12101 results for "cancer rna-seq"

in 13.33 milliseconds.

• Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

  We performed scRNA-seq of patient-derived glioblastoma cells alone or after co-culture with human iPSC-derived cerebral organoid cells. Transcriptional changes implicated in the invasion process that are coherent across patient samples indicate that GBM cells reactively upregulate genes required for their dispersion. Potential interactions between GBM and organoid cells identified by an in silico receptor-ligand pairing screen suggest functional therapeutic targets.

  Study EGAS00001003852

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000947

• GEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the GEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008418

• ADT/SPEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the ADT/SPEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008419

• An integrated single-cell reference atlas of the human endometrium

  This dataset includes both the anchor scRNA-seq and snRNA-seq datasets used to build the Human Endometrial Cell Atlas (HECA). HECA provides a comprehensive definition of endometrial cell types and states throughout the menstrual cycle in donor with and without endometriosis. It identifies consensus cell types across datasets generated by teams worldwide, as well as previously unreported cell types, all of which are validated and mapped in situ using spatial transcriptomics. Processed data is available from ArrayExpress with accession number E-MTAB-14039. See Marečková, M., Garcia-Alonso, L., Moullet, M. et al. An integrated single-cell reference atlas of the human endometrium. Nat Genet 56, 1925–1937 (2024) https://doi.org/10.1038/s41588-024-01873-w for more information.

  Dataset EGAD00001015446

• Time Lapse to Cancer-Defining the Transition from Polyp to Cancer

  In the US, CRC incidence has declined with uptake in colonoscopy for early detection and removal of polyps, the precursor lesion, can stop a cancer from developing but in spite of this, CRC remains the second leading cause of cancer death in the United States. One third of people who undergo screening colonoscopy will have adenomatous polyps, but less than 5% of the time are these polyps presumed to go on to develop into cancer. Why does one polyp develop into cancer while another one that looks very similar does not. In this proposal we will identify what molecular genetic changes in the genome, in the mRNA expression and genetic methylation patterns will distinguish a polyp that has already transformed into cancer from one that has not.

  Study phs001384

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• Multi-omics RNA profiling of glioblastoma patient tissues

  Multi-omics profiling of paired primary and recurrent glioblastoma patient tissues

  Dataset EGAD00010001895

• TXT_CD138N_15

  TPM matrices of counts from RNA sequencing (RNAseq) from longitudinal CD138(–) BM fractions.

  Dataset EGAD00001011145

• SNF_RNAseq_CD138n_20f

  TPM matrices of counts from RNA sequencing (RNAseq) from baseline CD138(–) BM fractions.

  Dataset EGAD00001011142