11973 results for "cancer rna-seq"

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• RNA-seq of oropharynx cancer cases from University of Michigan

  This dataset consists of 67 bulk RNA-seq data (sorted aligned BAM files) from formalin-fixed paraffin-embedded (FFPE) oropharynx tumor samples from the University of Michigan (UM). Samples were collected as part of the UM Head and Neck SPORE between 2008-2014. Library preparation was performed using the ribo-depletion method with the FastSelect kit and sequenced on the NovaSeq 6000 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v3.4) and aligned to hg38 and high-risk HPV genomes using STAR (v2.7.9a). 62 of 67 samples were determined to be HPV RNA-positive.

  Dataset EGAD50000001306

• June 2016 data update for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  June 2016 data update (bam/fastq for CEMT0062, CEMT0068, CEMT0072, CEMT0086, CEMT0087 ChIP-Seq and RNA-Seq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001002239

• Comprehensive RNA repository of tissue and plasma from patients with esophageal cancer or precursor lesions

  A comprehensive RNA repository (both coding and non-coding) from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were collected. This dataset includes both mRNA and small RNA sequencing data (fastq.gz files) of all tissue and plasma samples. In total,102 RNA-seq libraries from 51 samples (17 plasma and 34 tissue samples) were sequenced (plasma mRNA libraries were sequenced twice).

  Dataset EGAD00001006857

• BLUEPRINT EpiVar RNA-seq for Naive naive CD4+ T-cells

  BLUEPRINT EpiVar RNA-seq for Naive naive CD4+ T-cells

  Study EGAS00001000752

• High-grade serous ovarian cancer refined with single-cell RNA-sequencing

  We performed single-cell RNA-sequencing of 18,403 cells unbiasedly collected from 7 treatment-naive HGSOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. Next, we explored which phenotypic clusters correlate with overall survival based on expression of these transcriptomic markers in 1467 bulk RNA-seq tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

  Study EGAS00001004987

• In this study single cell RNA-Seq data was used to train a deconvolution algorithm. The algorithm was validated on paired bulk RNA-Seq profiles.

  In this study single cell RNA-Seq data was used to train a deconvolution algorithm. The algorithm was validated on paired bulk RNA-Seq profiles.

  Dataset EGAD00001009688

• RNA-Seq - Characterization of a Breast Patient-derived Tumor Organoid biobank from an underserved population of patients

  RNA-seq datasets of patient and patient-derived organoids

  Study EGAS50000000683

• van Hijfte GBM dataset 2022/A (single-nucleus RNA-seq)

  van Hijfte GBM dataset 2022/A (single-nucleus RNA-seq) 1x GBM

  Study EGAS00001006920

• CASCADE tumour transcriptome data

  RNA-Seq data from 20 fresh-frozen postmortem samples from three patients who participated in the CASCADE rapid autopsy program and died of metastatic castration resistant prostate cancer.

  Dataset EGAD00001009492

• Drug-induced epigenomic plasticity reprograms circadian rhythm regulation to drive prostate cancer towards androgen-independence

  ChIP-seq for AR, FOXA1 and H3K27ac in primary prostate tumors before and after 3 months of neoadjuvant enzalutamide treatment. RNA-seq expression data of primary prostate tumors before and after 3 months of neoadjuvant enzalutamide treatment.

  Dataset EGAD00001008562

• Single-cell RNA-seq, single-cell TCR-seq, single-cell ATAC-seq, and CITE-seq of human tonsillar CD4+ T cells

  To describe human tonsillar CD4+ T cells, especially IL10+ Foxp3- follicular CD4+ T cells (Tfr1, T follicular regulatory type 1), human tonsillar CD4+ T cells were analyzed with single-cell RNA-seq, single-cell TCR-seq, single-cell ATAC-seq, and CITE-seq.

  Study JGAS000805

• Single-cell RNA-seq, single-cell TCR-seq, single-cell BCR-seq, and CITE-seq of B and T cells

  To describe human tonsillar CD4+ T cells, especially IL10+ Foxp3- follicular CD4+ T cells (Tfr1, T follicular regulatory type 1), human tonsillar CD4+ T cells were analyzed with single-cell RNA-seq, single-cell TCR-seq, single-cell ATAC-seq, and CITE-seq.

  Study JGAS000827

• Leiomyosarcoma Cancer Transcriptome Sequencing

  RNA-Seq data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 75bp paired-end protocol to a minimum mean reads of 50 million.

  Dataset EGAD00001003192

• Single Cell Transcriptomic Analysis of Cellular Heterogeneity in Human Colorectal Tumours

  1,591 single cells from 11 colorectal cancer patients were profiled using Fluidigm based single cell RNA-seq protocol to characterized cellular heterogeneity of colorectal cancer. 630 single cells from 7 cell lines were profiled similarly to benchmark de novo cell type identification algorithms.

  Dataset EGAD00001002727

• RNA-seq analysis of human primary keratinocytes and skin

  Bulk and single cell RNA-seq analysis of human keratinocyte and human skin

  Study EGAS00001002981

• A Genomic Approach to Improved Diagnosis and Treatment of Neuroendocrine Tumors

  These are RNA-Seq samples from patients undergoing surgery for small bowel and pancreatic neuroendocrine tumors. Normal tissue, primary tumors, lymph nodes, and liver metastases were collected at surgery and stored in RNAlater until RNA extraction was carried out for RNA-Seq.

  Study phs001772

• Expressed Pseudogenes in the Transcriptional Landscape of Human Cancers

  In this study, we describe a systematic analysis of pseudogene 'transcription' from an RNA-Seq resource of 293 samples, from 13 cancer and normal tissue types. We observed a highly prevalent, genome-wide expression of pseudogenes that could be categorized as universally expressed or lineage- and/or cancer-specific. We also explored disease subtype specificity and functions of selected expressed pseudogenes. We provide evidence that transcribed pseudogenes are a significant contributor to the transcriptional landscape of cells and are positioned to play significant roles in cellular differentiation and cancer progression. Our work provides a transcriptome resource that enables high-throughput analyses of pseudogene expression.

  Study phs000525

• RNA-seq analysis of human peri-implantitis samples

  Bulk RNA-seq analysis of human biopsy material collected from implant sites with peri-implantitis.

  Study EGAS50000000369

• Comparison of capture-based method for transcriptome profiling of formalin-fixed paraffin embedded tumor samples

  Background: The need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. Methods: Transcriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. Results: The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p < 0.01). Both Agilent and IDT detected all the clinically relevant fusions that were initially identified in FF-TruSeq. Conclusion: All exome capture-based methods had comparable performance and concordance with FF-TruSeq. By enabling the interrogation of FFPE tumor samples, our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

  Study EGAS00001005255

• Bulk RNA data from Wilms Tumors

  Bulk RNA-seq data of pediatric Wilms tumors

  Study EGAS00001006531

• Hereditary Gastric Cancer Syndromes: An Integrated Genomic and Clinicopathologic Study of the Predisposition to Gastric Cancer

  Gastric cancers are cancers of the stomach. Hereditary cancers are passed from parent to child. Researchers want to gather data about hereditary gastric cancers. Bulk RNA sequencing (RNA-seq) of signet ring cells (SRCs) and adjacent non-SRC epithelium (NEP) was performed on laser-capture microdissected (LCM) regions of interest found in risk-reducing total gastrectomy specimens from hereditary diffuse gastric cancer (HDGC) patients (Clinicaltrials.gov ID: NCT03030404). Twenty patients (6 male, 14 female) with confirmed HDGC were identified. Analysis of differentially expressed genes (DEGs) demonstrated upregulation of certain individual epithelial–mesenchymal transition (EMT) and proliferation genes. SRC regions had significant enrichment in pathways involved in T cell signaling. CIBERSORTx predicted significant increases in the presence of regulatory T cells (Tregs) specific to SRC regions.

  Study phs003422

• Response and Resistance to ER-Directed Therapy in Metastatic Breast Cancer

  Despite the reduction in cancer recurrence and mortality provided by hormonal therapy, estrogen receptor positive (ER+) metastatic breast cancer (MBC) remains the most common cause of breast cancer death, resulting in more than 20,000 deaths in the U.S each year. Although several therapeutic options exist to target the estrogen receptor, resistance to these therapies invariably occurs. Genetic mechanisms of acquired resistance to targeted therapies in ER+ MBC are not well understood. To address this, we developed a prospective biopsy protocol where multiple research biopsies are collected from metastatic samples and used for pathology, ER/PR/HER2, OncoPanel (a CLIA 300 gene sequencing panel), whole exome sequencing (WES), transcriptome sequencing (RNA-Seq), and single-cell RNA-seq (scRNA-seq). In some cases, tissue is used for cell line and xenograft generation. Archival primary biopsies are also obtained when possible for parallel genomic studies. Patients are followed and serial metastatic biopsies are obtained. This data will be used to determine the landscape of genomic alterations in treatment-resistant ER+ MBC, and compared to data generated by TCGA for treatment-naive ER+ primary breast cancer. Comparison of genomic studies from resistant, metastatic specimens with corresponding pre-treatment primary samples will allow us to identify genomic association with resistance to specific therapies. Analysis of the serial metastatic biopsies collected over the course of multiple treatments will also shed light on tumor evolution under selective therapeutic pressure.NoteA subset of the MBC blood biopsies that are included in our study can be accessed and downloaded from the phs001977 accession.Another subset of patients in this study participated in a clinical trial (NCT02871791) and have their data deposited in the current study as well.

  Study phs001285

• SF12264 snRNA-Seq Primary GBM

  Single Nuclei RNA-Seq Primary GBM. Gender Female Age 51. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005410

• Glioblastoma stem cell lines RNA-seq data

  RNA-seq data for 54 Glioblastoma stem cell (GSC) lines. Fastq files of the strand-specific paired-end RNA-seq data are available.

  Dataset EGAD00001006195

• Metastases of a cancer of unknown primary (CUP)

  RNA seq analysis of 6 CUP metastases (each in triplicate), analysed by paired sequencing with NextSeq 500. Whole exome sequencing of 15 CUP metastases, analysed by paired sequencing with NextSeq 500.

  Dataset EGAD00001005963