329 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

• 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

• 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

• Rio Dataset

  Homologous recombination DNA repair deficiency and PARP inhibition activity in primary triple negative breast cancer. RNA-Seq data for paired baseline and end of treatment samples

  Dataset EGAD00001006120

• Cellular composition of spheres derived from lymph nodes of lung cancer patients

  To decipher the cell type composition within single spheres we performed RNA-Seq of 25 selected spheres of 4 different categories (including 8 signature-/balanced, 9 signature+/balanced, 1 signature-/aberrant, 7 signature+/aberrant). To track the individual cell types within single spheres we performed deconvolution analysis.

  Study EGAS00001007369

• Whole-Genome and Transcriptomic Data from Colorectal Cancer Patients and Matched Healthy Controls in Sweden

  This dataset contains whole-genome sequencing (WGS) and RNA-seq data generated from tumor samples, matched blood samples, and healthy control samples collected from 350 Swedish individuals between 2019 and 2023. Tumor biopsies were obtained from colorectal cancer (CRC) patients, while control samples were collected from age- and sex-matched healthy volunteers with no history of CRC. For tumor samples, paired-end RNA-seq was performed to capture gene expression profiles, and WGS was carried out on DNA extracted from both tumor tissue and matched blood samples to identify somatic and germline variants. For controls, WGS was performed on peripheral blood DNA to provide baseline genomic profiles for comparison. The resulting dataset includes: RNA-seq files in FASTQ format (~2.8 TB total) WGS files in CRAM format (~4.2 TB total) Variant calls in VCF format (~150 GB) Clinical and sample metadata in CSV format Data are stored in FEGA Sweden under controlled access. Access requests will be reviewed by the Lund University RDO as the data controller. Ethical approval was obtained from the Swedish Ethical Review Authority (Dnr: 2023-01234).

  Dataset EGAD50000000155

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

  This study includes treatment-naïve fresh tissue sample from 4 HGSOC patients.

  Dataset EGAD00001006984

• 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

• Pheno-seq profiles of single clonal tumor spheroids derived from a patient with colorectal cancer

  Pheno-seq is a new approach that integrates high-throughput imaging and transcriptomic profiling of clonal spheroids/organoids to dissect functional tumor cell heterogeneity in 3D cell culture systems. The method is based on the iCELL8 technology (TakaraBio) that uses barcoded nanowells and a micro-solenoid valve dispenser. The CRC_spheroid dataset contains demultiplexed RNA-sequencing profiles (FASTQ file format, NextSeq 500) of 95 clonal tumor spheroids derived from a patient with colorectal cancer.

  Dataset EGAD00001004131

• 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