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• _WGS__Somatic_mutation_in_skin_epidermis__SMS_

  Previously we have sequenced 2mm2 biospies of human epithelia at high depth using a custom bait set. This has identified a range of mutations. Some of the biospies are predicted to be clonal and we would like to perform WGS to give an insight into mutational burden, and CNV which may be associated with these mutations.

  Study EGAS00001004464

• LongVar low-coverage data

  This dataset includes sequencing data from participants of the LongVar study. Specifically, it comprises low-coverage whole genome sequencing (WGS) data which was derived from cell-free DNA from blood samples. These data were generated to compare imputation accuracy. 133 individuals agreed to share their data, and are healthy volunteers.

  Study EGAS50000001114

• Liquid-based genomic profiling in high-risk localized prostate cancer.

  In this study, we evaluated the feasibility and performance of tissue and liquid-based genomic profiling in patients with high-risk localized prostate cancer. Genomic DNA from 12 FFPE tissue samples and cell-free DNA from 27 plasma samples were analyzed using Illumina TruSight Oncology (TSO) 500 panels.

  Study EGAS50000001712

• HipSci-RNAseq-healthy volunteers

  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 sup-study we perform RNAseq on iPS cells generated from skin biopsies from healthy volunteers.

  Study EGAS00001000593

• Pediatric B-cell precursor acute lymphoblastic leukemia samples with very early relapse

  In this study we performed a genomic analysis of diagnosis-relapse pairs of 12 children who relapsed very early, followed by a deep-sequencing validation of all identified mutations. In addition, we included one case with a good initial treatment response and on-treatment relapse at the end of upfront therapy.

  Study EGAS00001005615

• Pulmonary Fibrosis and Telomerase Dysfunction

  This study was used to perform an exome-limited analysis of whole genome sequencing data of patients with idiopathic pulmonary fibrosis (IPF) or familial pulmonary fibrosis. Case cohorts were derived from local centers at University of Southwestern or Columbia University, and subjects were from the IPFnet cohort of clinical trial. Rare damaging mutations in the coding regions of cases were compared to healthy controls, and gene burden analysis was performed to identify enrichment of novel risk genes in the development of pulmonary fibrosis. 

  Study phs002692

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

  Neutrophils and monocytes are critical contributors to the pathophysiology of sickle cell anemia (SCA) and are persistently elevated in patients' circulation. While chronic hemolysis has been implicated in this leukocytosis, the underlying mechanisms remain incompletely understood. Our data show a myeloid-skewed transcriptional signature in early progenitor populations, including multipotent progenitors (MPPs) and hematopoietic stem cells (HSCs). Notably, we identify upregulation of the type I interferon signaling pathway in HSPCs as a key driver of early myeloid programming in SCA.

  Study EGAS50000001046

• WES of breast cancer patients and controls

  This study assessed the variant profiles of 408 samples from 126 breast cancer patients with various survival outcomes, including paired uninvolved mammary gland samples collected at proximal distances from primary lesions. As a reference, control samples from 15 mammoplasty individuals without cancer history were studied. Whole exome sequencing was performed to identify post-zygotic and germline variants present in the studied samples. Variant annotation in known databases, interpretation, and statistical analyses followed to discern the clinical relevance of called variants.

  Study EGAS50000000539

• Mutational spectrum of highly differentiated, fusion-negative rhabdomyosarcoma (set 1).

  Pediatric PAX-FOXO1 fusion-negative rhabdomyosarcoma represents a diverse spectrum of tumors. In this study, the mutational spectrum of 22 fusion-negative rhabdomyosarcomas with high, rhabdomyoma-like levels of differentiation was evaluated using OncoPanel v.2 (OPv2), an Agilent SureSelect custom designed bait set consisting of the coding regions of 504 cancer-relevant genes. Corresponding normal tissue was not available. Discarded normal human skeletal muscle, obtained from 7 donors without tumor history, were also included in the sequencing run.

  Study EGAS00001002630

• Mutational spectrum of highly differentiated, fusion-negative rhabdomyosarcoma (set 2).

  Pediatric PAX-FOXO1 fusion-negative rhabdomyosarcoma represents a diverse spectrum of tumors. In this study, the mutational spectrum of 22 fusion-negative rhabdomyosarcomas with high, rhabdomyoma-like levels of differentiation was evaluated using OncoPanel v.2 (OPv2), an Agilent SureSelect custom designed bait set consisting of the coding regions of 504 cancer-relevant genes. Corresponding normal tissue was not available. Discarded normal human skeletal muscle, obtained from 7 donors without tumor history, were also included in the sequencing run.

  Study EGAS00001002771

• Lung_Cell_Atlas__Paediatric_RNA

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets

  Study EGAS00001008299

• Lung_Cell_Atlas__Paediatric_Spatial

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets

  Study EGAS00001008300

• IFN-γ and TNF-α drive a CXCL10+ CCL2+ Macrophage Phenotype Expanded in Severe COVID-19 Lungs and Inflammatory Diseases with Tissue Inflammation

  We explored how the human macrophages response to different inflammatory factors, focusing particularly on the effects of antiviral interferons (IFN-β and IFN-γ), pro-inflammatory cytokines such as TNF-α, and other mediators like IL-4. Co-cultured fibroblasts were a component in some conditions to generate factors produced by resident stroma. We used a single-cell antibody-based hashing strategy to multiplex samples from different stimulatory conditions in one sequencing run. This macrophage transcriptomic data reveals distinct macrophage activation states and polarizations shaped by different tissue-related inflammatory conditions at single-cell resolution. We further performed an unbiased integration between tissue-level macrophages and this stimulated human blood-derived macrophages, which pinpoint an IFN-γ and TNF-α synergistically driven inflammatory macrophage phenotype expanded in severe COVID-19 lungs and other inflamed disease tissues.

  Study phs002780

• Xeroderma Pigmentosum, Complementation Group C, (XPC) and Non-XPC Cutaneous Squamous Cell Carcinoma (cSCC) Mutation Rate Study

  Base mutations occur at higher frequencies within heterochromatin and late-replicating DNA. In this study, we show that regional differences in mutation frequency are absent in portions of the genome that are not transcribed within cutaneous squamous cell carcinomas (cSCCs) with an XPC-\- genetic background. The XPC-\- genetic background predicates a loss of global genome nucleotide excision repair (GG-NER), thus our data shows that regional differences in mutation frequency are a result of differential access of DNA repair protein. Unexpectedly, we also note that greater transcription reduces mutations on both strands of genes in heterochromatin, and only to those levels observed in euchromatin, in a XPC-dependent fashion. Therefore, transcription likely reduces mutation prevalence by increasing access to DNA repair proteins. This tripartite relationship between DNA repair, transcription, and chromatin state shows a new cancer risk factor in human populations.

  Study phs000830

• Long-Read Sequencing to Identify Inherited Mutations Predisposing to Breast Cancer

  We aimed to detect deeply intronic mutations within genes linked to breast/ovarian cancer that are potentially under-reported in clinical testing due to technical limitations. Current DNA and RNA tests typically exclude these regions, which harbor many variants within complex repetitive sequences that short-read sequencing cannot align. By employing targeted long read sequencing together with recent in silico prediction tools, we assessed the implications of rare deep intronic variants in severely affected patients with breast, ovarian, and/or metastatic prostate cancer, who had previously tested negative using standard genomic or cDNA methods. Through this approach, we identified participants who carried deep intronic mutations in tumor suppressor genes, resulting in abnormal transcripts causing premature truncations and loss of gene function. This study underscores the potential of long read DNA and cDNA sequencing in enhancing mutation discovery efforts.

  Study phs003638

• UTSW KCP DAC

  This DAC manages access to WES and RNA-Seq data from studies approved under the IRBs of KCP principal investigators.

  Dac EGAC50000000203

• Exome sequencing Parkinson's disease patients

  In this project we will sequence the exomes of 250 patients with Parkinson's disease

  Dataset EGAD00001000405

• Genomic Landscape of Chordoid Glioma

  This data set consist genomic information of 10 Chordoid Glioma samples: - Exome sequencing: 10 tumors and matched normal DNA for four of them (BAM files) - RNAseq : 10 tumors (fastq files) - CNV array: 9 tumors (IDAT files)

  Dataset EGAD00001004112

• Integrative genomic study of CML patients

  This dataset contains WES and RNA-Seq fastq files for 65 CML patient samples at various stages of disease progression.

  Dataset EGAD00001004179

• SMRT-seq

  In this study, we enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model.

  Dataset EGAD00001006875

• Ampliseq library database

  This database contains 46 samples for early stage ovarian high grade serous carcinoma project. Amplicon sequencing on 37 tumour samples from early stage ovarian high grade serous carcinoma as well as 5 adjacent normal tissue samples and 4 whole blood samples.

  Dataset EGAD00001008587

• Immune single-cell profiling of human chronic inflammatory skin disease

  This dataset includes 10X Genomics 3' single cell-RNA-seq profiles from 24 human rashes and 7 healthy controls. BAM files are provided for each sample.

  Dataset EGAD00001008624

• Transcriptome Analysis of CLL patient samples

  This dataset includes Illumina RNA Sequencing Data for 59 chronic lymphocytic leukemia patient samples. 57 samples are single end, 2 samples are paired end sequencing.

  Dataset EGAD00001008320

• CBD-RAW-RNASEQ: Bulk RNAseq data

  Bulk RNAseq data from whole blood. For further information regarding this dataset, please contact Katie Burnham and Andew Kwok at contact@combat.ox.ac.uk.

  Dataset EGAD00001007957

• CBD-RAW-SC-ATAC: 10X Single-Cell ATAC

  Raw Illumina sequencing data from single-cell ATACSeq experiments. For further information regarding this dataset, please contact Julian Knight and Tatjana Sauka-Spengler at contact@combat.ox.ac.uk.

  Dataset EGAD00001007963