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• Bulk RNA sequencing data in "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2"

  This dataset includes 14 bulk RNA sequencing data (28 fastq files) in the study entitled "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2". RNA sequencing library was generated with Truseq stranded total RNA Gold kit.

  Dataset EGAD00001006241

• Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer

  RNA sequencing data from breast cancers (n=18) and their matched HN tissues (n=36), healthy breast from cosmetic reduction mammoplasty (RM; n=5), and risk reducing mastectomies (RR, n=5), with peritumoral samples excised proximal to (TP, less than 2 cm) and distal from (TD, 5-10 cm) the primary tumor.

  Dataset EGAD00001006291

• Whole genome sequencing of adult glioblastoma nuclei

  Three primary adult glioblastoma specimens were dissociated and nuclei were extracted. A portion of the nuclei was used for single-cell ATAC seq and the remainder were submitted for whole genome sequencing, to provide orthogonal validation of copy number variations in the samples compared to single-cell ATAC seq. Samples were sequenced on the Illumina NovaSeq 6000 in paired-end mode.

  Dataset EGAD00001007651

• Single cell atlas of human glioma

  We profiled 87 primary-recurrentpatient-matched paired GBM specimens with single-nucleus RNA and bulk-DNA sequencing and single-cell open-chromatin and spatial transcriptomics/proteomics assays. We found that recurrent GBMs are characterized by a shift to a mesenchymal phenotype in response to therapy

  Dataset EGAD00001008811

• Acute myeloid leukemia bulk RNA-seq (Diagnosis and Relapse)

  To gain insight into the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs, we employed RNA-seq to longitudinally profile two t(8;21) (AML1-ETO = RUNX1-RUNX1T1), and four FLT3-ITD AML cases. All the samples are bone marrow aspirates.

  Dataset EGAD00001008374

• Healthy Never Smokers

  Bronchial brushing dataset from healthy never-smokers after exposure to diesel exhaust. Include 18 samples from 9 research participants who underwent bronchoscopy after controlled exposure to diesel exhaust. Main study design described in detail in Ryu et al 2022 AJRCCM (PMID: 35202552). This dataset was used in Hill et al Nature 2023.

  Dataset EGAD00001010024

• Pediatric Obesity Transcriptomics Data Access Committee

  The Pediatric Obesity Transcriptomics Data Access Committee is responsible for reviewing and approving requests for access to controlled-access transcriptomic and associated phenotypic data generated within the study "Circulating mRNA and miRNA signatures used as predictive markers of lifestyle modification outcomes in pediatric obesity management". Access requests are evaluated with regard to scientific merit, ethical compliance, consistency with participant consent, data protection regulations, and proposed data security measures.

  Dac EGAC50000001050

• Ultra-fast deep-learned pediatric CNS tumor classification.

  In this study nanopore sequencing was applied to obtain sparse DNA methylation profiles from pediatric CNS tumor samples. A neural network was used to classify the tumor based on the obtained methylation profile.

  Dataset EGAD00001011303

• PacBio Rare Disease Study

  This study leverages PacBio HiFi long-read sequencing technology to comprehensively analyze the genomic architecture of rare diseases. By generating highly accurate, long-read sequences, we aim to resolve complex structural variants, repeat expansions, and other genomic features that are often missed by short-read sequencing. Our approach facilitates improved variant detection and interpretation, advancing the understanding of rare disease etiology and enabling more precise genetic diagnoses.

  Dataset EGAD00001015611

• scRNA-seq dataset to study interactions between HSPCs, BMSCs and immune microenvironment

  Mechanisms of clonal evolution in myeloid neoplasms remain incompletely understood. Darwinian theory predicts that the (micro)environment of clone-propagating stem cells may contribute to clonal selection. Here, we provide data fitting this model, establishing a relationship between stromal niche inflammation, inflammatory stress in HSPCs, clonal resistance and leukemic evolution in human MDS.

  Dataset EGAD00001015770