510 results for "cancer rna-seq"

in 49.92 milliseconds.

• QSEA – modelling of genome-wide DNA methylation from sequencing enrichment experiments

  We describe a new method, QSEA, for analyzing methylation enrichment data. We generated a benchmark experiment consisting of MeDIP-seq enrichment data, targeted BS-seq validation data, and RNA-seq data on five pairs of tumor and adjacent normal samples of non-small cell lung cancer patients. Details of the method and its performance on the data have been described in Lienhard et al. (2016).

  Study EGAS00001001822

• Complete DNA/RNA sequencing dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07

  Complete WGS and RNA-Seq dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07, representing 93 donors. Sequencing was performed on Illumina HiSeq. Alignment of the lane-level fastq data was performed with bwa (WGS data) and RSEM (transcriptome data). For this dataset lane-level .bam files have been merged and de-duplicated to create a single bam file for each sample type (tumour/normal) for each donor. This dataset supersedes all previous datasets for this study. 2016-08-08 updated with 14 outstanding RNA-seq samples & corresponding RSEM bams 2016-12-07 updated with 7 outstanding RNA-seq controls and corresponding RSEM bams

  Dataset EGAD00001000877

• ProstOmics: spatial and bulk multi-omics of prostate cancer

  In this ERC-funded ProstOmics project we have used spatial and bulk multi-omics on fresh frozen prostate cancer samples to investigate cancer biology and find for biomarkers to improve patient treatment. All tissue material were collected from prostate cancer patients undergoing radical prostatectomy who had not received any prior cancer-specific treatment.Of the 498 prostate tissue samples (114 patients) included in our project, 176 samples (N=37 patients) have been analyzed with bulk transcriptomics (RNA-seq). Some of these 176 samples were also analyzed with spatial transcriptomics (n=32, N=8, Visium 10x RNA-seq) and DNA methylomics (n=96, N=24, array). All datasets include metadata for histopathological evaluation. Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Study EGAS50000000413

• bladder cancer patient data

  This contains H3K27ac ChIP-seq, RNA-seq and HiC fastq files.

  Dataset EGAD00001007052

• RNA-seq data from 121 tumor samples with muscle invasive bladder cancer.

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). RNA-seq was performed using the QuantSeq kit FWD HT kit (Lexogen) using 500 ng input RNA from 121 tumor samples. Data provided here consist of 780 fastq files for RNA-seq.

  Dataset EGAD00001006238

• Dataset for "HPV integration induces gene fusions" (RNA)

  RNA-seq data for "HPV integration induces gene fusions" We performed RNA-seq analysis of five HPV+ head and neck cancer samples using Illumina short reads. Sequenced are submitted in bam format. We also sequenced one samples with pacBio long reads, and the reads are submitted in fastq format.

  Dataset EGAD50000001303

• RNA-seq data from 121 tumor samples with muscle invasive bladder cancer.

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). RNA-seq was performed using the QuantSeq kit FWD HT kit (Lexogen) using 500 ng input RNA from 121 tumor samples. Data provided here consist of 780 fastq files for RNA-seq.

  Study EGAS00001004505

• RNA sequencing of multiple tumor biopsies and patient-derived spheroids from five colorectal cancer patients (BAM files)

  Whole transcriptome, strand-specific RNA-seq libraries were prepared from total RNA purified using RNeasy mini kit (Qiagen) using Ribo-Zero technology (Epicentre, an Illumina company) for depletion of rRNA followed by library preparation using ScriptSeq ScriptSeq RNA-Seq Library preparation Kit from Illumina. The paired raw sequence reads were processed using TopHat2 and mapped to the humane reference genome HG19.

  Dataset EGAD00001003820

• bulk RNA-Seq of colorectal cancer patient samples

  Study EGAS00001006666

• Pheno-Seq, linking 3D phenotypes of clonal tumor spheroids to gene expression

  3D-culture systems have advanced cancer modeling by reflecting physiological characteristics of in-vivo tissues, but our understanding of functional intratumor heterogeneity including visual phenotypes and underlying gene expression is still limited. Transcriptional heterogeneity can be dissected by single-cell RNA-sequencing, but these technologies suffer from low RNA-input and fail to directly correlate gene expression with contextual cellular phenotypes. Here we present pheno-seq for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from 3D models of breast and colorectal cancer. Specifically, we identify characteristic expression signatures that are associated with heterogeneous invasive and proliferative behavior including a rare cell subtype. Furthermore, we identify functionally relevant transcriptional regulators missed by single-cell RNA-seq, link visual phenotypes defined by heterogenous expression to inhibitor response and infer single-cell regulatory states by deconvolution. We anticipate that directly linking molecular features with patho-phenotypes of cancer cells will improve the understanding of intratumor heterogeneity and consequently prove to be useful for translational research.

  Study EGAS00001002999

• Transcriptional and Epigenetic Profiles of Male Breast Cancer at Single-Cell Resolution Nominate Salient Cancer Specific Enhancers

  We performed matched single-cell RNA sequencing (scRNA-seq) and single-cell chromatin accessibility sequencing (scATAC-seq) for two fresh human tumors collected from male breast cancer patients. The integration of these datasets revealed the intratumoral heterogeneity in both transcription and chromatin accessibility for each male breast cancer patient and allowed for comparisons to be made between male and female breast cancer. We hope these data will be a useful reference in the field of breast oncology, specifically for the treatment of males, as few studies have explored male breast cancer genetics.

  Study phs003006

• Multi-omic analysis of SDHB-related PCPG

  Hereditary SDHB-mutant pheochromocytomas (PC) and paragangliomas (PG) are rare tumours with a high propensity to metastasize although their clinical behaviour is unpredictable. To characterize the genomic landscape of these tumours and identify metastasis biomarkers, we performed multi-omic analysis on 94 tumours from 79 patients using six molecular methods including: whole-genome sequencing (WGS) of tumour and matched blood (n=94), whole transcriptome sequencing (RNA-seq) (n=91), small-RNA seq (n=90), DNA methylation profiling (n=93). Droplet-based (10x) single nuclei (sn)RNA-seq and snATAC-seq was applied to 9 and 7 cases, respectively. Additionally snATAC-seq was applied to one sample of normal adrenal medulla.

  Study EGAS50000000346

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001003063

• Genomic Profiling of Advanced Pancreatic Cancer to inform therapy - RNA-Seq unmapped reads

  Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer - Early Results from the COMPASS Trial - RNA-Seq unmapped reads

  Dataset EGAD00001003582

• Genomic Profiling of Advanced Pancreatic Cancer to inform therapy - RNA-Seq mapped reads

  Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer - Early Results from the COMPASS Trial - RNA-Seq mapped reads

  Dataset EGAD00001003584

• RNA-seq dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  RNA-seq dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  Dataset EGAD00001015639

• Plasma cell-free small RNA sequencing comparison of Illumina and Ultima Genomics in pancreatic cancer

  This study evaluates plasma-derived cell-free small RNA sequencing in a case-control cohort of 39 pancreatic ductal adenocarcinoma patients and 39 control subjects. Cell-free nucleic acids were isolated from plasma, small RNA libraries were prepared using the SMARTer smRNA-Seq workflow, and the same libraries were sequenced on both Illumina NovaSeq 6000 and Ultima Genomics UG 100 platforms. The project aims to compare platform performance for circulating small RNA and mature microRNA profiling, including read yield, alignment, RNA biotype composition, mature miRNA detection, expression concordance, and pancreatic cancer-associated differential expression. The dataset supports benchmarking of cross-platform reproducibility and assessment of biologically relevant plasma microRNA signals in pancreatic cancer.

  Study EGAS50000001907

• The role of the mammalian SWI/SNF chromatin remodeling complex in neuroendocrine prostate cancer

  We sought to determine the effects of SMARCA4 and SMARCA2 depletion in prostate cancer cell lines. We performed siRNA-mediated knock-down of SMARCA4 and SMARCA2 in an androgen-sensitive (LNCaP) cell line and in a castration-resistant prostate cancer (CRPC)-adenocarcinoma cell line (22Rv1) and compared global transcriptional alterations using RNA-seq.

  Study EGAS00001004177

• GBM cancer stem cell lines, RNA-seq and WGS data

  This dataset contains 3 GBM stem cell samples profiled by RNA-seq. Two of those samples have been profiled with WGS as well (with matched blood WGS data available)

  Dataset EGAD00001005077

• ART-NKI II HNSCC RNA-Seq

  RNA-Seq data of 25 HNSCC specimens from patients treated at The Netherlands Cancer Institute, Amsterdam and enrolled in the ARTFORCE trial. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005721

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005006

• single-cell RNA-Seq of colorectal cancer patient samples

  Study EGAS00001006665

• Human colorectal cancer single-cell RNA sequencing

  The aim was to investigate changes in transcriptomics following irradiation. This was studied in colorectal cancer-patient derived organoids. Analysis was performed with scRNA-seq.

  Study EGAS50000001348

• Oesophageal adenocarcinoma whole exome and RNA-seq raw sequencing data

  Study EGAS00001005957

• RNA-seq data from the tumor samples of head and neck cancer patients

  This dataset contains paired-end RNA sequencing data (2x50 bp) from the primary tumors and the recurrences/metastases of 6 head and neck cancer patients.

  Dataset EGAD00001011279