1436 results for "fut 26 credit Visitez le site Buyfc26coins.com Support réactif et efficace pour mes FC 26 coins.Hxz1"

in 26.77 milliseconds.

• Paired-end RNA-Seq Dataset of 72 Brain Organoid Samples: Sequencing and Gene Expression Analysis

  72 fastq sequencing files of 72 brain-organoid paired-end sequenced samples (R1/R2). RNA sequencing libraries were prepared using the NEBNext Ultra II RNA Library Prep Kit for Illumina following the manufacturer’s instructions (New England Biolabs, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End configuration (ver. 1.5) on an Illumina NovaSeq 6000 The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014) (file: "All_Counts_final.xlsx") For more information, see "Study Description"

  Dataset EGAD50000000935

• Synchronous patterning of hiPSC-derived CNS progenitors generates comprehensive axial spinal cord organoids (CASCOs) containing diverse motor neuron population

  Dataset includes scRNA-sequencing data of cells isolated by dissociation of ~20 BJ WT day 20 hiPSC-derived MN embryoid bodies generated in ULA 96w plates following the protocol described in Rodriguez-Muela et al., JCI 2018). Droplet-based scRNA-seq was performed using 10X Genomics scRNA-sequencing was performed using 10X Genomics Chromium Single Cell Kit v3. The resulting sequencing reads were processed as described in Buchner et al 2024. Analysis of the count matrices was performed using the R toolkit for single cell genomics, Seurat v5.1.0, with R v3.3.3 “Angel Food Cake.”

  Dataset EGAD50000001301

• Shallow whole genome sequencing of ctDNA samples from DETECT study

  A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival from the paper "A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival", by Beddowes et al. Mol.Onc.

  Study EGAS50000000911

• Capture Hi-C on MM

  In situ promoter capture Hi-C on multiple myeloma cell line KMS11 in experimental triplicates. Hi-C libraries were prepared as previously described (Rao et al., 2014, http://dx.doi.org/10.1016/j.cell.2014.11.021). Promoter capture was based on 32,313 biotinylated 120-mer RNA baits (Agilent). Hi-C libraries were sequenced using Illumina HiSeq 2000 technology. The files are in FASTQ format.

  Study EGAS00001002614

• Chronic myelomonocytic leukemia

  Chronic myelomonocytic leukemia is an aggressive hematological malignancy with dismal outcomes, with the pCMML subtype in particular having median OS of <2 years and high rates of AML transformation (Patnaik et al., 2014). Given limited therapeutic options for affected patients, we carried out this study to define the genetic and epigenetic landscape of pCMML and identify therapies that could modify disease biology.

  Study EGAS00001005107

• Sequencing data associated with Smith et al, Acta Neuropathologica, 2020 (PMID: 32519082)

  The dataset includes 144 BAM files of WGS, WES, and RNA-seq data from primary and PDOX samples analyzed in Smith et al, Acta Neuropathologica, 2020 (PMID: 32519082).

  Dataset EGAD00001007980

• Knoll et al Identification of drug candidates targeting monocyte reprogramming in people living with HIV PBMC drug in vitro

  PBMC RNAseq drug in vitro

  Dataset EGAD50000000070

• Walter and Eliza Hall Institute - University of Melbourne

  Data Access Committee for Gocuk, Lancaster et al. 2024: nanopore sequencing data of patients with choroideremia and X-linked retinitis pigmentosa, to determine X inactivation skew.

  Dac EGAC50000000301

• Human embryonic stem cells dopaminergic neurons

  These are two biological replicates at timepoint day 17 and day 28 of dopaminergic neuron differentiation of human embryonic stem cells. Ásgrimsdottir et al. (Arenas Lab, Karolinska Institutet)

  Dac EGAC50000000652

• Ethiopia_Genome_Project_and_Egyptian_low_coverage_vcf

  Integrated callset of low coverage Ethiopian and Egyptian genomes from the Pagani et al. 2015 AJHG paper (doi: http://dx.doi.org/10.1016/j.ajhg.2015.04.019)

  Dataset EGAD00001003296

• Therapeutic Targeting of ATR Yields Durable Regressions in High Replication Stress Tumors

  Patients with relapsed or recurrent small cell lung cancer or extra-pulmonary small cell cancers were enrolled on an investigator-initiated, single-arm, phase 2 trial (NCT02487095) combining an ATR inhibitor M6620 (VX-970, berzosertib) administered at 210 mg/m2 intravenously over 60 minutes on day 2 and day 5, and topotecan 1.25 mg/m2 intravenously over 30 minutes every 23 hours on days 1 through 5, with a support of pegfilgrastim 6mg subcutaneously on day 6 in 21-day cycles. Tumor samples were collected either just before starting the treatment or before starting treatment prior to be enrolled in the trial. Whole exome and RNA were sequenced to evaluate genomic and transcriptomic characteristics associated with the response to the combination treatment.

  Study phs002327

• Germline variants in UHRF1 are associated with multi-locus imprinting disturbance in humans and mice

  Genomic imprinting provides is an epigenetic process crucial for normal development and is disrupted in congenital imprinting disorders(CIDs). There is great interest in the clinical consequences and aetiology of multilocus imprinting disturbance(MLID) which occurs in some individuals with CID, though the cause of MLID is unknown in most cases. We investigated a kindred with a CID and MLID and identified a rare genetic variant in the UHRF1 gene which has a critical role in the establishment and maintenance of DNA methylation. We generated a mouse model and found that the equivalent Uhrf1 variant was associated with prenatal lethality and disruption of normal imprinting mechanisms. These findings support UHRF1 as a novel candidate gene for CIDs with MLID.

  Study EGAS50000001179

• Assessing the suitability of formalin-fixed paraffin-embedded (FFPE) tissue for genome-wide association studies (GWAS)

  This study evaluates the feasibility of conducting genome-wide association studies (GWAS) using DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue. Genotyping results from paired FFPE and blood samples were compared using both microarray technology and low-coverage whole-genome sequencing (lcWGS). The analysis demonstrated high concordance between FFPE- and blood-derived genotypes. Although both platforms performed well, microarrays achieved significantly higher recall and precision and currently offer greater cost-effectiveness and computational efficiency. These findings support the suitability of FFPE-derived DNA for GWAS, with microarrays representing the preferred approach at present. However, the broader variant detection enabled by lcWGS may represent an additional advantage to be explored in future studies, particularly in diverse populations.

  Study EGAS00001008103

• Epidemiological study comparing rates and risk factors for dementia in African Americans in Indianapolis and Yoruba living in Ibadan, Nigeria

  In 1991 collaboration between researchers at Indiana University School of Medicine and the University of Ibadan, Ibadan, Nigeria established the Indianapolis-Ibadan Dementia Project. It is a longitudinal, prospective population-based comparative epidemiological study of the prevalence and incidence rates and risk factors of Alzheimer's disease and other age associated dementias. The project compares samples of community-dwelling elderly (age > 70 years) African Americans living in Indianapolis to Yoruba living in Ibadan, Nigeria, employing the same research design, methods, and investigators. It initially reported significantly lower prevalence rates of disorders in the Yoruba compared to the African Americans. In subsequent waves of the study (1994-1995, 1997-1998) incidence rates, rates of newly diagnosed cases, were also found to be significantly lower in the Yoruba. In genetic studies, the frequency of the APOE 4 allele was about the same in the two groups. APOE 4 was a significant risk factor for Alzheimer's disease and dementia in the Americans, while no association was found for the Yoruba. The APOE 2 allele appears to be protective in the Americans, but not the Yoruba. A constellation of factors often associated with vascular risk including a history of hypertension, diabetes, and high cholesterol levels is less common in the Yoruba than in the American group. An interaction was observed between cholesterol, APOE genotype and Alzheimer's disease in both study groups. In 2001-2002 survivors of the original cohort were once again evaluated (N~800 in each site) and 2,000 additional individuals age 70 years and older were enrolled in each site. Blood samples were collected from approximately 1,500 study participants in each site for genetic studies and analysis of biochemical risk factors for vascular disease. Subsequent waves of field work were conducted in 2004, 2007, 2009, and 2011. This fieldwork followed the classic two-stage study design. The study design involves an in-home screening interview with the study participant, which includes a cognitive assessment, medical history and current medications, brief neurological examination, height and weight, blood pressure measurement and assessment of social involvement. There is also a screening interview with a close relative of the study participant to assess activities of daily living, personality change, and medical history of the study participant. On the basis of the screening interview a sample of study participants (N~500 in each site) is selected for a full clinical diagnostic dementia work up which includes a neurological test battery, extensive interview with a family member and examination by a clinician. Diagnoses are made in a consensus diagnosis conference using the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition (DSM-III R) and International Classification of Diseases 10th Revision (ICD-10) for dementia. The criteria of the National Institute for Neurological and Communicative Disease and Stroke-Alzheimer's Disease and Related Disorders Association were used to diagnose possible and probable Alzheimer's disease. The focus of the study is risk factors for dementia and Alzheimer's disease, but also of particular importance is the question of mild cognitive impairment. This refers to the condition of having some decline in cognition but the decline is not sufficient to meet the criteria for dementia. We have studied this over the course of this project. In follow up studies of individuals who have this diagnosis about one third of them are better at follow up, about a third are about the same, and about a third decline more to meet the criteria for dementia. This is a very important issue for researchers because the ultimate goal of the research is to figure out how to identify the individuals who will definitely progress to dementia. If there are clear identifiers, it would be possible to make interventions, while individuals still function well, and possibly prevent the development of dementia altogether or delay the onset significantly. This is crucial because at the moment individuals usually do not enter into the medical care system until the dementia symptoms are quite severe, and the pathological damage to the brain cannot be undone.

  Study phs000378

• Mult-omics Palbociclib Resistance Study in HR+/HER2– Metastatic Breast Cancer

  Resistance to CDK4/6 inhibitors and endocrine therapy (ET) are common and poorly understood since they have been real game changer in patients with HR-positive and HER2-negative MBC. A comprehensive genomic and transcriptomic analysis of pre-treatment and post-treatment tumors from patients treated with palbociclib plus ET identified novel markers associated with poor prognosis such as genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four unique prognostic clusters with distinct molecular features. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly. By comparing genomic and transciptomic profiles of paired samples, tumors were found to be further enriched in HRD genomic scars and many had switched to aggressive molecular subtypes. Furthermore, we identified high frequencies of acquired genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C. Our findings provide new insight into potential predictive biomarkers that could be targeted to overcome resistance. (NCT03401359)

  Study EGAS00001005736

• Drug development for pediatric cancers: the importance of patient' s genomic data re-use

  Cancer in children is uncommon and the overall prognosis for most pediatric cancers is good. However, while the combined survival rates have improved over the last decades, certain childhood malignancies, such as high-grade gliomas or metastatic sarcomas, still remain incurable in most patients. New strategies for targeting those devastating diseases are imperative, and patient genomic data can become a key asset in the process [1]. The Pediatric Cancer Genome Project’s datasets At EGA, we store over 500 datasets with sequencing data from pediatric cancer patients. A remarkable case is the datasets belonging to the Pediatric Cancer Genome Project (PCGP) from St. Jude Children’s Research Hospital–Washington University (Table 1 - EGAS list). PCGP is an ambitious effort to identify the mutations that drive childhood cancer and find new cures. Those datasets include 600 patients with complete tumor and normal genomes from 15 different tumor types. PCGP datasets have been an important resource for various studies that pooled genomic data from different public and in-house datasets to perform extensive genomic characterizations and publish comprehensive pan-cancer pediatric studies [2],[3]. Other interesting pediatric cancer datasets are from the Pediatric Brain Tumor Consortium, Sickkids or ICGC PedBrain project. How data reuse impacts drug development for pediatric cancers Recently, in October 2024, Nature Communications published a work led by the University of Michigan where authors used data from EGA (PCGP) check the table below as part of their strategy to pursue the identification of new tumor vulnerabilities susceptible to becoming novel therapeutic targets in diffuse midline glioma. Diffuse midline gliomas (DMG) are treatment-resistant and uniformly fatal pediatric brain tumors. The prognosis of this brainstem tumor is dismal with a median overall survival of 9–12 months from diagnosis. In this study, the authors first developed a lab model of the disease and reanalyzed data from the EGA to identify genes potentially linked to tumor severity. This approach revealed involvement of specific metabolic pathways, suggesting new possibilities for therapeutic intervention. In mice, the study shows that the use of statins can improve survival. For a brief overview of the underlying science, diffuse midline gliomas present intratumor heterogeneity with subpopulations of less-differentiated oligodendrocyte precursors and more differentiated astrocytes. Authors established in vitro models to recapitulate both phenotypes and identify metabolic programs in both subpopulations. To determine the clinical relevance, the authors re-used gene expression data from 76 DMG patients identifying a gene signature predicting decreased overall survival. After extensive metabolic characterization of subpopulations, authors defined strategies to target specific metabolic vulnerabilities. Pre-clinical experiments in mice using OXPHOS inhibitors and statins showed a reduction in tumor burden and increased overall survival [4]. In this scenario, the re-use of high-quality patient’s sequencing data appeared as an advantageous strategy to support the clinical relevance of in-vitro and pre-clinical findings. On the other hand, in rare conditions such as childhood cancer, the availability of public datasets and the possibility of pooling data from different sources can be the only way to obtain impactful results that lead to improvements for patients. References Davidoff, A. M. Pediatric Oncology. Seminars in pediatric surgery 19, 225–233 (2010). Gröbner, S. N. et al. The landscape of genomic alterations across childhood cancers. Nature 555, 321–327 (2018). Venu Thatikonda et al. Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers. Nature Cancer 4, 276–289 (2023). Mbah, N. E. et al. Therapeutic targeting of differentiation-state dependent metabolic vulnerabilities in diffuse midline glioma. Nature Communications 15, (2024). Datasets and Studies ID Title Access Policy Year EGAD00001000134 Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAS0000100192 Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas St. Jude Children's Research Hospital - Washington University Pediatric Cancer Genome Project 2017 EGAS00001000575 Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue The hospital for sick children ("SickKids") 2016 EGAD00001000792 Exome sequencing reads of paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAD00001002006 Whole genome sequencing of paediatric glioblastoma in the ICGC PedBrain project ICGC PedBrain project 2016

  Blog drug-development-for-pediatric-cancers

• STAMPEED: Northern Finland Birth Cohort 1966 (NFBC1966)

  The Northern Finland Birth Cohorts program (NFBC) was initiated in the 1960s in the two northernmost provinces of Finland to study risk factors involved in pre-term birth and intrauterine growth retardation, and the consequences of these early adverse events on subsequent morbidity and mortality. The uniqueness of NBFCs is that the data of the cohorts were obtained from early fetal life (including maternal health during pregnancy) to adulthood. The NFBC1966 includes 12,058 live births to mothers in the two northern-most provinces of Finland. Two decades later, a second cohort of 9432 births was obtained (NFBC1986). In NFBC1966 pregnancies were followed prospectively from the first antenatal contact (10-16th week). After birth, the offspring were examined and then again underwent clinical evaluation at ages 1y, 7y, 14-16y and 31y. At each visit, a wide range of phenotypic, lifestyle and demographic data were gathered by questionnaires and clinical examinations. For the most part, NFBC1986 has undergone similar evaluations to NFBC1966. Linkage to national registries includes hospitalization, deaths, education, medication, pensions, and provides up-to-date demographic and clinical information for members of both cohorts. DNA samples were obtained from 5,923 subjects from NFBC1966 and 6688 subjects from NFBC1986. Data coverage, 96% of all births in 1966 and 99% in 1986, is highly representative for the whole population. The NFBC program comprises more than 20 different projects coordinated by the Center of Lifecourse Disease studies in Northern Finland (COLD) at Oulu University. The prospective data collected from the NFBCs form a unique resource, allowing the study of disease emergence, and of the importance of genetic, biological, social and behavioral risk factors. The genome-wide association (GWA) study sponsored through the STAMPEED program of NHLBI employed genomic DNA samples previously collected by the NFBC1966 study and stored in the DNA repository of the National Institute for Health and Welfare, Finland. This NHLBI sponsored RO1 project aimed to identify genetic variants contributing to metabolic and cardiovascular diseases (CVD). In addition to de-identified genome wide genotypic data, a selected list of phenotypic data related to CVD including weight, height, BMI, HDL, LDL, total cholesterol, triglyceride, glucose, insulin and fasting status, are also available in dbGaP. A summary of the GWAS for the NFBC1966 cardiovascular risk traits can be found in Sabatti et al., Nature Genetics 41: 35-46, 2009, PMID: 19060910. The version 2 release of this study contains sequence data from seventeen loci associated with levels of triglyceride, HDL-C, LDL-C, total cholesterol, fasting plasma glucose, and fasting plasma insulin (Kathiresan et al. 2008, Willer et al. 2008, Sabatti et al. 2009, Dupuis et al. 2010, Teslovich et al. 2010). At each locus, protein-coding regions and 5' and 3' untranslated regions of genes nearest to single nucleotide polymorphisms showing genome-wide significant association with metabolic syndrome-related traits, were sequenced. Targeted Illumina sequencing of 78 genes (~270kb) using 150bp probes was performed on 4943 subjects of the Northern Finland Birth Cohort 1966 (NFBC1966). Whole exome sequencing on the Illumina platform was carried out on 586 of those participants. The sequencing study is part of a larger project that is funded by the National Human Genome Research Institute's Allelic Spectrum in Common Disease Initiative, and comprises sequence data from more than 7000 individuals in two Finnish cohorts: NFBC1966 and the Finland-United States Investigation of NIDDM Genetics (FUSION) study.

  Study phs000276

• bam files Targeted BS

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001667

• BAM files corresponding to PARN mutations identified in Hoyeraal-Hreidarsson syndrome patients

  PARN sequences of Patients 1 and 2 carrying mutatoins as decribed in Benyelles et al., EMBO Molecular Medicine 2019)

  Dataset EGAD00001005125

• BAM Files MBD-SEQ

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001668

• CentralAfricanCMC_Pemberton

  The CentralAfricanCMC_Pemberton dataset encompasses 153,798 SNPs from the Illumina Cardio-MetaboChip (Voight et al. 2012) genotyped in 406 individuals from 19 Central African Populations from Gabon, Cameroon, Centralafrican Republic and Uganda). Individual phenotypic and cultural information at the individual level for this data set encompass gender, lifestyle (hunter-gatherer or farmer), and, when available, stature phenotype (standing height in cm, sitting-height in cm, and weight in kg). Other cultural, linguistic, and geographical location information about the sampled populations can be found in Pemberton et al. , Human Genetics, 2018 (https://doi.org/10.1007/s00439-018-1902-3).This dataset can only be accessed and used for non-commercial research purposes with a finality complying with the informed consent provided by Central African donors for the study of human evolutionary history only.

  Dataset EGAD00010001584

• Integrative Analysis of Lung Adenocarcinoma in Never Smokers

  We performed whole genome sequencing of lung cancers from never smoker subjects from Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval (IUCPQ-UL) (N=125), Université Côte d'Azur (Nice) (N=47), the Environment And Genetics in Lung cancer Etiology (EAGLE) study (N=27), Yale University (N=22), and Moffitt Cancer Cente (N=11).

  Study phs001697

• Tumor-resident T-cell regulate responses to checkpoint blockade immunotherapies

  In cancer models, CD103+CD8 TRM cells are implicated in the response to anti-PD-1 immunotherapy, and a subset of CD4 TRM cells expressing the integrin CD49a is required for response to anti-CTLA-4 immunotherapy. We performed single-cell RNA sequencing on tumour-infiltrating T lymphocytes (TILs) isolated from colon carcinoma et unsupervised analyses reveal several TRM populations.

  Study EGAS50000000826

• Capture Hi-C on Hodgkin lymphoma cell line L-428

  In situ promoter capture Hi-C on Hodgkin lymphoma cell line L-428 in experimental triplicates. Hi-C libraries were prepared as previously described (Orlando et al., 2018, https://currentprotocols.onlinelibrary.wiley.com/doi/pdf/10.1002/cphg.63). Promoter capture was based on 32,313 biotinylated 120-mer RNA baits (Agilent). Hi-C libraries were sequenced using Illumina HiSeq 2000 technology. The files are in FASTQ format.

  Study EGAS00001003032

• Leeds Melanoma Cohort (LMC) gene expression study

  Array-based profiling (whole genome DASL HT12.4, Illumina Inc) in over 700 FFPE tumour blocks from the population-based Leeds Melanoma cohort recruited in the North of England, with a long follow up. Data used in tumour immune micro-environment investigation (Nsengimana et al 2018, J Clin Invest doi: 10.1172/JCI95351).

  Study EGAS00001002922

• Enzymatic methylation sequencing of rectal mucus from patients suspected to have colorectal cancer

  This dataset contains comprises enzymatic methylation sequencing (EM-Seq) data generated from 208 rectal mucus samples from patients suspected to have colorectal cancer and healthy controls. Targeted CpG sites were enriched using a panel of genes implicated in colorectal cancer, and libraries were prepared with NEBNext EM-Seq prior to Illumina sequencing. Sequencing was performed on the Illumina NovaSeq6000 platform, producing paired-end FASTQ files. These data support analyses of DNA methylation patterns in CRC detection and progression

  Dataset EGAD50000001871

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015718

• Single-cell RNA-sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumouroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015708

• Whole-genome sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumoroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015707

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015709

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015714

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Ither NB in Organoids WXS dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids WXS dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010281

• Primary Neuroblastoma Circle-seq Data

  Circle-seq data for 21 primary neuroblastoma samples supporting Koche et al. Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma (2020).

  Dataset EGAD00001006580

• Angiopredict Whole genome Shallow Sequencing

  Shallow sequencing of metastatic colorectal cancer samples for the Angiopredict and Nobev cohorts described in: van Dijk et al., JCO, in revision

  Dataset EGAD00001003990

• Neuroblastoma tumors by bulk RNAseq, from Berlanga et al, 2022

  To prouve the relevance of the use of PDX models derived from patient's tumors.

  Study EGAS00001007161

• SNPArray_TW

  The compressed file contains plink format file for the Affymetrix Human Origins SNP array data of 55 individuals generated and analyzed in Liu et al 2023 study of Taiwanese groups.

  Dataset EGAD00010002424

• 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

• Methylation of Ewing sarcoma tumors - RRBS (ICGC)

  RRBS data of 86 Ewing patients (French). Illumina HiSeq 2000/2500 (Fastq files available). Sheffield et al. Nat Med. 2017 Jan 30

  Dataset EGAD00001003133

• Somatic evolution in the non-neoplastic IBD affected colon

  Whole genome and whole exome sequencing data supporting the manuscript 'Somatic evolution in the non-neoplastic IBD affected colon' by Sigurgeir Olafsson et al.

  Dataset EGAD00001006061

• Circulating cell-free DNA analysis in Small Cell Lung Cancer

  Small cell lung cancer (SCLC) accounts for ~250,000 deaths worldwide each year. Acquisition of adequate tumour biopsies is challenging and liquid biopsies present the best option for patient stratification and response monitoring. We present genome-wide and targeted plasma DNA sequencing data that identifies tumour related changes in 91% of limited (LS-SCLC) and 100% of extensive stage (ES-SCLC) patients. Parallel analysis of circulating tumour cells (CTCs, by CellSearch) based on ≥ 1 CTC/7.5ml blood increased tumour detection frequencies to 98% patients (95% for LS-SCLC) where CTC count and plasma DNA readouts correlated with disease stage and overall survival (OS). Targeted plasma DNA sequencing identified potential therapeutic targets in >50% of patients. This approach will support trials of targeted therapies where improved patients outcomes are urgently required.

  Study EGAS00001003110

• Upper respiratory microbiome of COVID-19 patients

  Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 microbiome studies by analyzing the upper respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We found that time in the intensive care unit and the type of oxygen support explained the most variation within the upper respiratory tract microbiome, dwarfing (non-significant) effects from viral load, disease severity, and immune status. Specifically, mechanical ventilation was linked to altered community structure, lower species- and higher strain-level diversity, and significant shifts in oral taxa previously associated with COVID-19.

  Study EGAS00001004951

• Genome-wide associations of human gut microbiota variation and implications for causal inference analyses

  Here we use appropriate taxon-specific models along with support from independent cohorts to show association between human host genotype and gut microbiome variation. Using fecal derived 16S rRNA gene sequences and host genotype data from the Flemish Gut Flora Project (FGFP) we identify genetic associations involving multiple microbial traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease, however in the absence of clear microbiome driven effects, caution is needed in interpretation. This work marks a growing catalog of genetic associations which will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.

  Study EGAS00001004420

• RNA sequencing data from visceral and abdominal subcutaneous adipose tissue from morbidly obese women with normal glucose tolerance or type 2 diabetes

  The study group consisted of 17 obese women with normal glucose tolerance and 15 obese women with T2DM. Adipose tissue specimens were taken from the epigastric region of the abdominal wall (SAT) and from the major omentum (VAT). RNA was isolated and RNA sequencing was used to analyse the transcriptome. Dharuri H et al, Diabetologia. 2014;57(11):2384-92.

  Study EGAS00001001872

• QSEA – modelling of genome-wide DNA methylation from sequencing enrichment experiments

  We describe a new method, QSEA, for analyzing methylation enrichment data. We generated a benchmark experiment consisting of MeDIP-seq enrichment data, targeted BS-seq validation data, and RNA-seq data on five pairs of tumor and adjacent normal samples of non-small cell lung cancer patients. Details of the method and its performance on the data have been described in Lienhard et al. (2016).

  Study EGAS00001001822

• Liver CD14+CD8+ T cells scRNAseq dataset

  Sorted single CD8+T cells expressing CD14 from human liver for SMARTSeq2. Livers processed: Kucykowicz et al STAR Prot 2022:pubmed.ncbi.nlm.nih.gov/35516846/ Published: Pallett et al Nature 2022 Tissue CD14+CD8+T-cells are reprogrammed by myeloid cells and modulated by LPS A modified SMART-seq2 protocol was performed on the single flow cytometry sorted-cells as previously described58. After cDNA generation, libraries were prepared (384 cells per library) using the Illumina Nextera XT kit (Illumina). Each library was sequenced to achieve a minimum depth of 1-2 million raw reads per cell using an Illumina HiSeq 4000 using v. 4 SBS chemistry to generate 75-bp paired-end reads.

  Dataset EGAD00001009831

• A Phase II Trial of High Dose Interleukin-2 and Multi-site Stereotactic Ablative Radiotherapy for Patients with Metastatic Renal Cell Carcinoma

  Immune-based therapies have improved outcomes for metastatic renal cell carcinoma (mRCC) but there is still a significant margin for improvement. Here, we report the results of a phase II trial combining high dose Interleukin-2 (HD-IL-2) with stereotactic ablative body radiotherapy (SAbR) for patients with metastatic renal cell carcinoma.

  Study EGAS00001003605

• Single-cell RNA-seq of human kidney tumors

  Fresh nephrectomy samples were collected from a total of 5 untreated ccRCC patients. Out of these 5 patients, 7 samples were obtained. Two samples consisted of fresh versus frozen single cells from the primary tumor site of one patient. Two other samples consisted of matched primary and distant thrombus sites (the vena cava) of a second patient. The three remaining samples came from the primary tumor sites of three distinct ccRCC patients. Single-cells were captured into 10x barcoded gel beads and RNA-sequencing library preparation was done using Chromium Single Cell 3' v2 chemistry. Sequencing was performed on a Illumina HiSeq 4000 sequencer.

  Dataset EGAD00001009306

• Genome-Wide Association Study of Preterm Birth

  Preterm birth (PTB, born before 37 weeks of gestation) is a leading cause of neonatal mortality and post-natal morbidity. PTB affects one in nine all live births in the U.S. Notably, the highest rate of PTB occurs among African Americans (one in six). PTB is a complex trait, likely determined by multiple environmental and genetic factors and their interactions. We demonstrated strong familial aggregation of preterm and low birthweight in the US Blacks and Whites (Wang et al, NEJM, 1995) and conducted the largest candidate gene study of preterm birth at that time (Hao et al, HMG, 2004). We showed that a subset of mothers with certain metabolic gene variants are particularly vulnerable to the adverse effects of cigarette smoking on low birthweight and preterm births (Wang et al, JAMA, 2002). We also published a number of papers that examined the effect of maternal pre-pregnancy BMI, micronutrient status, stress and environmental toxins on the risk of preterm birth and related conditions. This project, supported by a grant from the NICHD (2R01HD41702, PI, Xiaobin Wang), aimed to conduct a genome-wide association study (GWAS) and apply advanced statistical methods to identify susceptibility loci of PTB in a predominantly urban low-income African American sample, a subset of the Boston Birth Cohort. PUBLIC HEALTH REVELANCE: We anticipate that this study will lead to the identification of novel genetic loci of PTB and gene-environment interactions. Such findings not only will provide important insights into mechanisms leading to PTB, but also may help identify women at high-risk of PTB, which in turn, may lead to the development of early and targeted interventions that can prevent PTB or mitigate the severity and consequences of PTB.

  Study phs000332

• Sequenced IDH wildtype, untreated, human glioblastoma samples (GB-UK cohort)

  BAM files for 42 IDH wildtype, untreated, human glioblastoma samples from the GB-UK cohort, published in Noorani & Haughey et al. Cancer Discovery (2025).

  Dataset EGAD50000001649

• DAC for Liquid CNA in High Grade Serous Ovarian Cancer

  Low pass sequencing of sequential cell free and tumour DNA with matched whole genome sequencing from five patients with high grade serous ovarian cancer presented in Hockings et al Cancer Research paper, 2025.

  Dac EGAC50000000648

• L1-Architect Project Dataset

  Tumours with high and ultrahigh rates of somatic retrotransposition studied in the publication by Zumalave et al. titled Synchronous L1 retrotransposition events promote chromosomal crossover early in human tumorigenesis

  Dataset EGAD50000000607

• RNAseq of LC2AD with AD80 or DMSO

  RNAseq of LC2AD with AD80 or DMSO Plenker et al., Mechanistic insight into RET kinase inhibitors targeting the DFG-out conformation in RET-rearranged cancer

  Dataset EGAD00001003316

• Ovarian cancer sequencing dataset

  Sequencing data from patients with Ovarian cancer. Data utilised in the 'Enhanced detection of circulating tumor DNA by fragment size analysis' manuscript (Mouliere et al, 2018)

  Dataset EGAD00001004939

• Neuroblastoma Cell Line Circle-seq Data

  This dataset comprises Circle-seq data for 12 neuroblastoma cell lines supporting Koche et al. Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma (2020).

  Dataset EGAD00001006579

• Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) - OncoArray Genotypes

  The data come from 40 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). CIMBA recruits individuals with pathogenic mutations in BRCA1 or BRCA2. The majority of carriers were recruited through cancer genetics clinics offering genetic testing, and were enrolled into national or regional studies. The remainder were identified by population-based sampling of cases, or community recruitment. Eligibility to participate is restricted to carriers of pathogenic BRCA1/2 mutations who were 18 years or older at recruitment. Information collected included amongst other variables: age at recruitment; ages at breast and ovarian cancer diagnosis; and estrogen receptor (ER) status. Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in Phelan et al, Identification of twelve new susceptibility loci for different histotypes of epithelial ovarian cancer, Nat Genet. 2017 May;49(5):680-691 (PMID:28346442), and Milne et al, Identification of ten variants associated with risk of estrogen receptor negative breast cancer, Nat Genet (in press).

  Study phs001321

• NHLBI TOPMed: Walk-PHaSST Sickle Cell Disease (SCD)

  Walk-PHaSST study is a multi-center clinical trial to evaluate the effects of sildenafil on Sickle Cell Disease (SCD) population with low exercise capacity associated with an increased Doppler-estimated pulmonary artery systolic pressure (as assessed by the tricuspid regurgitant velocity (TRV)). It is a double-blind, placebo-controlled trial to assess the safety, tolerability, and efficacy of sildenafil in patients with SCD who had both an elevated TRV and decreased exercise capacity. The screening phase of the study enrolled 720 subjects and 74 of them were randomized for the clinical trial. For the screening cohort, we have collected general demographics and race/ethnicity, hemoglobin genotype, physical examination, laboratory screening, transthoracic Doppler echocardiography, and 6 minute walk test in 9 US and 1 UK site. The walk-PHaSST biorepository have banked samples from 610 of the screening subjects. A total of 592 subjects from the screening phase are included in the TOPMed program for WGS.

  Study phs001514

• SEER Remote Access Pilot Test Data (2018)

  This is a limited use Surveillance, Epidemiology, and End Results (SEER) file for use in a pilot test of remote data access. The SEER Program of the National Cancer Institute (NCI) is an authoritative source of information on cancer incidence and survival in the United States. SEER currently collects and publishes cancer incidence and survival data from population-based cancer registries covering approximately 34.6 percent of the U.S. population. The SEER Program registries routinely collect data on patient demographics, primary tumor site, tumor morphology and stage at diagnosis, first course of treatment, and follow-up for vital status. The mortality data reported by SEER are provided by the National Center for Health Statistics. The population data used in calculating cancer rates is obtained periodically from the Census Bureau. The SEER research data files include SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas.

  Study phs002012

• 1000 Genomes Used for Cloud Testing

  WARNING: This is a test data set. The phenotype data was not checked to match 1000 Genomes project. Use with caution.This study provides public access to a demonstration subset of 1000 genomes sequence data in dbGaP. It is intended to be used by software developers who design, implement and validate pipelines for dbGaP data. While this project distributes only public data, it uses dbGaP security mechanisms which include a project-specific security key and a decryption password. Since the data are public, the key and password for this project will be included by SRA into public demonstration packages that permit users to test and validate the security of their computational pipelines. Note that all public users of this data will be logged under the same project and account ID. The datasets attached to this project must be restricted to 1000 Genomes data identical to the project's public FTP site. To access these test data using SRA toolkit use prj_phs710EA_test.ngc.

  Study phs000710

• ucfDNA workflows for molecular profiling of malignant disease

  Urinary cell-free DNA (ucfDNA) is a promising liquid biopsy analyte obtained by a non-invasive sampling method, particularly valuable in urological cancers due to the proximity of biofluids to the tumor site. However, extremely high fragmentation and low abundance of ucfDNA pose significant analytical challenges. Improper handling and storage can severely affect ucfDNA quality, necessitating optimized pre-analytical workflows for clinical applications. We evaluated multiple pre-analytical workflows, including urine stabilization approaches against unstabilized urine samples. Our results demonstrated that without stabilization, ucfDNA degraded rapidly and minimal quantities remaining after 72 hours. In contrast, urine stabilization preserved ucfDNA integrity, enabling successful downstream analyses, including digital PCR and next-generation sequencing, for mutation detection in cancer-related genes and genome wide copy number profiling. These findings underscore the critical role of stabilization for a reliable ucfDNA analysis and highlight its potential in molecular diagnostics as a complementary tool to plasma-based liquid biopsies.

  Study EGAS50000001093

• Tracking the origins and drivers of subclonal metastatic expansion in prostate cancer

  Tumour heterogeneity in primary prostate cancer is a well-established phenomenon. However, how the subclonal diversity of tumours changes during metastasis and progression to lethality is poorly understood. Here we reveal the precise direction of metastatic spread across four lethal prostate cancer patients using whole-genome and ultra-deep targeted sequencing of longitudinally collected primary and metastatic tumours. We find one case of metastatic spread to the surgical bed causing local recurrence, and another case of cross-metastatic site seeding combining with dynamic remoulding of subclonal mixtures in response to therapy. By ultra-deep sequencing end-stage blood, we detect both metastatic and primary tumour clones, even years after removal of the prostate. Analysis of mutations associated with metastasis reveals an enrichment of TP53 mutations, and additional sequencing of metastases from 19 patients demonstrates that acquisition of TP53 mutations is linked with the expansion of subclones with metastatic potential which we can detect in the blood.

  Study EGAS00001000942

• Rna-Seq Leiomyosarcoma subtypes

  Leiomyosarcomas (LMS) are genetically heterogeneous tumors differentiating along smooth muscle lines. Currently, LMS treatment is not informed by molecular subtyping and is associated with highly variable survival. While disease site continues to dictate clinical management, the contribution of genetic factors to LMS subtype, origins, and timing are unknown. Here we analyzed 70 genomes and 130 transcriptomes of LMS, including multiple tumor regions and paired metastases. Molecular profiling highlighted the extremely early origins of LMS. Three specific subtypes of LMS develop from distinct lineages of smooth muscle cells. Of these, dedifferentiated LMS with high immune infiltration and tumors primarily of gynaecological origin acquired the highest burden of genomic mutation and are associated with worse survival. Homologous recombination defects lead to genome-wide mutational signatures, and a corresponding sensitivity to PARP and other DNA damage response inhibitors, suggesting a novel therapeutic strategy for LMS. Finally, by phylogenetic reconstruction, we present evidence that clones seeding lethal metastases arise decades prior to LMS diagnosis.

  Study EGAS00001004783

• Latency and interval therapy affect the evolution in metastatic colorectal cancer

  While comparison of primary tumor and metastases has highlighted genomic heterogeneity in colorectal cancer (CRC), previous studies have focused on a single metastatic site or limited genomic testing. Combining data from whole exome and ultra-deep targeted sequencing, we explored possible evolutionary trajectories beyond the status of these mutations, particularly among patient-matched metastatic tumors. Our findings confirm the persistence of known clinically-relevant mutations (e.g. those of RAS family of oncogenes) in CRC primary and metastases, yet reveal that latency and interval systemic therapy affect the course of evolutionary events within metastatic lesions. Specifically, our analysis of patient-matched primary and multiple metastatic lesions, developed over time, showed a similar genetic composition for liver metastatic tumors, which were 21-months apart. This genetic makeup was different from those identified in lung metastases developed before manifestation of the second liver metastasis. These results underscore the role of dormancy in the evolutionary path of metastatic CRC.

  Study EGAS00001003646

• Next-generation sequencing raw data from metastatic prostate cancer biopsies - observational study Vall d'Hebron Institute of Oncology (Ethics committee code PR-AG-5248)

  Paired tumor-normal whole exome sequencing data from patients with metastatic prostate cancer; dataset from Arce-Gallego et al, Cell Reports Med 2024

  Dac EGAC50000000448

• Khoe-San whole genome sequencing

  High-coverage (>30X) whole genome data (FASTQ) for 25 southern African Khoe-San individuals (from five populations). These are the same individuals as in Schlebusch et al. 2020 (EGAD00001006183), but different data.

  Dataset EGAD50000001559

• WES/WXS data for ependymomas (42 tumor-control pairs)

  Whole exome sequencing data for ependymomas (42 tumor-control pairs). See Mack, Witt et al. Nature 506(7489):445-50, 2014 (PMID: 24553142).

  Dataset EGAD00001000951

• WGS data for ependymomas (5 tumor-control pairs)

  Whole genome sequencing data for ependymomas (5 tumor-control pairs). See Mack, Witt et al. Nature 506(7489):445-50, 2014 (PMID: 24553142).

  Dataset EGAD00001000950

• SNP array data in Massim study

  The compressed file contains plink format file for the Illumina MEGA SNP array data of 255 individuals generated and analyzed in Liu et al study of genom-wide variation of the Massim region.

  Dataset EGAD00001008545

• Implementation, Adoption, and Utility of Family History in Diverse Care Settings

  The purpose of this study is to address the key question of whether and how family health history (FHH) is adopted as a tool to more efficiently manage patients at risk for breast, colon, ovarian, and hereditary cancer syndromes as well as thrombophilia and coronary heart disease (CHD) and to provide evidence supporting clinical utility -- improved health behaviors in patients and physician screening recommendations. Five health care delivery organizations will participate in this demonstration project: Duke University, the Medical College of Wisconsin, the Air Force, Essentia Health, University of North Texas. Duke will serve as a coordinating center for this project (Pro00043372) as well as a site. Healthcare Effectiveness Data and Information Set (HEDIS) measures as intermediate clinical effectiveness measures for Coronary Heart Disease (CHD) and selected cancers as well as survey/formative data and electronic medical record (EMR) data will be used as outcomes measures. The research model is purposely designed to mimic clinical delivery as an important step toward widespread implementation and sustainability. In addition, a cost-effectiveness analysis comparing usual care to the FHH guided preventive health model will be used. The completion of this project will result in an optimal strategy for integration of FHH data collection and clinical decision support (CDS) tools into an EMR and demonstrate the utility of the FHH intervention among diverse primary care patients, their settings, their providers, and the health systems that deliver their care. Specific Aim 1: To optimize the collection of patient entered FHH in diverse clinical environments for coronary heart disease, thrombosis, and selected cancers Specific Aim 2: To export FHH data to an open clinical decision support (open CDS) platform and return CDS results to providers and patients (and to EMRs where relevant). To explore the integration of genetic risk and FHH data at selected sites. Specific Aim 3: To assess the clinical and personal utility of FHH using a pragmatic observational study design to assess reach, adoption, integrity, exposure, and sustainability, and to capture, analyze, and report effectiveness outcomes at each stakeholder level: patient, provider, and clinic/system. Specific Aim 4: To take a leadership role in the dissemination of guidelines for a FHH intervention across in diverse practice settings. AAA Hypertension Lupus Multiple sclerosis Obesity Osteoporosis Thyroid disease Rheumatoid arthritis Blood clotting (6): Blood Clot (high risk features) Factor V PT mutation AT III deficiency Protein S deficiency Protein C deficiency Brain Disorders (5): Dementia Hemorrhagic stroke Ischemic stroke Macrocephaly Seizure Cancer/Adenomas (32): Bone cancer Brain cancer Breast cancer Colon cancer Adrenal cortex tumor Neuroendocrine tumor Paraganglioma Pheochromoctyoma Pituitary adenoma Medullary thyroid cancer Non-medullary (follicular or papillary) thyroid cancer Don't know type of thyroid cancer Thyroid nodule Other type of endocrine cancer Esophageal cancer Kidney cancer Leukemia Lipoma Liver cancer Muscle cancer Ovarian cancer Pancreatic cancer Prostate cancer Rectal cancer Retinoblastoma Melanoma Non-melanoma skin cancer Do not know type of skin cancer Small bowel cancer Stomach cancer Uterine cancer Other type of cancer Cardiovascular/heart/artery disease (5): Atrial fibrillation Carotid stenosis Heart attack/coronary artery disease Peripheral arterial disease Other heart disease Diabetes (3): Gestational diabetes Diabetes type I Diabetes type 2 Digestive Disorders (5): Colon polyp Crohn's disease Irritable bowel syndrome Ulcerative colitis Other digestive disorder Eye Disorder (3): Blindness Glaucoma Macular degeneration Hereditary Cancer Syndromes (22): Birt-Hogg-Dube syndrome Cowden syndrome Familial adenomatous polyposis Hereditary breast and ovarian cancer syndrome Hereditary diffuse gastric cancer Hereditary leiomyomatosis and renal cell carcinoma syndrome Hereditary melenoma Hereditary papillary renal cancer syndrome Hereditary paraganglioma-pheochromocytoma syndrome Hereditary retinoblastoma Juvenile polyposis Li-Fraumeni syndrome Lynch syndrome Mutyh-associated polyposis Malignant hyperthermia susceptibility Multiple endocrine neoplasia type 1 Multiple endocrine neoplasia type 2 Nevoid basal cell carcinoma syndrome Peutz-Jeghers syndrome Tuberous Sclerosis complex Von-Hippel Lindau syndrome Other hereditary cancer Hereditary Cardiovascular syndromes (10): Long qt Brugada Catecholaminergic polymorphic ventricular tachycardia Hypertrophic cardiomyopathy Dilated cardiomyopathy Left ventricular non-compaction syndrome Arrhythmogenic right ventricular dysplasia Ehlers-Danlos syndrome Marfan syndrome Other hereditary cardiovascular syndrome High cholesterol (2): Hyperlipidemia Familial hypercholesterolemia Kidney Disease (6): Cystic kidney disease Diabetic kidney disease Kidney nephrosis Nephritis Nephrotic syndrome Other kidney disease Liver Disease (6): Alpha 1 antitrypsinase deficiency Auto-immune hepatitis Hereditary hemochromatosis Primary biliary cirrhosis Sclerosing cholangitis Wilson's disease Lung Disease (3): Asthma COPD/chronic bronchitis/emphysema Other lung disease Psychological disorder (14): Addiction ADHD Autism Bipolar Depression Eating disorder Intellectual disability Obsessive compulsive disorder Panic disorder Personality disorder PTSD Schizophrenia Social phobia Sickle cell/thalassemia (3): Sickle cell disease Sickle cell trait Thalassemia

  Study phs001641

• De novo detection of somatic variants

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

  Dataset EGAD50000001292

• Whole-genome sequencing data of poorly differentiated thyroid carcinomas and matched blood from six patients

  This dataset contains raw sequencing reads in FASTQ format from 12 samples, comprising paired tumour and matched blood DNA from six patients diagnosed with poorly differentiated thyroid carcinoma (PDTC). Genomic DNA was extracted from fresh-frozen tumour tissue and peripheral blood using standard protocols. Whole-genome sequencing was performed on the Illumina HiSeq X Ten platform, generating paired-end reads at an average depth of approximately 20X. These data support investigations into the somatic mutational landscape and genomic alterations associated with PDTC.

  Dataset EGAD50000001628

• 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

• Development and Validation of a Prognostic and Predictive 32-Gene Signature for Gastric Cancer

  We applied this signature to a 567-patient GC cohort to establish genomic-based molecular subtypes and then used a support vector machine to build a molecular subtype-based risk-scoring model. Both source code and supplementary datasets for risk score prediction are available at https://github.com/hwanglab/Yonsei_gastric_cancer_32genes.

  Dataset EGAD00001008091

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Ither NB in Organoids RNA-Seq dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids RNA-Seq dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010283

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715

• McGill Epigenomics Mapping Centre

  The McGill Epigenomics Mapping Centre (EMC) and Data Coordination Centre (EDCC) were established in 2012 at the McGill University and Genome Quebec Innovation Centre (Montreal, Canada) to support large-scale human epigenome mapping for a broad spectrum of cell types and diseases. Previous epigenetic studies have provided profiles of specific chromatin marks in relation to basic biological processes, and future studies of molecular mechanisms must build upon these proofs-of-concept by integrating sequence-based variation with multiple levels of epigenetic and transcriptional regulation across the genome of human tissues and animal disease models. This project leverages the high-throughput sequencing infrastructure and expertise in genomics and transcriptomics at the McGill Innovation Centre to carry out this research. Controlled access to the data by collaborators and the greater scientific community is gained via a portal, which takes advantage of Compute Canada high-performance computing cluster resources to manage the large volume of data associated from the generation of reference epigenome maps. McGill University is one of two Canadian mapping and data coordination centres, the other based at the Michael Smith Genome Sciences Centre in Vancouver, British Columbia. The generation of comprehensive epigenome maps at McGill University is part of a larger international effort that is coordinated by the International Human Epigenome Consortium (IHEC), whose overall long-term objective is to determine the extent to which the epigenome shapes human populations over generations and in response to the environment. This project is funded under the Canadian Epigenetics, Environment, and Health Research Consortium (CEEHRC) by the Canadian Institutes of Health Research and by Genome Quebec, with additional support from Genome Canada. The computing and networking infrastructure, and part of the software development, are provided by Compute Canada and CANARIE.

  Study EGAS00001000995

• Ongoing Replication Stress Tolerance and Clonal T Cell Responses Distinguish Liver and Lung Recurrence and Patient Outcomes in Pancreatic Ductal Adenocarcinoma

  Patients with metastatic pancreatic ductal adenocarcinoma (PDAC) survive longer when disease spreads to the lung but not to the liver. We generated overlapping, multi-omic datasets to identify molecular and cellular features that distinguish patients whose disease develops liver metastasis (liver cohort) from those whose disease progression results in lung metastasis without liver metastases (lung cohort). Lung cohort patients generally survived longer than liver cohort patients, independent of tumor subtype. We developed a pORG gene signature that distinguishes primary tumors in the liver and lung cohorts. We identified ongoing replication stress (RS) response pathways in high pORG/liver cohort tumors, while low pORG/lung cohort tumors had greater densities of lymphocytes and shared T cell clonal responses. Our study demonstrates that liver-avid PDAC is associated with tolerance to ongoing RS, limited tumor immunity, and less favorable outcomes; whereas low RS, lung-avid/liver-averse tumors are associated with active tumor immunity that may account for favorable outcomes. As expected, we found high frequencies of KRAS, TP53, CDKN2A, and SMAD4 gene alterations in our tumor samples. High pORG activity (GSVA scores) in our primary tumors appear to be positively correlated with alteration frequencies in both TP53 and CDKN2A. We did not see a correlation with alterations in KRAS as almost all the tumor samples have KRAS alterations. From a de-identified dataset of 1,873 patients diagnosed with and/or treated for PDAC at our institution between 2004 and 2020, we identified 422 patients for which we had specimens with sequencing data (N=374) and/or specific evidence of disease metastasis site(s) from the OHSU cancer registry or disease-relevant computed tomography (CT) scans to allow cohort classification. Note that our study includes RNA-Seq, DNA-Seq panel, and TCR-Seq (T-cell Receptor Sequencing) data, but that this dbGaP submission just includes the patients/samples with RNA-Seq and/or DNA-Seq panel data. Therefore, this submission includes 290 samples from 278 patients. TCR sequence data is available on the Adaptive Biotechnologies platform. Clinical course timepoints, patient demographics, stage, grade, nodal involvement, resection margins, and angiolymphatic invasion were provided as deidentified data by the OHSU cancer registry with quality control data verification in a subset by pathologists (BB and TM). We reviewed all available computed tomography (CT) scans for all patients with primary tumor resection dates recorded by the cancer registrar, with tumor samples analyzed by RNA-seq, DNA-seq, or TCR-seq, and/or with additional information indicating metastatic spread (e.g., metastatic samples received for related studies). We abstracted the site of all lesions proven to be metastatic by biopsy and/or that clearly increased in size during progression or decreased in size during treatment as long as a radiologist described the lesion as “likely”, “suspicious for”, “concerning for”, or “favor” metastasis. Clinical imaging was reviewed by a radiologist (AG) to validate patient assignments to the liver, lung, and neither liver nor lung (other recurrence site) cohorts. Time to recurrence was calculated from the earliest of either the recurrence date provided by the OHSU cancer registry, or the date of earliest lesion abstracted from CT reports. The subject attributes reported in this submission were up to date at the time of our data freeze, which occurred July 2021.

  Study phs003597

• Very Low Tumor Mutation Burden Identifies Inflamed Recurrent Glioblastomas Responsive to Cancer Immunotherapy

  A subset of available tumors (with matched blood) from patients enrolled in a phase I clinical trial testing a recombinant poliovirus, published by Desjardins et al. NEJM 2018 (PMID:29943666), were analyzed by whole exome sequencing and RNA-seq. It was discovered that low tumor mutation burden correlated with survival outcome, and also discovered that low tumor mutation burden correlated with higher inflammatory gene signatures by RNA-seq.

  Study phs002270

• Identification of Novel Therapeutic Targets for Calcific Aortic Valve Stenosis Using Integrative Genomics

  In order to identify novel therapeutic targets for calcific aortic valve stenosis, we have generated a large transcriptomic dataset from RNA sequencing of human aortic valve tissues from 500 individuals undergoing aortic valve replacement or heart transplant at the Institut universitaire de cardiologie et de pneumologie de Québec – Université Laval (QUEBEC-CAVS-RNA). This dataset represents a unique resource to understand the molecular mechanisms underlying aortic valve diseases.

  Study phs003541

• The Natural History of Human Prostate Cancer

  Whole genome DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of 3 men. For each of three different prostates, multiple tumour samples (4, 5, and 3 depending on the case) and one normal tissue sample were whole genome sequenced with a matched blood sample using the Illumiuna HiSeq platform. Tumour samples were sequenced to a target depth of 50X and normals and blood to a target depth of 30X. As of September 2020, some of the studies using these data include: Cooper et al, Nature Genetics 2015 (PMID: 25730763) Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001000689

• Genomic study of an AT-AML

  Ataxia Telangiectasia (A-T) is caused by biallelic mutations in ATM and confers predisposition to cancer, with acute myeloid leukaemia (AML) being rarely observed. We investigated an AML arising in an A-T patient for secondary genetic events by performing whole exome sequencing of serial samples over the disease course. AML samples were compared to a reference "germline" sample from a much earlier time point. Goldgraben et al 2020, Pediatric Blood & Cancer

  Study EGAS00001004392

• Center for Technology Licensing at Cornell University for data associated with Nature Medicine 2024 paper

  For data access to plasma/tumor/normal samples from the manuscript "Ultrasensitive plasma-based monitoring of tumor burden using machine learning-guided signal enrichment" from Widman et al. Nature Medicine 2024

  Dac EGAC50000000207

• WGS data from COMPASS Trial

  WGS data for pancreatic cancer samples (COMPASS Trial; Knox et al., Journal of Clinical Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=263 tumour/normal pairs).

  Dataset EGAD50000001832

• Women's Interagency HIV Study (WIHS)

  The Women's Interagency HIV Study (WIHS), a multicenter, prospective study, was established in August 1993 to carry out comprehensive investigations of the impact of HIV infection and its clinical, laboratory, and psychosocial effects in women. The purpose of this study is to collect and evaluate these data from HIV infected and at-risk women to better understand and provide support for women whom are currently HIV infected or who are at risk for HIV infection. Participants will have study visits every 6 months. Questionnaires regarding sexual behavior, health care utilization, medical and obstetric/gynecological history, psychosocial factors, and sociodemographics will be completed by participants. Physical, gynecological, and lipodystrophy examinations will also be conducted at each visit, and current medication regimen will be noted. Blood and other bodily fluid samples will be collected and registered in both local and national repositories of the WIHS in conjunction with NIAID.

  Study phs001503

• MYC Inhibition By Omomyc Causes DNA Damage And Overcomes PARPi Resistance In Breast Cancer.

  This study investigates the role of MYC dysregulation in DNA damage response (DDR) and PARP inhibitor (PARPi) resistance in breast cancer. Using Omomyc, a direct MYC inhibitor, we demonstrate that MYC inhibition shuts down DDR genes in triple-negative breast cancer (TNBC), causing DNA repair defects and inducing DNA damage that synergizes with PARPi treatment. Through patient-derived models and clinical samples from metastatic HR-altered breast cancer patients treated with PARPi, we identify MYC transcriptional activity as a predictive biomarker of PARPi resistance. Digital spatial profiling (DSP) analysis of pre-treatment tumor biopsies reveals that patients with progressive disease have significantly elevated MYC signatures compared to responders. These findings support the therapeutic strategy of combining MYC inhibition with PARPi in PARPi-resistant breast cancers where high MYC activity predicts poor response to therapy.

  Study EGAS50000001347

• 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

• 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

• Vento_Placental_Cell_Atlas

  The Human Cell Atlas initiative is an ambitious global research effort which aims to describe every cell in the human body across all developmental stages to generate a reference map to accelerate progress in science and medicine particularly relating to human development and disease. The initiative is led by investigators based at the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard and funding support from the Wellcome and NIH. This specific project will assess human development. We aim to interrogate the cellular composition and molecular regulators underpinning development and maturation through single cell RNA-sequencing/spatial transcriptomics and computational algorithms to predict cellular developmental trajectories and cell-cell interactions. We will subsequent validate these findings in situ using allied imaging technologies e.g. immunohistochemistry and RNAscope and in vitro culture of human intestinal organoids (HIOs).

  Study EGAS00001004187

• Reprogramming of stroma-derived chemokine networks drives the loss of tissue organization in nodal B cell lymphoma

  Here, we utilized single-cell and spatial mapping to interrogate the mechanisms directing tissue architecture in human lymph nodes (LN) and its disruption in nodal B cell lymphoma. Specifically, we mapped the cellular landscape of follicular lymphoma (FL; n=6) and diffuse large B cell lymphoma (DLBCL; n=8) alongside non-malignant reactive LNs (rLN; n=5) using single-cell RNA sequencing. Our data support the central role of LN-resident stromal cells in chemokine-driven lymphocyte zonation and reveal an inflammatory feedback loop fueled by tumor-reactive T cells, triggering stromal remodeling, progressive loss of homeostatic chemokine gradients and tissue organization from non-malignant to FL and DLBCL. Collectively, our results highlight the principles of LN organization and suggest how lymphoma-induced microenvironmental reprogramming drives loss of tissue organization.

  Study EGAS00001006986

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Study EGAS00001001184

• BRCA1 secondary splice-site mutations

  BRCA1 splice isoforms d11 and d11q can contribute to PARP inhibitor (PARPi) resistance by splicing-out mutation-containing exons, producing truncated, partially-functional proteins. However, the clinical impact and underlying drivers of BRCA1 exon skipping remain undetermined. We analyzed nine ovarian and breast cancer patient derived xenografts (PDX) with BRCA1 exon 11 frameshift mutations for splice isoform expression and therapy response.

  Study EGAS50000000022

• Luminal progenitor cell line iHBEC(CD117)

  Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions. After culturing the cells for more than 60 passages, cells were subjected to scRNA-seq as well as bulk RNA sequencing of two subpopulations (CD271+ and CD271-).

  Dataset EGAD50000000723

• SNPArray_Viet

  The compressed file contains plink format file for the Affymetrix Human Origins SNP array data of 260 individuals generated and analyzed in Liu et al 2020 study of 22 ethnolinguistic groups in Vietnam.

  Dataset EGAD00010002287

• RCC_HTA2.0_Reustle2020

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Reustle et al, Genome Med 12:2020 32. Preprocessing of microarray data was performed using Robust Multi-array Average (RMA).

  Dataset EGAD00010002323

• DKFZ-St.Jude Medulloblastoma - 6 TB control exomes

  6 control exomes, TB cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006664

• 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