15167 results for "cancer studies using rna-seq"

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• Clinical sequencing in multiple myeloma

  DNA (n=1281) and RNA (n=767) were extracted from bone marrow aspirates where CD138+ selection had been performed to enrich plasma cells from patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), or multiple myeloma (MM). DNA and/or RNA were sent to Foundation Medicine where targeted sequencing was performed using their Foundation 1 Heme panel. Resulting BAM files were returned along with annotations for somatic events including single nucleotide mutations, indels and structural rearrangements.

  Dataset EGAD00001004113

• Human CD4 Memory T Cell Activation Time Course

  We performed a high-resolution time course RNA-seq experiment on CD4+ memory T cells during activation with anti-CD3/CD28 beads. We performed this in 24 adult individuals of European ancestry with no autoimmune diseases. We used 1 million cells as starting material, per time point (up to 8 time points per individual from 0 to 72 hours). We identified widespread dynamic allele-specific expression (dynASE) across the genome, i.e. ASE that changes with time after activation, which reflects cell state-dependent genetic regulatory effects. DynASE events were enriched in risk loci for multiple autoimmune diseases. This highlights the importance of studying multiple cellular states in order to elucidate the mechanisms of autoimmune disease. It also provides a successful framework to do it in other cellular systems relevant for other traits. We also showed an unprecedented amount of regulatory variation for HLA genes. HLA-DQB1 has 3 distinct regulatory haplotypes with expression profiles that could come from 3 different genes. We performed ATAC-seq in replicate for CD4+ memory T cells stimulated for 72 hours from another healthy individual. These data, together with genetic fine-mapping, CRISPR editing, EMSA and luciferase assays, helped us find a SNP in the promoter of HLA-DQB1 that causes at least part of the large cell state-dependent change in expression, at the RNA and protein levels.

  Study phs002259

• Single cell mRNA sequencing of primary GBM - SF 10345

  We collected fresh tissue from an untreated GBM (SF10345) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001002271

• Single cell mRNA sequencing of primary GBM - SF 10360

  We collected fresh tissue from an untreated GBM (SF10360) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001002272

• Single cell mRNA sequencing of primary GBM - SF 10282

  We collected fresh tissue from an untreated GBM (SF10282) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001002270

• RNA-seq TPM matrices

  Matrices of TPM-normalized counts from RNAseq data for the three phase II clinical trials (IMvigor210, POPLAR, IMmotion150) and the phase I clinical trial PCD4989g.

  Dataset EGAD00001006741

• Whole-exome and whole-genome sequencing data

  Multi-omic data for lung neuroendocrine neoplasms, including the first multi-omic sequencing data for the understudied lung atypical carcinoids. The data includes Whole-exomes, whole-genomes, RNA-seq, and EPIC 850K methylation array data.

  Dataset EGAD00001005087

• BLUEPRINT: RNA-seq of progenitor cells

  Data supporting the paper Transcriptional diversity during lineage commitment of human blood progenitors

  Dataset EGAD00001000745

• Gene expression matrix for Smart-seq2 data of peripheral blood B cells

  The dataset contains scRNA-seq gene expression matrix (csv file) and metadata (csv file) after quality control filtering for data generated with the Smart-seq2 protocol. Transcript expression was quantified with Salmon v0.11.3 using cDNA sequences from GRCh38.94 and k-mer length 25, and was aggregated to gene level and transcript-length-corrected using tximport v1.8.0. The dataset comprises IgA+ transglutaminase 2-specific and other IgA+ B cells from the peripheral blood of 355 cells from two untreated celiac disease patients.

  Dataset EGAD50000000338

• Somatic L1 retrotransposition mapping in high-grade serous ovarian carcinoma using LDI-PCR/Nanopore-sequencing (part 2)

  Somatic L1 retrotransposition was mapped in high-grade serous carcinoma (HGSC) tumors using LDI-PCR/Nanopore-seq method. This method identifies somatic L1 insertions originating from two active L1 loci at chr22q12.1 and chrXp22.2. Multiple tumors from the same patient were utilised to understand L1-mediated intrapatient heterogeneity. Long-read data generated by LDI-Nanopore sequencing was aligned to the reference genome (GRCh38). This dataset contains the remaining file of this study.

  Dataset EGAD50000001757