12337 results for "cancer rna-seq"

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• Epigenetic analysis of clear cell renal cell carcinoma using ChIP-seq

  To investigate the epigenetic landscape of clear cell renal cell carcinoma (ccRCC), we performed ChIP-seq data for the CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, and HIF1A marks in the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as the HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and narrowPeak formats. Data were processed using the nf-core chipseq pipeline.

  Dataset EGAD50000001886

• 5 scRNA-seq with TCR Enrichment of Tumour-Involved Lymph Nodes, Malignant Seromas and Patient-Derived Xenografts from 18 T-Cell Lymphoma Patients

  This raw data contains 5' scRNA-seq with TCR enrichment data from 18 individual patients analysing cells taken from tumour-involved lymph nodes (LN), malignant seromas and patient-derived xenografts (PDX) including systemic/nodal ALK+ ALCL (n=3 PDX), BIA-ALCL (n=2 seromas), PTCL-NOS (n=5 nodal tumours), nodal T follicular helper lymphoma - angioimmunoblastic type (nTFHL-AI) (n=1), nTFHL, not otherwise specified (nTFHL, NOS, n=1), TLBL (n=5) and 1 case of Sezary Syndrome (SS, cutaneous tumour). Droplet-based 5’ scRNA-seq with TCR enrichment (10x Chromium platform) was performed for all live cells, or the viable CD45+CD3- and CD45+CD3+ fractions following cell sorting by flow cytometry.

  Dataset EGAD00001015703

• ChIP-seq on Hodgkin lymphoma DAC

  Dac EGAC00001001007

• Henssen Lab Neuroblastoma Circle-seq Data

  Dac EGAC00001001803

• Henssen Lab Neuroblastoma Circle-seq Data

  Dac EGAC00001001804

• Human Inflammatory Skin Disease scRNA-seq

  Dac EGAC00001002309

• A capture methyl-seq protocol with improved efficiency and cost-effectiveness using pre-pooling and enzymatic conversion

  The opportunities for sequencing-based methylome analysis of clinical samples are increasing. To reduce its cost and the amount of genomic DNA required for library preparation, we aimed to establish a capture methyl-seq protocol, which adopts pre-pooling of multiple libraries before hybridization capture and TET2/APOBEC-mediated conversion of unmethylated cytosine to thymine. We compared a publicly available dataset generated by the standard Agilent protocol of SureSelect XT Human Methyl-Seq Kit and our dataset obtained by our modified protocol, EMCap, that adopted sample pre-pooling and enzymatic conversion. We confirmed that the quality of DNA methylation data was comparable between the two datasets. As our protocol, EMCap, is more cost-effective and reduces the amount of input genomic DNA, it would serve as a better choice for clinical methylome sequencing.

  Study JGAS000605

• DAC for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Data access comittee for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Dac EGAC50000000650

• RNA sequencing of mCRPC patient biopsies

  RNA sequencing of mCRPC patient biopsies obtained for the profiling of the prevalence of immune transcripts. Manuscript can be found at PMID: 35491356

  Dataset EGAD50000001811

• Single cell RNA sequencing of samples from core and periphery of human glioblastoma

  Samples taken from various regions of three human glioblastomas were subject to single cell RNA sequencing.

  Dataset EGAD50000002080