7190 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• Platelet RNAseq data for SLFN14 K219N patients

  RNAseq dataset containing 20 control and 2 SLFN14 K219N patient samples, derived from platelets. Sequencing libraries were constructed using an Illumina TruSeq stranded Ribo Zero Gold kit and paired end sequenced at a read depth of 30 million reads on an Illumina NovaSeq 6000 platform.

  Dataset EGAD00001008965

• Sequencing data for oesophageal and related samples - Ng, Contino et al (RNA)

  Data supporting: "Interplay of processes shapes structural variations undergoing selection in oesophageal adenocarcinoma" Ng, Contino et al. RNAseq (BAM files) 214 oesophageal adenocarcinoma samples

  Dataset EGAD00001007809

• Nuclear Optimized 10x data

  Optimized 10x library to increase the coverage of selected nuclear variants from 3’ 10x Genomics scRNAseq data. SNVs were selected based on exome data and criteria described in the Supplementary Information of the manuscript.See details of the experimental method in the methods section of the manuscript

  Dataset EGAD00001010192

• Baseline and progression dataset

  RNAseq FASTq files from 44 pre-treatment (Ven-Obi or Clb-Obi) and 44 paired, post-treatment relapsed CD19+ B cells.

  Dataset EGAD00001009419

• scRNA-seq of nonhematopoietic cells in human lymph nodes and lymphoma

  Single-cell count data generated by the Cellranger (10X Genomics).

  Dataset EGAD00001008311

• A molecular atlas of the human postmenopausal fallopian tube and ovary from single-cell RNA

  This datasets contains raw sequencing fastq data of 17 samples from 7 donors of single cell RNA using10x genome technology of human postmenopausal fallopian tube and ovary tissues.

  Dataset EGAD00001010076

• MutaSeq data for A.10-12

  MutaSeq was applied to CD34+ cells from patient samples A.10, A.11 and A.12 of the study. The protocol followed is described in https://doi.org/10.1038/s41467-021-21650-1 and in the methods of the manuscript

  Dataset EGAD00001010189

• Mitochondria Optimized 10x data

  Optimized 10x library to increase the coverage of the mitochondrial genome from 3’ 10x gene expression data. See details of the experimental method in the methods section of the manuscript

  Dataset EGAD00001010191

• Single Cell Transcriptomics of peripheral immune cells pre- and post-Immune Checkpoint Blockade

  This is raw sequencing data, analysis of which is presented in the paper "Sensitivity to Immune Checkpoint Blockade and Progression-Free Survival is associated with baseline CD8+ T cell clone size and cytotoxicity", DOI: https://doi.org/10.1101/2020.11.15.383786

  Dataset EGAD00001007942

• RNAseq of liver harvested from CDAHFD mice treated for 8 weeks with either the MGAT2 inhibitor compound BMS-963272 or vehicle

  This experiment consists of RNAseq of liver harvested from CDAHFD mice treated for 8 weeks with either the MGAT2 inhibitor compound BMS-963272 (N = 10) or with vehicle (N = 10).

  Dataset EGAD00001009389

• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287

• Digital spatial transcriptomic

  Nanostring DSP spatial profiles of 8 patients whose antral sections contained histologically normal, IM, GC, lymphoid aggregates, and stromal regions, representing 480 regions of interest (ROIs) and 76 CD45-segmented areas of illumination (AOIs).

  Dataset EGAD00001010174

• Mapping of runs back to samples for snRNASeq data

  Mapping of runs back to samples for PDN, PDO and TIS snRNASeq data. 4 sets of matched PDN, PDO and TIS samples (12 unique samples total) underwent pooled snRNASeq (Parse Biosciences). 2 sublibraries were created from this and sequenced at separate times

  Dataset EGAD00001015609

• eQTL summary statistics

  This dataset contains the eQTL summary statistics (nominal pass, significant eQTLs, best associated variant per gene). eQTL mapping was performed with fastQTL. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

  Dataset EGAD00001005041

• Gluten reactive and non-reactive T-cells from treated celiac disease patients on a gluten challenge sampled at day 6

  Gluten reactive T-cells from blood samples from patients undergoing a 3 day gluten challenge. Samples were collected on day 6. Both gluten reactive and non-gluten reactive T-cells were sequenced.

  Dataset EGAD00001006899

• Single cell TotalSeqC protein data of 20 PMBC pools of HCC patients

  Single cell TotalSeqC protein data serial peripheral blood mononuclear cell (PBMC) samples taken from advanced HCC patients. TotalSeqC is available for 41 out of 72 PBMC samples included in the study, and were combined into 20 pools.

  Dataset EGAD00001011346

• Single-Cell Data from "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer"

  This dataset contains the FASTQ files from the Single-Cell GEx+TCR 10X Genomics data from the study "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer" (EGAS00001008174)

  Dataset EGAD00001015632

• Unraveling mutagenic processes influencing the tumor mutational patterns of individuals with Constitutional Mismatch Repair Deficiency

  Molecular characterization of 41 tumors from 17 individuals with CMMRD to gain a better understandig of mutational processes driving subsequent tumor development. The molecular characterization includes the investigation of tumor mutational load and mutational signatures.

  Dataset EGAD00001015635

• RNAseq data for 6 samples from the DEV cell line

  - Six samples from the DEV cell line: 2 controls, 2 transduced with IL4R WT and 2 transduced with IL4R mutant (I242N) - This DEV cell line is not commercially available and was acquired from a colleague in the Netherlands

  Dataset EGAD00001003908

• Whole Genome Sequencing of Mutifocal HCC tisue

  The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy.

  Dataset EGAD00001003348

• Comprehensive genetic analysis of Epstein-Barr virus-associated hematological malignancy

  Comprehensive genetic analyses including whole-exome sequencing, targeted sequencing, and whole-genome sequencing of the human genome and the Epstein-Barr virus (EBV) genome were performed to reveal the molecular pathogenesis of EBV-associated hematological malignancy.

  Dataset EGAD00001004286

• Sequencing data for oesophageal and related samples - Alex Frankell et al (RNA)

  Data supporting: "The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic." Frankell et al. RNAseq (BAM files) 116 tumours

  Dataset EGAD00001004423

• Raw sequencing files from WGS and RNA-Seq

  Acute leukemias are the most common malignancies in children with an onset of the disease among 0-6 years-old. The early development of theses malignancies has been proposed as an indicator of their prenatal origin, hypothesis that has been confirmed especially in the case of acute lymphoblastic leukemia. For acute myeloid leukemia (AML), comprising an heterogenous group of different cytogenetics subtypes, this prenatal origin has also been confirmed specially for MLL-rearranged and t(8;21) subgroups. AMLs carrying t(7;12) constitute up to 30% of cases under 2-years-old, frequently being associated with a trisomy of chromosome 19 and an overexpression of MNX1 gene. An in utero origin of this specific subgroup has been suggested but not clearly confirmed. Here, we present the case of a 5-months-old AML patient with t(7;12) in which we have fully characterized a novel breakpoint occurring among ETV6 and NOM1 genes. We demonstrate the presence of this specific ETV6-NOM1 fusion in CD34+ hematopoietic stem and progenitor cells isolated from the cord blood unit from the same patient and stored at birth. Moreover, trisomy +19 present at diagnosis was not detected at birth. Together, our results demonstrate the prenatal origin of the t(7;12) in infant AML, and establish trisomy +19 as a secondary event in this leukemia.

  Study EGAS50000000186

• Regulatory and Effector T cells in Oral Immunotherapy for Food Allergy

  This study consisted of a clinical trial for peanut oral immunotherapy (OIT) and a follow-up project (see below). Patients were included from 2013-2015, and samples from the last timepoints were collected in 2017. The study focused on peanut-specific CD4+ T cell responses before, during, and after OIT with peanut protein. We analyzed T cell gene expression, cytokine production, and T cell receptor β (TCRβ) and TCRα clonotypes, both in bulk T cell populations and single cells, and sought to correlate these data with differences in clinical sensitivity between peanut-allergic patients before OIT, and with differences in clinical outcome after OIT. The goal was to better understand the role of peanut-specific effector and regulatory T cells in peanut allergy and tolerance, which may inform more effective therapies (e.g., OIT combined with biologicals, probiotics, or adjuvants) in the future. Tolerance Following Peanut Oral Immunotherapy (PNOIT2, NCT01750879): The unifying objective of this project is to determine whether peanut oral immunotherapy (PNOIT)-induced clinical tolerance in the context of food allergy is significantly associated with the expansion of a specific regulatory T cell subset (CD45RA-, CD25++, FoxP3+ +) that is thought to be inducible in the gut-associated lymphoid compartment and associated with immunological tolerance. The hypothesis of the study is that the induction of Treg cells will be associated with clinical tolerance. The investigators will measure the change from baseline of induced Treg cells as a frequency of total CD4+ T cells during active treatment and compare that between participants who achieve significant clinical tolerance and those who do not. High Threshold Peanut Challenge Study (PAID-UP, NCT02698033): This protocol was designed to better characterize a sub-population of peanut-sensitized individuals who may be non-allergic, despite significant sensitization, or who may be allergic, but at high threshold doses. By specifically targeting participants who met the initial screening criteria of an earlier study, NCT01750879, but failed to react during the pre-treatment 443 mg challenge to peanut, the investigators anticipate that they will identify individuals who have become spontaneously tolerant, despite persistent sensitization. The investigators might also find that clinical sensitivity persists but only with higher thresholds, or that sensitivity has increased (or is variable) since the previous allergen exposure. By repeating food challenges through to a full serving dose (7.4 gram), the investigators will distinguish participants who react only at higher doses from those who were not truly peanut-allergic, address whether their sensitivity has changed, and have the opportunity to further investigate their immune response to peanut allergen. Methods: Peripheral blood mononuclear cells were isolated from patient blood samples, and stimulated with peanut protein. Peanut-activated CD4+ T cells were sorted based on the activation marker CD154. For a more recent study, the activation marker CD137 was used as well. Total RNA from peanut-activated CD154+ and resting CD154- CD69- T cells was used for cDNA synthesis and amplification (SMARTer ultra low input RNA kit for sequencing - v3; Clontech Laboratories). Libraries were prepared and sequenced on the Illumina HiSeq platform, at a read depth of approximately 30 million reads per sample. Genomic DNA from CD154+ and CD154- CD69- T cells was used to amplify and sequence the TCRβ CDR3 regions (immunoSEQ assay; Adaptive Biotechnologies). The immunoSEQ approach generates an 87 base-pair fragment capable of identifying the VDJ region spanning each unique CDR3. Amplicons were sequenced using the Illumina NextSeq platform. Using a baseline developed from a suite of synthetic templates, primer concentrations and computational corrections were used to correct for the primer bias common to multiplex PCR reactions. Raw sequence data were filtered on the basis of TCRβ V, D, and J gene definitions provided by the IMGT database (www.imgt.org) and binned using a modified nearest-neighbor algorithm to merge closely related sequences and remove both PCR and sequencing errors. For single-cell analysis, we aimed to recover TCR variable sequences from high-throughput single-cell libraries generated by popular platforms such as SeqWell and DropSeq. We paired TCR information with T cell single-cell RNA sequencing results from patients undergoing peanut OIT to show clonal expansion-related T cell phenotypes.

  Study phs001897

• Multimodal Analysis for Human Ex Vivo Studies Shows Extensive Molecular Changes from Delays in Blood Processing

  Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMCs up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states.

  Study phs002280