11768 results for "cancer rna-seq"

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• RNA-Seq Pair End

  RNA analysis of two patients 11 and 15 with WGS done on Illumina HiSeq2000. For research purpose and authorised user only.

  Dataset EGAD00001003429

• Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Study EGAS00001005734

• RNA-seq data of HGG PDOX study

  Study EGAS00001004633

• Data Access Commitee Hidradenitis suppurativa RNA-Seq

  Dac EGAC00001002270

• Pheochromocytoma and paraganglioma single nuclei RNA-seq

  Dac EGAC00001002657

• COVID-19 RNA-seq Data Access Commitee

  Dac EGAC00001002979

• Integrative single-cell and cell-free plasma RNA transcriptomics elucidates placental cellular dynamics

  10 single-cell placental RNA libraries were generated using the Chromium Single Cell 3′ Reagent Kit (10X Genomics). All single-cell libraries were sequenced with a customized paired end with dual indexing (98/14/8/10-bp) format according to the recommendation by 10X Genomics. The data were aligned using the Cell Ranger Single-Cell Software Suite (version 1.0). Moreover, plasma RNA from 22 samples were extracted using the RNeasy Mini Kit (Qiagen). cDNA reverse transcription, second-strand synthesis, and RNA-sequencing (RNA-seq) library construction were performed using the Ovation RNA-seq System V2 (NuGEN) kit according to the manufacturer’s protocol. For alignment of the plasma RNA library, adaptor sequences and low-quality bases on the fragment ends (i.e., quality score < 5) were trimmed, and reads were aligned to the human reference genome (hg19) using the TopHat (v2.0.4) software. All aligned reads were deposited in bam file format.

  Dataset EGAD00001003705

• GEP-NEN Bulk-RNA-seq dataset

  This dataset entails 40 Bulk-RNA sequenced patient-derived gastro-intestinal neuroendocrine (GEP-NEN) neoplasms.

  Dataset EGAD00001006657

• Single MII oocyte mRNA expression from women

  This dataset contains 14 paired-end FASTQ sequences from mRNA-Seq on single human M-II stage oocytes that were collected from ovarian tissue from unstimulated patients undergoing fertility preservation treatments due to cancer diagnoses, which did not influence ovarian function. Cumulus-oocyte-complexes were matured in vitro according Gruhn et al (Science 365: 1466-1469) and short term flash frozen prior to lysis, RNA extraction, full length cDNA preparation and amplification using the Ultra-low-input SMART-Seq2 v4 kit from Takara Clonetech. Further, these cDNA were used to prepare libraries for sequencing according the Nextera XT DNA library preparation kit from Illumina

  Dataset EGAD00001005971

• RNA-seq analysis of human skin

  RNA sequencing analysis comparing epidermal subpopulations in normal and inflamed skin.

  Study EGAS00001002927