11750 results for "cancer rna-seq"

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• Genomic profiling of BRCA- mutant breast cancer tumors

  This data set contains whole exome sequencing (WXS) and RNA-Seq on germline BRCA- mutant tumors from 18 patients. BAM files are provided for WXS on tumor and germline samples. FASTQ files are provided for the RNA-Seq samples. Sequencing was done on an Illumina Hi-Seq 2500.

  Dataset EGAD00001008276

• Genomic landscape of metastases from 97 patients with metastatic urothelial carcinoma

  Metastatic urothelial carcinoma (mUC) is a lethal cancer, with limited therapeutic options. Large-scale studies in early settings provided critical insights into the genomic and transcriptomic characteristics of non-metastatic UC. The genomic landscape of mUC remains however unclear. Whole exome (WES) and mRNA sequencing (RNA-seq) were performed on metastatic biopsies from 111 patients with mUC. Driver genomic alterations from mUC were comparable to primary UC (TCGA data).

  Study EGAS50000000373

• Genomic and Transcriptomic Data from Advanced Rare Cancer Patients Treated with Pembrolizumab

  This dataset comprises whole exome sequencing data and RNA-seq data of advanced rare cancer patients.

  Dataset EGAD50000002182

• Proteogenomic Landscape of Curable Prostate Cancer

  Aligned RNA-seq sequences in this dataset are from the Proteogenomic Landscape of Curable Prostate Cancer study

  Dataset EGAD00001004875

• SYSCOL Human colorectal cancer project pilot RNA-seq and germline genotyping

  Genotyping by array and Transcriptome profiling by high-throughput sequencing

  Dataset EGAD00001000880

• RNA-Seq of kidney cancer organoid biobank

  Dataset EGAD00001005318

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• Spatial heterogeneity, stromal phenotypes, and therapeutic vulnerabilities in colorectal cancer peritoneal metastasis

  Peritoneal metastases (PM) in colorectal cancer (CRC) portend a poor prognosis. We sought to elucidate molecular features differentiating primary tumors (PTs) from PMs and actionable targets facilitating transcoelomic dissemination and progression. We performed multi-omic profiling of 217 samples from 136 patients, including 56 primary tumor (PT) and 120 PMs comprising 25 matched PT-PM pairs. Whole exome, and bulk RNA-seq analysis was conducted to identify underlying genomic aberrations and transcriptomic differences between primary and peritoneal lesions.

  Study EGAS50000000813

• Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in HGSOC

  Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Long-read single-cell RNA sequencing (scRNA-seq), capturing full-length transcripts, lacked the depth to provide this information so far. Here, we increased the PacBio sequencing depth to 12,000 reads per cell, leveraging multiple strategies, including artifact removal and transcript concatenation, and applied the technology to samples from three human ovarian cancer patients. Our approach captured 152,000 isoforms, of which over 52,000 were novel, detected cell type- and cell-specific isoform usage, and revealed differential isoform expression in tumor and mesothelial cells. Furthermore, we identified gene fusions, including a novel scDNA sequencing-validated IGF2BP2::TESPA1 fusion, which was misclassified as high TESPA1 expression in matched short-read data, and called somatic and germline mutations, confirming targeted NGS cancer gene panel results. With multiple new opportunities, especially for cancer biology, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.

  Study EGAS00001006807

• Natural variation of circulating RNAs in human serum

  The Janus Serum Bank (JSB) is a population-based cancer research biobank. This dataset contains small RNA sequencing (RNA-seq) data of 520 JSB samples from cancer-free individuals. Sequencing libraries were indexed and 12 samples were sequenced per lane on a HiSeq 2500 (Illumina) to an average depth of 18 million reads per sample. The dataset files are raw FASTQ files from the sequencing machine (50bp, single-end sequencing)

  Dataset EGAD00001003968