4991 results for "*oma"

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• RNA-seq in insulinomas

  RNA-seq datasets in human insulinoma samples

  Dataset EGAD50000000462

• WGS in insulinomas

  Whole-Genome Sequencing datasets of insulinoma samples and paired blood controls

  Dataset EGAD50000000464

• Investigating differential diagnostic and prognostic biomarkers in primary cutaneous follicle center lymphoma and follicular lymphoma using low-coverage whole-genome sequencing

  In this study, we analyzed 28 primary cutaneous follicle center lymphoma samples from 20 patients and compared the copy number profiles to a cohort of diagnostic samples of 64 nodal follicular lymphoma patients using low-coverage whole genome sequencing (lcWGS).

  Dataset EGAD50000000199

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD50000000201

• Longitudinal sampling in relapsed and refractory Hodgkin lymphoma

  Ultra-deep next-generation panel-sequencing on 59 FFPE-samples (20 LTR, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. Data was processed as described in the publication and mark duplicated bam files were uploaded.

  Dataset EGAD50000000210

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 3)

  Whole genome sequencing data of 25 high-grade serous carcinoma (HGSC) patients (65 samples) sequenced with Illumina Novoseq 6000

  Dataset EGAD50000000211

• Ovarian carcinoma

  Genome-wide NanoRCS of cfDNA from ascites of Ovarian cancer patients

  Dataset EGAD50000000219

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Dataset EGAD50000000226

• ScRNA-seq of human kidney immune cells of patients with ANCA-associated glomerulonephritis, Lupus Nephritis against a healthy nephrectomy control

  ANCA-associated glomerulonephritis (AGN) associates with a high risk of end-stage kidneydisease. The role of kidney immune cells in local inflammation remains unclear. This study investigates kidney immune cell diversity and function. Kidney tissue from AGN patients (n=5) and a lupus nephritis (LN) patient (n=1) were aquired during a biopsy procedure for a clinical indication. Needle-core biopsies were obtained for histopathological examination, and an additional pass was performed to retrieve kidney tissue for scRNA-seq. Healthy kidney tissue (n=1) was obtained from a kidney that was surgically removed do tue due to a (non-invasive) papillary urothelial carcinoma. Immediately after collection, kidney tissue was processed into a single-cell suspension and sorted using a 4-color flow cytometry panel to isolate living, CD45+immune cells. To aid in the multi-omic characterization, surface markers and T and B cell repertoires were sequenced in 2 samples (1 AGN patient and the nephrectomy control). These samples were incubated with an oligo-antibody TotalSeq-C cocktail containing 130 unique cell surface antigens.

  Dataset EGAD50000000229

• Dataset for central nervous system glioma samples

  This dataset contains VCF files for 124 central nervous system glioma samples for the study "Cerebrospinal fluid cfDNA sequencing for classification of central nervous system glioma"

  Dataset EGAD50000000085