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• The Emirati T2T-level Pangenome: A complete Diploid Graph of 58 Genomes

  This dataset is an Emirati telomere-to-telomere (T2T) pangenome graph in GBZ format built from 116 haplotype-resolved assemblies spanning 58 individuals (28 trio-based and 30 single-sample assemblies). Assemblies were generated with long-read sequencing (PacBio HiFi and ONT ultra-long) with standard polishing, then integrated into a graph representation. The genomes show high contiguity (median ≈150 Mb) and high consensus accuracy (median QV 59). The resulting GBZ graph captures globally shared and Emirati-enriched variation, including sequence in complex regions, and serves as a population-matched reference for downstream variant discovery and annotation.

  Dataset EGAD50000001756

• Transcriptomics for IMMU-SCCHN1 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with confirmed locally recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN) who receive first-line treatment with immune checkpoint inhibitors (ICI) or ICI combined with chemotherapy. This dataset contains transcriptomics data processed with the STAR pipeline. Two sequencing kits were employed: Roche KAPA for high-quality RNA samples and Takara SMART-Seq Stranded for samples with limited RNA quantities.

  Dataset EGAD50000002206

• Bleomycin Induced Pneumonitis WGS dataset

  This is whole genome sequencing data from a cohort of 18 patients with germ cell tumours or Hodgkin Lymphoma, who developed clinically significant bleomycin-induced pneumonitis despite low clinical risk. DNA was extracted from whole blood, and 150-base paired-end reads were generated on an Illumina NovaSeq 6000 instrument to a minimum 30x depth. Sequence reads were aligned to the GRCh38 reference with BWA MEM, and germline variants were called following GATK best practice procedures. The dataset comprises per-sample read alignment files in BAM format, and a joint-called germline variant file in VCF format.

  Dataset EGAD50000002221

• Single Cell RNASeq for ARMS tumors

  6 samples from 3 mice related to Alveolar Rhabdomysarcoma. In this study, we employ scRNA-seq to analyze ARMS tumors from a conditional mouse model of ARMS. The conditional knock-in mouse model of ARMS, in which the Pax3-Foxo1 allele is activated in the skeletal muscle cell lineage via Myf6Cre (Myf6CrePax3P3Fm/P3FmTrp53F2-10/F2-10; referred to hereafter as GEMM-ARMS) has been described previously23,24. These mice also carry Cre-activated reporters, eYFP to label Pax3::Foxo1-expressing cells and dsRED2 to labels Myh2-expressing cells. Some tumors are derived from GEMM-ARMS mice, and some are allografts of GEMM-ARMS tumors into immunodeficient mice

  Dataset EGAD50000002241

• Single cell RNA-sequencing of tissues from NSCLC patients treated with chemoimmunotherapy

  The goal of this study is to characterize immune cell populations by single cell RNA-sequencing (scRNA-seq) in tumor and uninvolved normal tissues from non-small cell lung cancer (NSCLC) patients with resectable non-small cell lung cancer and who received neoadjuvant chemoimmunotherapy. scRNA-seq was performed on seven pairs of tumor and normal tissues as well as one lymph node (LN) sample. Data set includes pair-end fastq files for single cell RNA sequencing of 7 neo-immuno patients. (Total 15 samples and 50 runs).

  Dataset EGAD00001009778

• Peruvian Genome Project

  Through the Peruvian Genome Project we generate and analyze the high coverage genomes of 150 individuals where the majority have >90% Native American ancestry and explore questions at the interface of evolutionary genetics, history, anthropology, and medicine. This is the most extensive sampling of high-coverage Native American and mestizo whole genomes to date. Reference: https://doi.org/10.1073/pnas.1720798115

  Dataset EGAD00001007082

• Whole Genome Sequences of 18th century African descended individuals from Charleston, South Carolina.

  This study presents Whole Genome Sequencing results from the Anson Street African Burial Ground Project, which is a community-based initiative aimed at understanding the histories of 37 Ancestors in Charleston, South Carolina. Here we report fastq files for all 37 Ancestors. DNA was extracted at the University of Tennessee-Knoxville following Dabney et al. 2013, and dual index libraries prepared using a modified NEBNext Ultra II kit with partial USER enzyme digestion. Libraries were then enriched for human genomic DNA (MyBaits) and sequenced on Illumina Platforms.

  Dataset EGAD00001009643

• COMPARE study: participants typed during UK Biobank version 2 array development phase

  The COMPARE study enrolled 29,066 British blood between donors between February 2016 and March 2017, the study aim is to find the optimum technology for haemoglobin screening (ISRCTN 90871183). All participants were at the time of recruitment active blood donors. The 4,796 participants in this dataset have consented to join the NIHR BioResource. Genotyping data was produced using the Thermo Fisher Scientific Axiom Genotyping platform. The UK Biobank version 2 array design was used, content on this array has been added to allow for accurate DNA based identification of human blood group antigens.

  Dataset EGAD00001005023

• Subset of EGAS00001005112 (The INFORM Precision Medicine Study for High-Risk Pediatric Malignancies, 17 exomes) which is used in EGAS00001005243 (Radiation-induced gliomas represent H3-/IDH-wild type pediatric gliomas with recurrent PDGFRA amplification and loss of CDKN2A/B)

  Part of the project: The INFORM Precision Medicine Study for High-Risk Pediatric Malignancies resulted in the publication of this study: Radiation-induced gliomas represent H3-/IDH-wild type pediatric gliomas with recurrent PDGFRA amplification and loss of CDKN2A/B. This dataset contains the subset of 17 patient exome sequencing data.

  Dataset EGAD00001007864

• Chordoma Sequencing Project Whole Genome

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000721