12215 results for "cancer rna-seq"

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• Data access to Small RNA-Seq of MicroRNA's in Tear EV's of Ushers Syndrome patients

  Via this DAC you can get access to Small RNA-Seq dataset of MicroRNA's in Tear EV's of Ushers Syndrome patients. The study involved genetically confirmed USH1B patients and their healthy relatives, with additional fibroblast samples from Spanish collaborators, to ensure a robust comparison of small non-coding RNAs (sncRNAs). Tear and blood samples were collected using non-invasive methods, and extracellular vesicles (EVs) were isolated from both tears and hiPSC-derived retinal pigment epithelium (RPE) cells. RNA was extracted from these EVs and assessed for quality before preparing libraries using the TruSeq Small RNA Library Preparation Kit. Sequencing was performed on the Illumina NextSeq 2000 platform, generating data for comparative analysis of sncRNA profiles between patients and controls.

  Dac EGAC50000000711

• scRNA-seq Next GEM-X Flex

  Single-cell RNA sequencing (scRNA-seq) was generated using the 10x Genomics GEM-X Flex Gene Expression Multiplexed platform

  Dataset EGAD50000001186

• scRNA-seq Next GEM Single Cell 3ʹ

  Single-cell RNA sequencing (scRNA-seq) was generated using the 10x Genomics Chromium Next GEM Single Cell 3ʹ platform

  Dataset EGAD50000001185

• Pharmacogenomics of T-ALL

  Whole exome seq (N=21) and RNA-seq (N=36) data of additional T-ALL

  Dataset EGAD00001006434

• Microbiome-Host Interactions in Oral Squamous Cell Carcinoma: a Metatranscriptomic Exploratory Study

  Oral cancer (predominantly squamous cell carcinoma; OSCC) is the 14th most prevalent malignancy worldwide, accounting for more than 300,000 new cases and 145,000 deaths annually. Despite advances in cancer treatment modalities, OSCC continues to have poor prognosis with 5-year survival rates less than 50%. Although use of tobacco and alcohol consumption constitute the major risk factors, there is emerging evidence for the role of the microbiome in OSCC. However, studies on the association between the microbiome and OSCC has so far focused on compositional analysis and has been largely limited to the bacterial component of the microbiome. The aim of this study is to characterize the transcriptional activity (function) as well as composition of the multi-kingdom microbiome associated with OSCC and correlate it with the gene expression of the host using ultra-deep metatranscriptome sequencing, which will provide new insight into the role of the microbiome in OSCC and the possible mechanisms by which the tumor’s microbial community may influence on its behavior. This project comprises RNA-Seq data from twenty OSCC tumor/normal tissue pairs and twenty tongue scraping samples from healthy controls. However, due to consent constraints, the human sequences from the control data are filtered out.

  Study phs002678

• 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

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

  Study EGAS00001005066

• RNA profiles of human placentas

  This DAC addresses the control of the access to the RNA-seq of the human placentas. It covers the project "Decoding human placental cellular and molecular responses to maternal obesity and fetal growth"

  Dac EGAC50000000505

• HCC.GNE RNA-Seq

  RNA-Sequencing data (raw read sequences) for 23 samples, from 12 patients, for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma"

  Dataset EGAD00001000886

• RNA-seq of pcAECyTCL

  RNA sequencing of frozen tumor biopsies from patients with primary cutaneous CD8+ aggressive epidermotropic cytotoxic T-cell lymphoma. 6 samples. Illumina HiSeq 4000.

  Dataset EGAD00001006085