are recurrent and both were treated with chemotherapy after their first surgery. DAH123 is a untreated sample, metastasis from an primary endometrial tumour. All HGSC, GCT, CCOC and the rest ENOC tumours are primary tumour samples. Library construction and sequencing Frozen specimens with >50% tumour cellularity (based on initial slide review) were used for cryosectioning and subsequent nucleic acid extraction. Patient tumour and normal blood samples derived from primary, untreated fresh frozen tumour specimens harvested at diagnosis during standard of care debulking surgery. Germline DNA was provided from peripheral blood buffy coat on all specimens except 13 from Tokyo, where non-cancer frozen tissue was used as a germline source. DNA extraction from both matched normal (blood) and tumour samples (frozen tissue) were performed using the QIAamp Blood and Tissue DNA kit (Qiagen) and quantified using a Qbit fluorometer and reagents (high-sensitivity assay). Three lanes of Illumina HiSeq 2500 v4 chemistry for normal samples and five lanes for tumour samples were obtained. The PCR-free protocol was adopted to eliminate the PCR-induced bias and improve coverage across the genome.

  Dataset EGAD00001003266

• Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare and lethal tumor in adolescent and young adult patients. Currently, there is no standard-of-care treatment for these patients. Reliable models that represent this disease and can be used for translational research are scarce. To model SCCOHTs, we have established eight patient-derived tumoroid lines from tumor lesions of three patients with SCCOHT. The tumoroids recapitulate genomic and transcriptomic characteristics of the corresponding patient tumors and capture intrapatient tumor heterogeneity. Organoid drug profiling using a library of 153 clinical compounds identified methotrexate as an effective and selective drug against SCCOHTs with a clinically relevant IC50 of 35 nmol/L. RNA sequencing demonstrated that methotrexate induced TP53 pathway activation and apoptosis. These data underscore that organoid technology can support the design of therapeutic strategies for rare cancers.

  Study EGAS00001007911

• An exome sequencing approach to defining the genetic risk factors for Achilles tendinopathy

  Musculoskeletal soft tissue injuries are complex phenotypes. Case control association studies using the candidate gene approach have predominantly been used to identify risk loci for these injuries. However, the ability to identify all risk conferring variants using this approach alone is unlikely. Therefore, this study aimed to define the genetic profile of these injuries using whole exome sequencing and a customized analysis pipeline. The exomes of ten exemplar asymptomatic controls and ten exemplar cases with Achilles tendinopathy were individually sequenced using a platform that included the coverage of the untranslated regions and miRBase miRNA genes. These results provide a proof of concept for the use of a customized pipeline for the exploration of a larger genomic dataset. This approach, using previous research to guide a targeted analysis of the data has generated new genetic signatures in the biology of musculoskeletal soft tissue injuries.

  Study EGAS00001003234

• Dataset for CD8-Positive lymphocyte samples

  This dataset contains scRNA sequencing data for CD8-Positive lymphocytes samples. Sequencing was performed on a Illumina NextSeq 550. The sequencing was always paired.

  Dataset EGAD50000000092

• WES data from patient samples at the stage of NDMM and EMM and normal samples

  This contains the raw Whole Exome sequencing data used for the publication

  Study EGAS50000000036

• RNA-seq dataset for gamma delta (γδ) T-ALL patients

  RNA-seq data for 85 patients with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL)

  Dataset EGAD50000000027

• Bulk RNAseq of patient samlpes at the stage of NDMM, RRMM without EMM and EMM

  This study contains the raw bulk RNAseq data used for the publication

  Study EGAS50000000035

• Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Dataset EGAD00010002682

• EARLY DIAgnosis of PAncreatic Cancer (EARLY DIAPAC) study

  Whole genome sequencing of pancreatic cyst fluid for early detection and diagnosis of pancreatic cancer.

  Study EGAS50000000611

• Helse Bergen HF Data Access Committee for the MetBreCS trial dataset submitted to Federated EGA Norway

  This Data Access Committee is appointed by Helse Bergen HF to administer access requests for the MetBreCS trial dataset submitted to Federated EGA Norway.

  Dac EGAC50000000523

• DAC for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Data access comittee for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Dac EGAC50000000650

• Genomic sequencing data for PNG15 and PNG16

  This data set contains genomic sequencing data and variant calls for PNG15 and PNG16.

  Dataset EGAD50000001598

• shallow Whole-Genome sequencing of 14 TNBC tumor in the MATADOR trial - for in silico spike-in experiment

  14 TNBC tumors with tumor percentage ~90% were selected for in silico spike-in experiment

  Dataset EGAD50000001863

• scRNAseq dataset of vitligo dermis and epidermis

  scRNAseq dataset of vitligo dermis and epidermis for 6 patients. For each patient nonlesional and perilesional skin were sampled and processed separately.

  Dataset EGAD50000001874

• NAR-GAB 2025 deposit data

  Human exome gVCFs: rare-disease cohort for the NAR-GAB 2025 study on splicing-SNV prioritization.

  Study EGAS50000001456

• HICHIP_TALL_t_14_16_translocation

  For patient P01, HiChIP experiment for was performed using the Arima-HiC+ kit (A510008, Arima genomics) according to the manufacturer’s protocols.

  Dataset EGAD50000002167

• V4_panel_bait_design_test

  Targeted gene screen of FFPEs, cell lines and primary tumours for testing the new V4 Cancer gene panel.

  Study EGAS00001001808

• Myeloma_Follow_up_Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Study EGAS00001000743

• WXS files for Mullighan BiTE WXS

  WXS files for Mullighan BiTE WXS paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005730

• RNASeq files for Mullighan Leventaki ALCL Project

  RNASeq files for Mullighan Leventaki ALCL Project paper titled "Integrative molecular analysis of pediatric Anaplastic large cell lymphoma reveals subtypes with distinct immune suppression signatures."

  Dataset EGAD00001005951

• RNAseq files for Mullighan BiTE RNASEQ1

  RNAseq files for Mullighan BiTE RNASEQ1 paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005731

• Brain mets discovery cohort whole-exome sequencing raw sequencing files

  These are the raw sequencing files for the 50 brain tumour, 3 extracranial tumour and 34 matched normals for the patients in the discovery cohort.

  Dataset EGAD00001005981

• WGS files for Millighan BiTE WGS

  WGS files for Mullighan BiTE WGS paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005729

• Mucoepidermoid Carcinoma

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001003958

• Primary Neuroblastoma Circle-seq

  We generated Circle-seq data for primary neuroblastoma to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004797

• Res1_PC9_exp2_MC_01_04_22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006170

• Res1_PC9_exp1_MC_29_03_22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006169

• Res1_H23_exp2_MC_13_07_22

  8 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006683

• Whole-genome sequencing data for 449 Nigerian individuals

  Whole-genome sequencing data in the form of multi-sample, per-chromosome VCFs for n=449 individuals across 47 unique ethnolinguistic groups.

  Dataset EGAD00001010095

• WES for Patient 9 to 14 of NIBIT-M4 clinical trial

  WES for Patient 9 to 14 of NIBIT-M4 clinical trial

  Dataset EGAD00001009700

• A95724A

  Whole genome sequencing for single cells for library A95724A 503 samples; filetype=bam

  Dataset EGAD00001008229

• Additional WGS files for Genomic Landscape ALL paper

  Additional WGS files for Genomic Landscape ALL paper titled "The genomic landscape of pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001010270

• WGS files for Klco-NUP98 data

  WGS files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015443

• WXS files for Klco-NUP98 data

  WXS files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015444

• RNASeq files for Klco-NUP98 data

  RNASeq files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015445

• scRNASeq files for Klco-NUP98 data

  scRNASeq files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015479

• Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Dataset EGAD00001011994

• neoALTTO

  RNAseq fastq files for 254 samples for the neoALTTO study of lapatinib, trastuzumab or combination in HER2+ breast cancer patients. Those are pre-treatment baseline samples.

  Dataset EGAD00001011354

• Targeted sequencing using SPET for Mesothelioma.

  Targeted sequencing using SPET for Mesothelioma.

  Dataset EGAD00001001916

• Mucoepidermoid carcinoma- normals

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001004946

• MT amplicon sequencing reads of 217 Egyptian individuals

  This data set contains for 217 Egyptian individuals the amplicon sequencing reads mapping to chrM. These were subsequently used for haplogroup assignment.

  Dataset EGAD00001006040

• Genomic Data Archive From the Network for Pancreatic Organ Donors With Diabetes

  The Network for Pancreatic Organ Donors with Diabetes (nPOD) is the largest biorepository of human pancreata from organ donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, and islet autoantibody positive (AAb+)/pre-T1D. The mission of the nPOD is to distribute biospecimens and associated de-identified data/metadata to an international researcher network, and to promote the development of new treatments for these diabetes conditions. Here, we describe the release of high-parameter genotyping data for the nPOD cohort. Specifically, 372 subjects were genotyped using a customized precision medicine single nucleotide polymorphism (SNP) microarray (UFDIchip). These data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 subjects were queried for rare known and novel coding region variants via whole exome sequencing (WES). These data are now publicly available, enabling genotype-selected sample requests and the study of novel genotype : phenotype associations, ultimately to explain diabetes heterogeneity and inform precision medicine strategies to interrupt diabetes pathogenesis.

  Study phs002861

• HTAN Pilot Project: Single-Cell Transcriptomics Toolbox for Fresh and Frozen Human Tumors (Lung, Breast, Ovarian, Melanoma, Neuroblastoma, Sarcoma, Glioblastoma, Glioma, and Leukemia)

  Single cell transcriptomics is a powerful tool to map the complex tumor microenvironment, providing unprecedented resolution into cell types, cell states, cell interactions, and tumor heterogeneity. Depending on their tissue site and whether processing begins from a fresh or frozen sample, different tumors require different optimizations in order to obtain high quality single cell transcriptomic data. In this study, we profiled a range of tumor types, varying in cell-of-origin, solid and non-solid forms, patient ages, and transitions. The tumors also further varied in their tissue site and in their sample collection method. To enable profiling of such diverse samples, we developed a systematic toolbox for single cell RNA-Seq and single nucleus RNA-Seq of fresh and frozen clinical tumor samples. We validated this toolbox for 216,490 cells and nuclei extracted from 39 samples across 23 tumors (some tumors were split into multiple samples). The 23 tumors represented eight unique tumor types. This toolbox comprises both experimental and computational protocols as well as guidelines for comparing and selecting protocols for the biological problem of interest.

  Study phs001983

• Ultra-Low-Pass Whole Genome Sequencing of Cell-Free DNA for Large B-Cell Lymphoma

  While deep targeted DNA sequencing of liquid biopsies has shown prognostic utility in large B-cell lymphoma (LBCL), the routine clinical adoption of these assays remains limited due to their high costs. Here, leveraging a well-annotated cohort of encompassing both frontline and relapsed/refractory (R/R) LBCL, we profiled patient plasma samples with two complementary modalities – ultra-low-pass whole genome sequencing (ulpWGS) and deep targeted DNA sequencing, the former being a cost-effective method to profile large scale chromosomal abnormalities and estimate tumor burden. Our findings revealed a strong association of high cell-free tumor burden by both genomic profiling modalities with established measures of tumor burden and patient survival. Notably, the associations with survival remained statistically significant after accounting for international prognostic index scoring. Furthermore, we showed that del(17p) in circulating tumor DNA as detected by ulpWGS was strongly associated with TP53 mutation status and predicted for significantly inferior patient outcome in frontline but not R/R LBCL patients. Our study demonstrates that ulpWGS can provide robust prognostic biomarkers for both frontline and R/R LBCL, highlighting its broad applicability for risk stratification.

  Study EGAS50000001027

• Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression

  Immunotherapy with chimeric antigen receptor T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify cancer specific exon targets, we analyze 1,532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We find 2,933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n=148) or the alternatively spliced isoform (n=9) level. Expression of selected alternatively spliced targets, including the EDB domain of fibronectin 1, and gene targets, such as COL11A1, are validated in pediatric patient derived xenograft tumors. We generate T cells expressing chimeric antigen receptors specific for the EDB domain or COL11A1 and demonstrate that these have antitumor activity. The full target list, explorable via an interactive web portal (https://cseminer.stjude.org/), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.

  Study EGAS00001007766

• Rapid Whole Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units

  Monogenic diseases are frequent causes of neonatal morbidity and mortality, and disease presentations are often undifferentiated at birth. More than 3,500 monogenic diseases have been characterized, but clinical testing is available for only some of them and many feature clinical and genetic heterogeneity. As such, an immense unmet need exists for improved molecular diagnosis in infants. Because disease progression is extremely rapid, albeit heterogeneous, in newborns, molecular diagnoses must occur quickly to be relevant for clinical decision-making. We describe 50-hour differential diagnosis of genetic disorders by whole-genome sequencing (WGS) that features automated bioinformatic analysis and is intended to be a prototype for use in neonatal intensive care units. Retrospective 50-hour WGS identified known molecular diagnoses in two children. Prospective WGS disclosed potential molecular diagnosis of a severe GJB2-related skin disease in one neonate; BRAT1-related lethal neonatal rigidity and multifocal seizure syndrome in another infant, identified BCL9L as a novel, recessive visceral heterotaxy gene (HTX6) in a pedigree, and ruled out known candidate genes in one infants. Sequencing of parents or affected siblings expedited the identification of disease gene in prospective cases. Thus, rapid WGS can potentially broaden and foreshorten differential diagnosis, resulting in fewer empirical treatments and faster progression to genetic and prognostic counseling. Reprinted from Saunders et. al, Rapid Whole-Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units. Sci. Transl. Med. 4, 154ra135 (2012; PMID: 23035047) with permission from AAAS.

  Study phs000564

• Reference Standards for Mosaic Variant Detection

  After conception, postzygotic mutations continuously occur throughout life in humans, causing somatic mosaicism in an individual. The variant type, time of origination, and locations of the mosaic mutations result in unique mosaic patterns in a combinatorial manner and further affect phenotypes, including various noncancerous diseases. Several efforts have, thus, been made to identify the mutational landscape and mechanisms underlying the mosaic mutations. From a technical aspect, the accurate detection of mutations is at the core of the mosaicism research, and the construction of a standard reference is a critical first step to serve as the basis for analytical validation and benchmarks for germline and somatic mutation detection. Furthermore, a reference standard for mosaic mutations is urgently needed to enable more advanced research.Herein, we generated robust, large-scale, and cell line mixture-based reference standards that contain abundant mosaic SNVs and INDELs along with wild-type sites and germ line variants. Moreover, the whole reference standard set mimics the cumulative aspect of mosaic variant acquisition in the early developmental stage through a progressive cell line mixing with confirmed genotypes. It can be used for optimizing the current use of mosaic variant detection strategies, as well as developing algorithms for future improvements.We previously generated an NCBI BioProject (PRJNA758606) to release much of these data. Only the data that are subject to authorized access constraints have been included in this submission to dbGaP. The two data sources are thus, complementary to each other.

  Study phs003399

• Preclinical Pediatric Molecular Analysis for Therapy Choice (MATCH)

  Purpose: Pediatric solid tumors arise from diverse tissues during development and exhibit a wide range of molecular, cellular and genetic features. This diversity, combined with the low incidence of pediatric cancer makes it increasingly difficult to personalize therapy for individual patients based on the unique features of their tumors. Therefore, well-credentialed preclinical models that capture the diversity and heterogeneity of pediatric solid tumors are essential for identifying molecular targeted therapeutics for precision medicine. Experimental Design: Here, we report 281 orthotopic patient derived xenografts (O-PDXs) from 224 patients representing 24 different types of pediatric solid tumors. We have performed genomic characterization of the O-PDXs and compared them to their corresponding patient tumors. To demonstrate the feasibility and utility of using such a diverse collection of O-PDXs in preclinical studies, we performed a preclinical pediatric precision medicine trial based on the NCI-COG Pediatric MATCH trial enrollment criteria. We also tested molecular targeted therapy for a novel oncogenic fusion recently reported in pediatric melanoma and precision drug delivery using nano-liposomal irinotecan. Results: In the preclinical match study, we identified one specific single agent response to LY3023414 in an osteosarcoma model with a TSC2 variant of unknown significance. Combinations of nano-liposomal irinotecan were effective in treating both Ewing sarcoma and rhabdomyosarcoma xenografts. Conclusion: Our studies demonstrate the value of large, well-credentialed preclinical models for future precision medicine in pediatric oncology using single agents, drug combinations and novel drug formulations.

  Study EGAS00001008011

• Platelet RNAseq data for SLFN14 K219N patients

  Pathogenic missense variants in SLFN14, which encodes an RNA endoribonuclease protein that regulates rRNA degradation, are known to cause inherited thrombocytopenia with impaired platelet aggregation and ATP secretion. Despite rather mild laboratory defects, these patients display an obvious bleeding phenotype. The function of SLFN14 in megakaryocyte (MK) and platelet biology is unknown. This study aims to characterize the platelet transcriptome in patients with a SLFN14 K219N variant and model the disease in the immortalized megakaryocyte cell line imMKCL. Total platelet RNA was sequenced for two patients and 19 healthy controls. Differential gene expression analysis yielded a total of 2999 and 2888 significantly (|log2FC|>1, FDR<0.05) up- and downregulated genes, respectively. Remarkably, these downregulated genes were not enriched for any biological pathway while upregulated genes were enriched for pathways involved in (mitochondrial) translation and transcription with a significant upregulation of 134 ribosomal protein genes (RPG). Heterozygous and homozygous SLFN14 K219N imMKCL showed a defect in MK differentiation that aggravated during cell passaging of undifferentiated cells and in proplatelet formation. SLFN14 defective platelets and MK showed signs of rRNA degradation while this was absent in undifferentiated imMKCL cells. Upregulation of RPG through increased mTOR signaling in SLFN14 K219N MK seems to be a compensatory response for rRNA degradation. Indeed, mTOR inhibition with rapamycin resulted in further enhanced rRNA degradation in SLFN14 K219N MK. Taken together, our study indicates dysregulation of mTOR-regulated ribosomal biogenesis as the disease mechanism for SLFN14-related thrombocytopenia.

  Study EGAS00001006339

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Study EGAS00001003661

• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  Background Despite advances in identification of genetic markers associated to severe COVID-19, the full genetic characterisation of the disease remains elusive. Imputation of low-coverage whole genome sequencing (lcWGS) has emerged as a competitive method to study such disease-related genetic markers as they enable genotyping of most common genetic variants used for genome wide association studies. This study aims at exploring the potential use of imputation in lcWGS for a highly selected severe COVID-19 patient cohort. Findings We generated an imputed dataset of 79 variant call format (VCF) patient files using the GLIMPSE1 tool, each containing, on average, 9.5 million single nucleotide variants. The validation assessment of imputation accuracy yielded a squared Pearson correlation of approximately 0.97 across sequencing platforms, showing that GLIMPSE1 can be used to confidently impute variants with minor allele frequency up to approximately 2% in Spanish ancestry individuals. We conducted a comprehensive analysis on the patient cohort, examining hospitalisation and intensive care utilisation, sex and age-based differences, and clinical phenotypes using a standardised set of medical terms specifically developed to characterise severe COVID-19 symptoms for this cohort. Conclusion This dataset highlights the utility and accuracy of lcWGS imputation in the study of COVID-19 severity, setting a precedent for other applications in resource-constrained environments. The methods and findings presented here may be leveraged in future genomic projects, providing vital insights for health challenges like COVID-19.

  Study EGAS00001007573

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• Privacy Notice for the Account User

  Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Username and password (to authenticate access to the system) IP Address (for anonymous usage statistics) We process your personal data: to provide you with the authenticated access to the EGA service (opening and managing submission and distribution account), to publicly publish some aggregate data to facilitate scientific research (e.g. number of accounts, geographic distribution), to better understand the needs of the users and to guide future improvements of the service, to create anonymous usage statistics. If you do not provide us with your personal data we will not be able to open the user account and offer you our services or we will only provide you a subset of functionalities available within the service. 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), Requested dataset Data access committee – DAC will have access to the name, email, organization, affiliation, title/position of the distribution user account, using it for their own purpose of granting access to their datasets. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Distribution user account data are in the process of granting access disclosed to dataset(s) DAC, which might be a recipient in countries outside of the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI) is necessary for important reasons of public interest embedded in the aims of the EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union. 6. How long do we keep your personal data? All data are stored for as long as you have the account open. Thereafter the storage is prolonged for as long as our service is live, even if you stop using our services. This prolongation is necessary for further scientific research, to ensure legal compliance and security and to facilitate internal and external audits it they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-user-account

• Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Sequence reads for pediatric GBM samples for manuscript: Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Dataset EGAD00001000134

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD50000000201

• Cancer Registry of Norway - NIPH Data Access Committee for CRCbiome datasets

  The Cancer Registry of Norway - NIPH appointed Data Access Committee for the CRCbiome datasets - The microbiome as a colorectal cancer screening biomarker. https://www.mn.uio.no/sbi/english/groups/rounge-group/crcbiome/.

  Dac EGAC50000000121

• WGS dataset for gamma delta (γδ) T-ALL patients

  Whole genome sequencing data for 61 samples with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL) and 29 germline samples

  Dataset EGAD50000000028

• RNA-seq data for genomic determinants of response and resistance to inotuzumab in B-ALL

  RNA-seq data for 101 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000095

• WTCCC2 Schizophrenia study

  A WTCCC2 project genome-wide case-control association study for schizophrenia (SP) in individuals from Ireland.

  Study EGAS00000000118

• DAC for "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling"

  This is the DAC for the study "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling" of PD Dr. Aurélie Ernst (a.ernst@dkfz.de) B420, DKFZ.

  Dac EGAC50000000452

• Massachusetts General Hospital Cancer Center DAC for high-throughput microfluidic enrichment from whole leukopak for CTC-based liquid biopsy

  Whole genome sequencing and whole exome sequencing data of circulating tumor cells isolated from patients with metastatic prostate cancer and liver cancer.

  Dac EGAC50000000423

• Akershus University Hospital Data Access Committee for Immunoglobulin Heavy-Chain locus in Multiple Sclerosis datasets in FEGA Norway

  This is the Data Access Committee appointed by Akershus University Hospital (AHUS) for datasets from Immunoglobulin Heavy-Chain locus in Multiple Sclerosis studies.

  Dac EGAC50000000659

• 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

• Targeted Capture DNA Sequencing

  We performed targeted capture DNA sequencing for 29 genes in extranodal NK/T-cell lymphoma, nasal type (n=67).

  Study JGAS000548

• ONT and PacBio data of 22q11 patient-parent duos/trios

  ONT and PacBio FASTQ files generated for de novo assembly and resulting de novo assemblies

  Study EGAS50000001647

• Sequencing data for Murtaza et al. Nature Communications 2015 (doi:10.1038/ncomms9760)

  Exome and targeted amplicon sequencing data for tumor, germline and plasma samples from a patient with metastatic breast cancer.

  Dataset EGAD00001002108

• MT sequencing reads from WGS of 10 Egyptian individuals

  This data set contains for 10 Egyptian individuals the WGS reads mapping to chrM. These were subsequently used for haplogroup assignment.

  Dataset EGAD00001006038

• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327

• lowinput RNASEQ files for Mullighan BiTE RNASEQ2

  lowinput RNASEQ files for Mullighan BiTE RNASEQ2 paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005732

• A96178A

  Whole genome sequencing for single cells for library A96178A 788 cells; filetype=bam

  Dataset EGAD00001007115

• Bam files for the whole exome sequencing from the study on Spatial homogeneity in pediatric brain tumors.

  Bam files for the whole exome sequencing from the study on Spatial homogeneity in pediatric brain tumors.

  Dataset EGAD00001001055

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006325

• Severe acne GWAS meta-analysis

  Summary statistics of a GWAS meta-analysis for severe acne. A total of 7,441,713 genotyped and imputed variants were used for 5,602 European severe acne cases and 21,120 matched population controls.

  Dataset EGAD00001004419

• RNA-Seq for PTPN1 project (EGAS00001000554)

  Fastq files corresponding to RNA-Seq dataset for PTPN1 project (EGAS00001000554)

  Dataset EGAD00001001646

• ChIP-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  ChIP-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003432

• WGS files for double minute brain tumor paper.

  Whole Genome Sequencing files accompanying the paper titled "Structure and evolution of double minutes in diagnosis and relapse brain tumors". Please read the paper for more details.

  Dataset EGAD00001004337

• A96233A

  Whole genome sequencing for single cells for library A96233A 637 cells; filetype=bam

  Dataset EGAD00001007622

• A98293B

  Whole genome sequencing for single cells for library A98293B 703 samples; filetype=bam

  Dataset EGAD00001008265

• A108735A

  Whole genome sequencing for single cells for library A108735A 714 cells; filetype=bam

  Dataset EGAD00001007593

• A98176B

  Whole genome sequencing for single cells for library A98176B 1389 samples; filetype=bam

  Dataset EGAD00001008261

• Additional RNASeq files for Roussel MBPRP

  Additional RNASeq files for Roussel paper titled "Combination of CDK4/6 with BET-bromodomain and PI3K/mTOR inhibitors in medulloblastoma in vitro and in vivo"

  Dataset EGAD00001009394

• WES for Patient 1 to 8 of NIBIT-M4 clinical trial

  WES for Patient 1 to 8 of NIBIT-M4 clinical trial

  Dataset EGAD00001009701

• consHLA extra samples for comparison with clinical HLA types

  Samples not in other datasets for the paper titled; consHLA: a Next Generation Sequencing Consensus-based HLA Typing Workflow

  Dataset EGAD00001015625

• A96172A

  Whole genome sequencing for single cells for library A96172A 1476 samples; filetype=bam

  Dataset EGAD00001008240

• A98294A

  Whole genome sequencing for single cells for library A98294A 994 samples; filetype=bam

  Dataset EGAD00001008266

• A95730A

  Whole genome sequencing for single cells for library A95730A 739 cells; filetype=bam

  Dataset EGAD00001007614

• A95724B

  Whole genome sequencing for single cells for library A95724B 581 samples; filetype=bam

  Dataset EGAD00001008230