11951 results for "cancer rna-seq"

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• Psoriasis Patient PBMC scRNA-seq data

  This dataset contains raw and processed data of four scRNA-seq PBMC samples from four Psoriasis patients (Pso3 = male, Pso4 = female, Pso7 = female, Pso8 = male). Raw sample libraries were prepared with 10x 5'-kit v2 multiplexing the individual samples using TrueSeq barcoded antibodies to stain the cells. Resulting sequencing data consists of four FASTQs (2 x antibody multiplex to demultiplex the samples + 2 x transcriptome data containing the typical cell x UMI barcode data for count matrix generation). The raw sequencing data was processed with cellranger 6.0.1 with the GRCh38 3.0.0 reference and cell to sample assignment was subsequently done with couhto 1.1.0 (https://github.com/dmalzl/counhto) employing the same algorithm as cellranger multi (couldn't be used here though as multi does not handle 5'-chemistry data). Processed data contains all main outputs of cellranger count in raw text format or in h5 formats including the used feature reference for (i.e. antibody barcode to sample assignment) as well as the computed cell to sample assignment computed by counhto. For further details including all used code in the analysis of the data please consult https://doi.org/10.5281/zenodo.13846873

  Dataset EGAD50000001102

• Feasibility study of enzymatic methylation sequencing of cell-free DNA from cerebrospinal fluid of pediatric brain tumors for classification

  Array-based DNA methylation profiling is the gold standard for molecular classification of brain tumors. However, it relies on significant amount of input DNA extracted from surgical tissue, thus limiting its use for tumors where biopsy is challenging or limited in quantity. Cell-free tumor DNA (cfDNA) in cerebrospinal fluid (CSF) presents alternative opportunities for brain tumor diagnosis and disease monitoring following treatment. Novel enzymatic DNA methylation sequencing (EM-seq) methods may allow us to overcome input DNA limitations and accurately quantify methylation from cfDNA for tumor classification.

  Study EGAS50000000871

• scRNA seq and scTCR seq data from 5 melanoma patients

  The Chromium Controller and Chromium X platfor of 10X Genomics were used for single cell partitioning and barcoding. Each cell's transcriptome was barcoded during reverse transcription, pooled cDNA was amplified and Single Cell 5' Gene Expression (GEX), V(D)J and Feature Barcode (FB) Libraries were prepared according to the manufacturer's protocols (CG000330 and CG000331, 10X Genomics). All libraries were quantified and normalized on library QC data generated on the Bioanalyzer system according to manufacturer's protocols (G2938-90321 and G2938-90024, Agilent Technologies). Based on the expected target cell counts, a balanced library sub-pool of samples was compsed for SC5'GEX, V(D)J and FB libraries. Library sub-pools were quantified by qPCR, accodring to the KAPA Library Quantification Kit Illumina(R) Platforms protocol (KR0405, KAPA Biosystems). Based on qPCR results a final sequencing pool was composed. Paired end sequencing was performed on a NovaSeq 6000 Instrument (Illumina) using NovaSeq 6000 Reagent Kits v1.5 100 cycles (cat. no. 20028401, 20028319, 20028316 Illumina), using 28 cycles for Read 1, 10 cycles for Read i7, 10 cycles for Read i5 and 90 cycles for Read 2.

  Dataset EGAD50000001155

• M116 scRNA-seq

  scRNA-seq was performed using Chromium Next GEM Single Cell 3’ Kit v3.1 (10X Genomics) according to the manufacturer’s instructions. Briefly, M116's PBMCs were thawed and quantified in order to calculate the number of cells to be loaded. Then, barcoded Single Cell 3ʹ Gel Beads, a master mix containing PBMCs, and Partitioning Oil were combined onto the Chromium Next GEM Chip G to generate Gel Beads-In-Emulsion (GEMs), where polyadenylated mRNAs were reverse transcribed. This way, all generated cDNAs from the same cell shared a common 10X Barcode. Following the reverse transcription, GEMs were broken and cDNAs were amplified and cleaned up with SPRIselect beads (Beckman Coulter®). Next, a portion of these cDNAs were enzymatically fragmented and subjected to adaptor ligation before using them as a PCR template for the incorporation of i5/i7 indexes. Finally, libraries were purified with SPRIselect beads, quantified and quality checked by using the 2200 TapeStation (Agilent®), and subjected to paired-end 150-bp sequencing (Novaseq systems, Illumina®) following standard practices at external facilities (Novogene®). Files types included in this dataset are raw Fastq files.

  Dataset EGAD50000001289

• Ibrutinib induces a global chromatin reorganisation in chronic lymphocytic leukaemia

  Chronic lymphocytic leukaemia (CLL) is the most common haematological malignancy in developed countries. Ibrutinib (PCI-32765), a specific and irreversible inhibitor of Bruton's Tyrosine Kinase (BTK) represents a major step forward in the treatment of CLL. We have undertaken a detailed analysis of the changes happening to the chromatin structure in CLL cells from patients continuously receiving oral doses of ibrutinib. ChIP-seq has been performed for H3K4me3, H3K27ac, H3K27me3 and EZH2 . We observed that Ibrutinib-dependent lymphocytosis correlates with a global and transient recruitment of EZH2 to active cis-regulatory elements and increased H3K27me3.

  Study EGAS00001002827

• Selective advantage of mutant stem cells in human clonal hematopoiesis is associated with attenuated response to inflammation and aging

  In this study we characterised the consequences of DNMT3A- and TET2-mutations in human clonal haematopoiesis. We screened 195 bone marrow samples for mutations by targeted DNA sequencing, and sequenced 99 paired peripheral blood samples to compare mutation detection between bone marrow and blood. We performed single-cell analysis with TARGET-seq+ on 13 samples (4 controls and 9 clonal haematopoiesis samples), which combines single-cell genotyping for targeted mutations with whole transcriptome sequencing on FACS sorted cells. Single-cell genotyping and transcriptomes were sequenced separately and linked by common single-cell identifiers.

  Study EGAS00001007358

• Dr. Fatima Mechta-Grigoriou, PhD, DR1 Head of Stress and Cancer Laboratory Deputy Director Genetic and Biology of Cancer Dpt Institut Curie - Inserm U830

  Dac EGAC00001000581

• ICGC prostate cancer whole genome sequencing

  ICGC prostate cancer whole genome sequencing

  Dataset EGAD00001000306

• Converging and evolving immuno-genomic routes towards immune escape in breast cancer

  Data access committe for the project: Converging and evolving immuno-genomic routes towards immune escape in breast cancer

  Dac EGAC50000000074

• Thoracic Patient-Derived Xenografts

  Targeted capture sequencing of 341 cancer associated genes in thoracic patient-derived xenografts.

  Study phs001192

• scRNAseq of ovarian cancer patient derived organoids

  scRNAseq of ovarian cancer patient derived organoids with or without estradiol

  Dataset EGAD50000002058

• Genentech gallbladder cancer study - whole genome sequencing

  Genentech gallbladder cancer study - whole genome sequencing

  Dataset EGAD00001004855

• Plasma methylome of metastatic prostate cancer

  The dataset contains plasma DNA methylation data derived from metastatic prostate cancer patients.

  Dataset EGAD00001005433

• 65 prostate cancer cases wgs sequencing

  65 prostate cancer cases wgs sequencing

  Dataset EGAD00001000983

• 65 prostate cancer cases wgs sequencing

  65 prostate cancer cases wgs sequencing

  Dataset EGAD00001001004