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• Single cell RNA-seq from AD and PS patients

  We applied single cell immune profiling to gain a holistic view from immune cells infiltrating the skin to circulating immune cells, facilitating a better understanding of the two diseases in their entirety, and the identification of potential type-2 or type-3-disease-driving mechanisms.

  Study EGAS00001007055

• Dataset Plasma-seq

  We performed low coverage whole genome sequencing of plasma DNA from prostate cancer patients to establish copy number profiles on both a genome-wide and a gene-specific level. The data include plasma samples from prostate cacner patients (n=13), non-malignant controls (males, n=10 and females, n=9), plasma samples from pregnancies with aneuploid and euploid fetuses (n=4). Furthermore, we sequenced different tumor samples (n=6) of one patients and a serial dilution of HT29 in a background of normal DNA (n=9).

  Dataset EGAD00001000364

• USARC 10X Genomics Single Cell DNA Sequencing Data

  We investigated the impact of ploidy heterogeneity on copy number inference at a single cell level using fluorescence-activated cell sorted (FACS) nuclei from an undifferentiated soft tissue sarcoma. FACS revealed the presence of three aberrant subpopulations, including a haploid, a near diploid and a whole genome doubled population. Once sorted, single cell nuclei underwent whole genome sequencing using the chromium CNV single cell DNA library kit (10X Genomics). We sequenced single normal nuclei (2n) and single aberrant / tumour nuclei (1n, 2n and 2n+).

  Dataset EGAD00001008668

• Comprehensive Deep Sequencing Atlas in HCC tumors

  The atlas aims to unravel the intricate genetic landscape of HCC, providing a detailed characterization of genomic alterations, transcriptomic profiles, and key mutations associated with liver tumors. The integration of WGS, RNAseq, and WES data offers a holistic perspective, facilitating a deeper understanding of the molecular mechanisms driving HCC pathogenesis. The resulting atlas serves as a valuable resource for researchers, clinicians, and the broader scientific community, contributing to advancements in HCC diagnostics, prognostics, and therapeutic interventions.

  Dataset EGAD00001015343

• Somatic Genetics of lesions from a POT1 patient (2017-04-27)

  In this project we will use exome sequencing to identify somatic mutations in lesions from a patient with a germline mutation in the protection of telomeres 1 gene (POT1). This dataset contains all the data available for this study on 2017-04-27.

  Dataset EGAD00001003307

• CD8+ Tumor-Infiltrating Lymphocyte Abundance is a Positive Prognostic Indicator in Nasopharyngeal Cancer

  This retrospective tissue study explores the prognostic significance of tumour-infiltrating lymphocyte (TIL) populations in NPC, using a combination of RNA sequencing and immunohistochemistry.

  Study EGAS00001006396

• Somatic Genetics of lesions from a POT1 patient (2016-04-20)

  In this project we will use exome sequencing to identify somatic mutations in lesions from a patient with a germline mutation in the protection of telomeres 1 gene (POT1). This dataset contains all the data available for this study on 2016-04-20.

  Dataset EGAD00001002050

• Clinical exome profiling of 7 members of a family with cases of familial Alzheimer's disease

  This dataset includes "clinical exome" profiling (approximately 4000 genes related to diseases) on individuals (n=7) from a family with a familial history of Alzheimer's disease. Two affected cases ad five cases without dementia are included.

  Dataset EGAD00001005320

• WGS Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015442

• ASTAR Skin Research Laboratory

  Data Access Committee for A*STAR Skin Research Laboratory, A*STAR Research Institutes, Singapore.

  Dac EGAC50000000109