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• 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

• Heterogeneous endocrine cell composition defines human islet functional phenotypes

  Phenotyping and genotyping initiatives within the Integrated Islet Distribution Program (IIDP), the largest source of human islets for research in the U.S., provide standardized assessment of islet preparations distributed to researchers, enabling the integration of multiple data types. Data from islets of the first 299 organ donors without diabetes, analyzed using this pipeline, highlights substantial heterogeneity in islet cell composition associated with hormone secretory traits, sex, reported race and ethnicity, genetically predicted ancestry, and genetic risk for type 2 diabetes (T2D). While α and β cell composition influenced insulin and glucagon secretory traits, the abundance of δ cells showed the strongest association with insulin secretion and was also associated with the genetic risk score (GRS) for T2D. These findings have important implications for understanding mechanisms underlying diabetes heterogeneity and islet dysfunction and may provide insight into strategies for personalized medicine and β cell replacement therapy.

  Study EGAS50000000697

• Exome sequencing of primary and relapse neuroblastoma

  In this dataset, 16 trios- primary tumor, relapse and corresponding normals- for patients with neuroblastoma are provided. For one patient, more than one relapse was available for the analyses.

  Dataset EGAD00001001607

• GATCI_Oncoscan_Data

  This dataset contains files generated from Affymetrix Oncoscan Arrays. For each sample there are two paired cel files containing the raw data from AT and GT channels. Raw data has been transfromed to OSCHP signal files also within this dataset.

  Dataset EGAD00010001579

• WGS/RNA-seq pair of an inflammatory hepatocellular adenoma (IHCA)

  This study contain the WGS and RNA-seq aligned bam files for this particular inflammatory hepatocellular adenoma sample.

  Dataset EGAD00001004141

• Epilepsy related sudden death (2019-08-21)

  These samples include exome sequences of samples from patients who suffered Sudden Unexplained Death in Epilepsy. They all are of European descent. . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005276

• Genomics Analysis Reveals Molecular Patterns of Tumorigenesis in HPV-Associated and HPV-Independent Sinonasal Squamous Cell Carcinoma

  The goal of this study was to identify molecular mechanisms of tumorigenesis in HPV-associated and HPV-independent sinonasal carcinoma using high-throughput sequencing approaches. Whole genome sequencing was performed for HPV-associated samples and whole exome sequencing for HPV-independent samples. Ultimately, we identified distinct molecular patterns of tumorigenesis between HPV-associated and HPV-independent disease. Data from patients for which informed consent allowed public sharing are included here.

  Study phs003591

• UK10K NEURO GURLING

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This sample set consists of DNA from multiply affected schizophrenia families. The families have been diagnosed using the SADS-L clinical instrument which gives diagnoses at the probable level of the research diagnostic criteria (RDC). In addition all diagnoses are available using DSMIIIR criteria. These criteria are widely accepted as being valid and reliable for the diagnosis of schizophrenia. All families have been collected to ensure that they are uni-lineal for transmission of schizophrenia, i.e. they have only one affected parent with schizophrenia, or a relative of only one transmitting or obligate carrier parent with schizophrenia. Families with bi-lineal transmission of schizophrenia (i.e. with both parents being affected) were not sampled for this study. All families have multiple cases of schizophrenia and related disorders. The families have been selected to ensure there are no cases of bipolar disorder within them and that they do not contain bipolar disorder in any relatives on either side of the family.For further information on this cohort please contact Hugh Gurling (h.gurling@ucl.ac.uk).

  Study EGAS00001000225

• Molecular Characterization of ETMRs

  ETMRs are poorly characterized embryonal brain tumors with a dismal outcome. We collected tumors from 184 ETMR patients and 23 matched recurrences to investigate the genomic landscape of this distinct entity. Tumors without C19MC amplification, the proposed driver, harbor other miRNA related aberrations like DICER1 mutations and amplifications of the MIR17-92 miRNA cluster. All tumors behave molecularly similar and no subgrouping was observed. Whole-genome sequencing revealed an overall low recurrence of SNVs, but highly prevalent R-loop associated genomic instability. Finally, we show that targeting R-loops with TOP1 and PARP inhibitors might be an effective treatment strategy for this deadly disease.

  Study EGAS00001003256

• Base modification analysis using single molecule real-time sequencing

  Based on the kinetic characteristics of single-molecule real-time sequencing, we implement a method to directly detect DNA modifications such as 5mC. However, there are room to further improve the accuracy of whole-genome-wide DNA modifications. Therefore, this study aims to utilize deep learning methods for the comprehensive profiling of multiple DNA modifications, including 5mC, 5hmC, and 6mA, using SMRT-seq.

  Study EGAS50000000366