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• Detection of maternal DNA contamination in the placenta

  We use whole-genome sequencing of monozygotic (and dizygotic) twins to detect somatic mutations to infer the cellular history of the twinning event. We recruited monozygotic twins with varying degrees of fetal membranes to compare the twinning events between theses subsets. We used blood, buccal epithelial cell, placenta, and umbilical cord to trace the embryonic somatic mutations. Using the somatic mutations from various tissues we infer the approximate timing of twinning in each monozygotic twin subtypes.

  Study EGAS00001006155

• glioblastoma single cell RNAseq

  Understanding the cellular origin and differentiation status of glioblastoma is critical to resolve the etiology of the disease. we profile 18 patient glioblastomas by single cell RNA sequencing (scRNAseq). From this, we uncovered two principal cell-of-origin relations. Each lineage displays unique directional differentiation trajectories and transcriptional cores from the naïve cell populations. Thus, glioblastoma is defined by robust cell lineage features which may provide insights into the cell origin of the diseases.

  Study EGAS00001006236

• RNA sequencing of NK cells in human lung

  Human lung tissue-resident NK cells (trNK cells) are likely to play important roles in viral infections, inflammation and cancer. However, knowledge about lung trNK cells is lacking but is fundamental for exploiting these cells in therapeutic approaches. Here we analysed the transcriptome of CD69+CD49a+CD103+CD16-CD56bright, CD69+CD49a+CD103-CD16-CD56bright, CD69+CD49a-CD103-CD16-CD56bright, CD69-CD49a-CD103-CD16-CD56bright, and CD56dimCD16+NKG2A+CD57- NK cells isolated from human lung.

  Study EGAS00001003544

• Single-cell RNA-seq of human kidney tumors

  The aim of this study is to analyze the transcriptomic information of fresh single cells originating from human clear cell renal cell carcinomas (ccRCC). Samples have been experimentally enriched in malignant cells in order to address specific questions regarding heterogeneity and clonality in ccRCC. Samples include one set of long-term frozen and thawed single cells in order to explore the impact of liquid nitrogen freezing on ccRCC single cells.

  Study EGAS00001006534

• Exome sequencing of HCV+ lymphoma

  The present retrospective study aimed to explore the genetic landscape of a well-characterized series of 34 HCV-associated B-cell lymphomas from the observational multicentric ANRS HC-13 Lympho-C Study using tumor and matched germline whole exome sequencing (WES). It reported the first series of VHC-positive lymphoma patients analyzed by WES. Our results provide an overview of the genetic landscape associated to HCV-related B-cell lymphomas and highlight some novel putative candidate genes.

  Study EGAS00001006860

• The Landscape of N-6 Methyladenosine in Primary Localized Prostate Cancer

  Using meRIP-sequencing, we profiled N-6 methyladenosine (m6A) in a cohort of 148 primary prostate cancer samples as part of the Canadian Prostate Cancer Genome Network project (CPC-GENE). Paired-end sequencing of 150 bp reads were mapped to GRCh38.p13 using annotations from gencode.v34.chr_patch_hapl_scaff.annotation.gtf. Peaks were called using MeTPeak, joint peaks were identified and IP reads were quantitated, normalized and adjusted using Input reads to obtain estimates of m6A abundance.

  Study EGAS00001006925

• PELICAN45 RNAseq Dataset

  To better understand the biology of prostate cancer, we performed RNAseq in cancerous (primary and metastatic) and noncancerous tissues in the PELICAN45 cohort. The PELICAN45 RNAseq samples include androgen-deprived metastasis samples from the PELICAN33 consenting rapid autopsy study participants, whose identifiers are A1, A2, etc. The PELICAN45 RNAseq dataset also includes data from non-androgen deprived metastases in an additional 12 men. These samples are identified as PB50, PB133, etc.

  Study EGAS00001006959

• Genetic scoring guide for personalized risk assessment in pediatric B-cell precursor Acute Lymphoblastic Leukemia

  In this study a next-generation sequencing based method was applied to comprehensively screen for recurrent, disease-relevant copy number aberrations in a cohort of Hungarian patients. Diagnostic bone marrow samples from 260 children with B-cell acute lymphoblastic leukemia and were investigated by digital multiplex ligation-dependent probe amplification using the disease-specific D007 probemix. Whole chromosome gains and losses, as well as subchromosomal copy number aberrations were simultaneously profiled.

  Study EGAS00001007239

• Possible DNA damage after paternal exposure to ionizing radiation in radar technicians

  Effects of accidental and prolonged radiation exposure on the human germline remain a topic of medical interest. Transgenerational signatures of ionizing radiation exposure are primarily implicated to be clustered de-novo mutations (cDNMs, multiple de-novo mutations within 20bp). We sequenced the whole genome of 110 children from 70 families (Radar cohort). The father in this cohort were exposed to 0-353mSv of ionizing radiation and serve as exposed samples.

  Study EGAS00001007321

• Acquisition of additional mutations drives accelerated progression of NPM1 positive CMML to AML

  This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ We performed exome sequencing on serial samples from a patient with CMML who progressed to AML. The exome sequencing suggests that NPM1, TET2 and DNMT3a mutations were present in the dominant clone in the CMML sample and that NRAS is a new subclonal mutation in the AML sample. Diagnostic data shows the presence of a FLT3-ITD mutation in the AML sample, which is likely to have driven progression. Here we are performing re-sequencing of the putative driver and some passenger mutations which appear to be in the same clone to validate these mutations and to verify the relative quantification of these abnormalities .

  Dataset EGAD00001002194