12312 results for "cancer rna-seq"

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• BLUEPRINT release August 2016, ChIP-Seq for macrophage - T=6days LPS, on genome GRCh38

  ChIP-Seq data for 2 macrophage - T=6days LPS sample(s). 6 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002498

• BLUEPRINT September 2016, ATAC-seq for venous blood, on Genome GRCh38

  ATAC-seq data for 136 sample(s) from venous blood, on Genome GRCh38. 141 run(s), 139 experiment(s), 139 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002709

• Peripheral Blood Leukocytes 10x Genomics scRNA-seq

  This dataset contains 10x Genomics Single Cell 3’ Solution (version 2) scRNA-seq data from peripheral blood leukocytes of a single healthy donor. Data from 20939 cells were collected over 8 lanes and 2 sequencing runs.

  Dataset EGAD00001008590

• PhIP-Seq Serum 1000IBD

  PhIP-Seq experiment conducted in Eran Sigal's group at WIS.

  Dataset EGAD00001010118

• Single-Cell Mitochondrial Variant Profiling via TAMITO-seq

  This dataset focuses on mitochondrial variant detection using the TAMITO-seq protocol. A pre-designed mitochondrial panel (https://designer.missionbio.com/catalogpanels/Virtual-mtDNA) was spiked into the scTAMseq workflow targeting 200 CpGs and 167 genotyping loci. Data were generated from a peripheral blood sample of a healthy donor, donor X.2, multiplexed with data from another donor.

  Dataset EGAD00001015494

• Single-Cell Protein Expression via scTAMseq Cite-seq

  This dataset contains single-cell surface marker expression profiles generated by integrating the Cite-seq protocol with scTAMseq. Samples were stained with an antibody panel targeting 45 (donor A.6 & A.7) and 56 (donors A.1-A.5, B.1-B.5, and X.2 ) surface proteins to enable robust phenotypic characterization.

  Dataset EGAD00001015497

• scRNA-seq data of FOXN1heterozygous patients and cord blood

  Single cell sequencing was performed from sorted CD45+ lymphocytes from two FOXN1het patients and one cord blood sample from frozen cryopreserved samples to undestand the shifts in immune cell populations in pateints with FOXN1 heterozygous deficiency. Each sorted population was labelled individually via multiplexing antibodies with subsequent Abseq staining before pooling and conducting the BD Rhapsody pipeline to generate scRNA-seq data.

  Study EGAS50000001199

• Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell ATAC-seq

  We report a deconvolution and identification strategy of scATAC-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and acquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures in different mixed ration and cell volumes.

  Study EGAS00001007380

• LuCaP cell line ChIP-seq

  ChIP-seq of 2 LuCaP cell lines with different factors. LuCaP cell line 189.4 was ChIP-sequenced for 6 factors with different conditions as well as the input DNA (n=31 in total). LuCaP 189.4 ChIP-sequence experiments include; 3 H3K27ac/DMSO, 3 H3K27ac/vorinostat, 3 H3K27ac/dexamethasone, 3 H3K27ac/dexamethasone/vorinostat, 3 GR dexamethasone, 3 GR dexamethasone/vorinostat, 3 HDAC3/DMSO, 3 AR, 3 FOXA1, 3 H3K27ac and 1 input sample. LuCaP 35 ChIP-sequence experiments as well as input include (n=10 in total); 3 H3K27ac, 3 AR, 3 FOXA1 and 1 input sample. All 41 samples were sequenced using paired-end reads on Illumina NovaSeq 6000. Each sample has 2 fastq files, one for the forward and reverse read, respectively.

  Dataset EGAD50000001345

• Single Cell Analysis of Sporadic Human Basal Cell Carcinomas

  To explore tumor heterogeneity in sporadic human basal cell carcinoma tumors, we profiled three individual patient tumors by scRNA-Seq and scATAC-Seq. Basal cell carcinomas (BCCs) are driven by hedgehog signaling with GLI1 representing the key downstream transcription factor that drives tumor growth. GLI1 as such is a readout of active hedgehog signaling. We identified that LY6D can mark squamous populations such as in squamous cell carcinomas (SCCs) that are negative for GIL1 and hedgehog signaling. As such, both GLI1 and LY6D can be used as biomarkers of BCCs and SCCs and their related states.

  Study phs003103

• Single-cell proteogenomics of MDS upon AZA

  To study the evolution of the clonal molecular and cellular architecture of MDS upon the treatment with AZA, we performed scDNA-seq of an amplicon panel of 53 genes recurrently mutated in myeloid malignancies, as well as typically lost or gain DNA regions, and scProt-seq of 42 cell-surface proteins to provide a simultaneous landscape of the genetic setting and immunophenotype using the Tapestri platform (MissionBio). We sequenced thousands of cells from 14 MDS patients, where paired bone marrow samples were obtained at the timepoint of diagnosis and after AZA treatment.

  Study EGAS00001007427

• RNA sequencing, ATACseq, and TCR-seq of Tfh cells and CXCR5- CD4+ T cells in HIV infected lymph nodes

  The high dimensional analyses of CD4+ T cells in human lymph nodes are case-based analyses of the TCR repertoire, transcriptome, and epigenetic signatures of various CD4+ T cells in human lymph nodes. The study aims to determine clonal overlap between phenotypically distinct CD4+ T cells and the similarities between these populations on transcriptional and epigenetic levels. This study performs TCR repertoire sequencing using Molecular Identifier Clustering-based Immune Repertoire Sequencing (MIDCIRS). We found clonal overlap between a population of CXCR5- T cells and follicular helper T (Tfh) cells. We also show epigenetic and transcriptional similarities between CXCR5-PD-1+ T cells and Tfh cells. This study shares an overlapping set of donors with phs001548.

  Study phs001849

• RNA-seq study of longitudinal blood cell samples from children at risk of type 1 diabetes

  The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (Case subjects) at a young age and matched control subjects.

  Study EGAS00001004071

• Identification of cardiovascular biomarkers through an integrative omics approach

  Recent GWAS studies have made extensive use of large eQTL data sets to functionally annotate index SNPs. With a large number of association signals located outside coding regions there has been an intense search among sequence variants affecting gene expression at the transcriptional level. However, little progress has been made in mapping regulatory variants that affect protein levels at the translational or post-translational level. It is now possible to undertake a protein QTL scan for focused sets of e.g. oxidized proteins by mass spectrometry. We have established a collaboration with a longitudinal, family-based study in France, the Stanislas cohort, which comprises circa 1000 nuclear families (4,295 individuals) and has follow up data for 10 years (three visits). We have undertaken a pilot study in a focus set of 257 subjects from 79 families with the aim to integrate GWAS, transcriptomic and DNA methylation data with proteomic data on a set of 100 proteins measured in PBMCs. We have already generated GWAS data using Illumina's core-exome chip as well as DNA methylation profiles with the 450K array. We propose to use RNA seq to generate transcriptomic data of the corresponding PBMCs. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002197

• IKZF5 RNAseq samples for platelets, neutrophils, monocytes and CD4+ T-cells.

  To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing (WGS) data from 13,037 individuals enrolled in the NIHR BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor (TF)-encoding gene IKZF5 and thrombocytopenia. We report five causal missense variants in or near IKZF5 zinc fingers (Znfs), of which two occurred de novo and three co-segregated in three pedigrees. A canonical DNA-Znf binding model predicts that three of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared to wild-type (WT) IKZF5 and electron microscopy (EM) revealed a reduced quantity of alpha granules in normally sized platelets. Proplatelet formation (PPF) was reduced in megakaryocytes (MKs) from seven cases relative to six controls. Comparison of RNA-seq data from platelets, monocytes, neutrophils and CD4+ T-cells from three cases and 14 healthy controls showed 1,194 differentially expressed genes (DEGs) in platelets but only four DEGs in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

  Dataset EGAD00001005107

• Feinstaub Methyl-Seq

  Dac EGAC00001003364

• Dengue scRNA-seq

  Dac EGAC00001002099

• Cite-seq committee

  Dac EGAC00001002453

• DPR mRNA Seq team

  Dac EGAC00001002600

• TRACERx NSCLC, multiregion sequencing of the first 100 tumors

  BACKGROUND TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). METHODS Multiregion high-depth whole-exome sequencing (M-seq) was performed on 100 early stage NSCLC tumors resected prior to systemic therapy. A total of 327 tumor regions were sequenced and analyzed to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between ITH and recurrence-free survival (RFS). RESULTS Widespread ITH was observed for both somatic copy number alterations (median 48% [0.03-88%]) and mutations (median 30% [0.5-93%]). Driver mutations in EGFR, MET, BRAF and TP53 were almost always clonal. However, heterogeneous driver alterations occurring later in evolution were found in over 75% of tumors and were common in PIK3CA, NF1 and genes involved in chromatin modification and DNA response and repair. Genome doubling and ongoing dynamic chromosomal instability (CIN), illustrated by mirrored subclonal allelic imbalance, were identified as causes of ITH resulting in parallel evolution of driver copy number events, including amplifications of CDK4, FOXA1, and BCL11A. Elevated copy number heterogeneity was associated with shorter RFS (HR=4.9, P=0.00044), which remained significant in a multivariate analysis. CONCLUSIONS ITH mediated through CIN, rather than point mutational heterogeneity, was associated with increased risk of relapse, supporting its value as a prognostic predictor, and the need to target this high-risk phenotype.

  Dataset EGAD00001003206

• Transcriptome - Uveal Melanomas

  Total RNA sequencing on 9 uveal melanomas. Libraries were prepared using the TruSeq Stranded Total RNA Library Prep Gold (Illumina, 20020599). Paired-end libraries (2 x 100 bp) were sequenced on a NovaSeq 6000 instrument (Illumina).

  Dataset EGAD50000000763

• RNA data for Glioblastoma (EGAS00001003953, H016)

  RNA data for human glioblastoma patients, EGAS00001003953. 64 human samples, 2 cell lines (LN229, ZH487).

  Dataset EGAD00001006547

• RNA sequencing of 20 intra/extra hepatic bileduct organiods

  This dataset contains RNA sequencing data for 20 intra/extra hepatic bileduct organiods. Data is in BAM format and was processed by STAR.

  Dataset EGAD00001005225

• The polarity and specificity of antiviral T lymphocyte responses determine susceptibility to SARS-CoV-2 infection in cancer patients and healthy individuals

  We monitored patient's anti SARS-CoV-2 immune responses using an in vitro cross presentation assay. The goal of this study was to identify immune correlates of clinical protection against SARS-CoV-2 infection. Briefly, peripheral blood mononuclear cells of patient were divided into a monocyte and lymphocyte. Monocyte were differentiated into monocyte derived dendritic (mo-DC)cells using GM-CSF and Interferon alpha. Mo-DC were then loaded with SARS-CoV-2 culture lysates , or VeroE86 lysates. SARS-CoV-2 loaded mo-DC were then used to stimulates their autologous lymphocytes and T cell cytokine secretion was monitored in the supernatant. We discriminated patients producing IL-2 and patients producing IL-5. RNA sequencing was performed for 18 patients, to identify gene profile associated with IL-2 or IL-5 production.

  Dataset EGAD00001008538

• Extensive three-dimensional intratumor proteomic heterogeneity revealed by multiregion sampling in high-grade serous ovarian tumor specimens

  Enriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor “purity.” Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling.

  Dataset EGAD00001008344