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• scRNAseq of distal colon biopsies from patients with ulcerative colitis and healthy controls

  scRNAseq dataset of colonic epithelium from distal colon biopsies from 4 patients with ulcerative colitis and 4 healthy individuals. Includes 11 samples split into three conditions: healthy, healthy margin and ulcerated. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into 4 lanes and into index (I1) and read (R1, R2) files. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Cell Ranger (v3.0.1) software from 10x Genomics was used to process the output and align the reads. The refdata-cellranger-GRCh38-3.0.0 reference was downloaded from the 10x Genomics website. First, cellranger mkfastq function was used to demultiplex raw base call files into FASTQ files. Then, the FASTQ files were aligned and filtered with cellranger count function.

  Dataset EGAD00001010167

• DNA and RNA sequencing data from Ovarian Carcinosarcoma patients from the Glasgow Cohort.

  In this study, we analysed DNA and RNA sequencing data from Ovarian Carcinosarcoma patients, from isolated carcinoma and sarcoma components and investigated DNA variants as well as gene expression. Genomic analyses from this data and further investigation from preclinical models of ovarian carcinosarcoma support the conversion theory for disease development and indicate that microtubule inhibitors could be used to suppress EMT and stimulate anti-tumour immunity.

  Study EGAS00001006605

• Structural variants

  Structural variants assessed in 6 patient samples with varying phenotypes, through the use of sniffles2 with a support parameter of 1 and at a length of 30 bp

  Dataset EGAD50000000741

• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Glioblastoma patient derived Fast/Slow cycling cancer stem cell RNA sequencing. Consists of 3 patient cell lines and 6 files

  Dataset EGAD00001004380

• Fred Hutchinson Cancer Research Center - Whole-Exome Sequencing of Hereditary Prostate Cancer Families

  The specific aim of this study is to identify hereditary prostate cancer (HPC) susceptibility genes using a novel study design, whereby whole-exome sequencing will be undertaken on multiple affected relatives from 19 HPC families, in which ≥ 3 affected relatives were diagnosed with clinically aggressive and/or early onset prostate cancer (PC). While whole-exome sequencing of unrelated affected individuals would result in hundreds of candidate disease variants, this family-based, aggressive/early onset phenotype approach will provide an enriched genetic background for discovery and significantly reduce the number of candidate mutations that will require follow-up. Findings from this pilot study will immediately be followed-up to confirm whether candidate mutations found in each family segregate with disease in the remaining unscreened relatives. As part of this pilot study, we aim to: Perform whole-exome sequencing on 80 affected and 11 unaffected relatives from 19 HPC families that have multiple men diagnosed with an aggressive and/or early onset disease phenotype using the Illumina HiSeq platform; and, Analyze sequencing data using BWA, SAMtools and SeattleSeq to prioritize candidate HPC mutations that segregate with aggressive and/or early onset disease in affected relatives.

  Study phs000350

• Early Family Prevention of Adolescent Alcohol, Drug Use, and Psychopathology

  The Early Steps Multisite Study is comprised of researchers from the University of Virginia, the University of Pittsburgh, Arizona State University, and Oregon Research Institute. This longitudinal study has been funded by the National Institute on Drug Abuse at the National Institutes of Health since 2002. The Early Steps Multisite Study conducted a randomized control trial to examine the effects of an intervention program called the Family Check-Up (FCU) offered in early to middle childhood. Outcomes include problem behaviors including substance use. Primary caregivers (PC) and their children (TC) were recruited from Women, Infant, and Children's (WIC) Nutritional Supplement centers in and around Pittsburgh, PA, Eugene, OR and Charlottesville, VA when target participating children were age 2. Participants were screened in three key areas of risk for later child conduct problems: (1) sociodemographic risk (e.g., poverty, teen parent status), (2) family risk (e.g. maternal stress, depressive symptoms), and (3) child conduct problems. Randomization to the intervention condition was balanced on gender to assure an equal number of males and females in the control and intervention groups. Data submitted to dbGaP are from the 515 subjects who were consented to provide a saliva sample.

  Study phs003442

• Genomic_characterisation_of_MGUS__

  he hematological malignancy multiple myeloma (MM), also called Kahler’s disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Study EGAS00001004124

• Genomic profiling of patient-derived xenograft models of myxoid liposarcoma either sensitive or resistant to trabectedin

  The dataset consists of two patient-derived xenograft model of myxoid liposarcoma one sensitive and one resistant to trabectedin. Both models underwent the same treatment schedule with trabectedin (tree time points and one treatment with doxorubicin). We performed genomic profiling using Agilent OneSeq assay.

  Dataset EGAD00001005099

• Characterization of the molecular signature of human monocytes in aging and myelodysplastic syndrome

  Deep immunophenotypic profiling of peripheral blood immune cells from young and older control subjects as well as patients with MDS was initially performed, using mass cytometry to identify monocyte subpopulations. Abundance of monocyte subpopulations separated the samples from patients with MDS from elderly control subjects was identified. Therefore, targeted immunophenotyping of monocytes was also performed with flow cytometry and RNA sequencing from isolated CD14+ peripheral blood longitudinally in 26 subjects, six young healthy individuals, nine older healthy individuals and eleven patients with MDS.

  Study EGAS00001007676

• Datasets of RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  RNA-seq analyses were performed on tumor tissue samples of 115 advanced clear cell renal cell carcinoma patients who participated in the NIVOREN GETUG-AFU-26 trial. The samples were obtained prior to treatment initiation. RNA-seq was performed to evaluate previously published gene expression signatures. These included: the IMmotion T effector (CD8A, EOMES, PRF1, IFNG and CD274) and the IMmotion Myeloid (IL-6, CXCL1, CXCL2, CXCL3, CXCL8, and PTGS2) gene signatures represent gene expression patterns associated with T effector cells and myeloid cells, respectively, while JAVELIN Renal 101 Immuno (T-cell receptor signaling: CD3G, CD3E, CD8B, THEMIS, TRAT1, GRAP2, CD247; T-cell activation, proliferation, and differentiation: CD2, CD96, PRF1, CD6, IL7R, ITK, GPR18, EOMES, SIT1, NLRC3; Natural killer cell mediated cytotoxicity: D2, CD96, PRF1, CD244, KLRD1, SH2D1A; Chemokine: CCL5, XCL2; and Other immune response genes: CST7, GFI1, KCNA3, PSTPIP1) represents gene expression patterns associated with both innate and adaptive immune response.

  Dataset EGAD50000001541