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• HipSci___Whole_Exome_sequencing___BPD

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with blood and platelet disorders

  Study EGAS00001001976

• HipSci___Whole_Exome_sequencing___PID

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with blood and platelet disorders

  Study EGAS00001001983

• Identification of Structural Variants Relevant to Autism by Pacific Biosciences HiFi Whole-Genome Sequencing

  The purpose of this research study was to perform long-read whole-genome sequencing on a family with autism. This family had no known genetic cause based on clinical array and whole-exome sequencing analysis. Utilizing PacBio HiFi long-read whole-genome sequencing, we identified a relevant missense variant in the KCNC2 gene. This variant was likely to be a germline mosaic in the paternal germline.

  Study phs002698

• Broad utility of ultrasensitive analysis of ctDNA dynamics across solid tumors treated with immunotherapy

  Plasma ctDNA sequencing data from samples collected from a pan-cancer cohort of patients with advanced-stage disease treated with IO therapies. This study highlights the broader applicability of ultrasensitive ctDNA as a biomarker across cancer types and immunotherapy modalities. Here, we applied a whole-genome, tumor-informed approach to study ctDNA in 202 advanced-stage cancer patients treated at VHIO. This study captures the plasma sequencing data from the project.

  Study EGAS50000001271

• Leiden_melanomafamilies

  Around 10% of patients who present in melanoma clinics have a first degree relative with a previous diagnosis of melanoma. While around 3% have three or more relatives who have been diagnosed with the disease. In this project we will whole genome sequence patients from large Dutch familial melanoma pedigrees to identify mutations in genes that drive melanomagenesis. The identification of these genes will facilitate the management of familial melanoma patients and their families.

  Study EGAS00001000627

• The_genomic_architecture_of_mesothelioma_

  The genome-wide landscape of somatically acquired mutations in mesothelioma has not been deeply characterised to date, but advances in DNA sequencing technology now allow this to be addressed comprehensively. Harnessing massively parallel DNA sequencing platforms, we will identify somatically acquired point mutations in all coding regions of the genome from patients with mesothelioma. In addition, using paired-end sequencing, we will map copy number changes and genomic rearrangements from the same patients.

  Study EGAS00001000353

• Shallow whole genome sequencing

  This dataset contains a collection of tumour samples from high grade serous ovarian carcinoma patients with recurrent disease collected near the point of diagnosis as well as tumour samples collected after patient relapse upon or some time after study entry. The majority of diagnosis samples were preserved in neutral buffered formalin whereas the majority of post-relapse samples were preserved in universal molecular fixative (UMFIX, Sakura Finetek USA, Inc). DNA was extracted and whole genome sequencing libraries were prepared either using the TruSeq DNA Nano kit (Illumina) or the ThruPLEX DNA-Seq Kit (Takara Bio), which were respectively sequenced at low depth (~0.1-0.5X) on illumina HiSeq 2500 and HiSeq 4000 sequencing platforms. Sequenced reads were aligned to the GRCh37 reference genome (release hs37d5).

  Dataset EGAD00001011049

• Exome and transcriptome sequencing of CDS and ES tumor samples

  This dataset contains WES and RNASeq data of 31 CDS and ES tumor and control samples. Sequencing was performed on Illumina NovaSeq 6000. The sequencing was performed paired in bulk.

  Dataset EGAD00001015608

• Ovarian cancer sample size analysis

  The dataset contains exome sequencing fastq from 5 ovarian cancer patients, paired with tumor normal blood samples. Three tumor samples were sequenced from each patient: a biopsy sample ("-1" suffix in the file name), a local sample (multiple regions around the biopsy pooled together, with the "-2" suffix in the file name), and a global sample (multiple regions from the tumor pooled together, with a "-3" suffix in the file name).

  Dataset EGAD00001005947

• Functional and genomic heterogeneity of long-term self-renewing compartment as the origin of treatment resistance in pancreatic tumors

  Adaptive drug-resistance mechanisms allow human tumors to evade treatment through selection and expansion of treatment-resistant clones. Here, studying clonal evolution of tumor cells derived from human pancreatic tumors, we demonstrate that in vitro cultures and in vivo tumors are maintained by a common set of tumorigenic cells that can be used to establish clonal replica tumors (CRTs), large cohorts of animals bearing human tumors with identical clonal composition. Using CRTs to conduct quantitative assessments of adaptive responses to therapeutics, we uncovered a multitude of functionally heterogeneous subpopulations of cells with differential degrees of drug sensitivity. High-throughput isolation and deep characterization of unique clonal lineages showed genetic and transcriptomic diversity underlying functionally diverse subpopulations. Molecular annotation of gemcitabine-naïve clonal lineages with distinct responses to treatment in the context of CRTs generated signatures that can predict the response to chemotherapy, representing a potential biomarker to stratify patients with pancreatic cancer. RNA-Seq data on these clones are available on EBI ENA, under accession number: PRJEB27735.

  Study EGAS00001003442