14983 results for "cancer studies using rna-seq"

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• Spatial profiling of hepatocellular carcinoma identifies distinct tumor and immune micro-ecosystems related to patient outcomes

  Hepatocellular carcinoma (HCC) shows substantial intra-tumor heterogeneity that remains poorly understood. Using spatial transcriptomics, we identified 13 recurrent tumor and stromal micro-ecosystems (MES) and mapped their spatial organization and biological functions. One immune-enriched MES containing Kupffer cell–like macrophages was strongly associated with improved disease-free survival and response to atezolizumab–bevacizumab. Our findings demonstrate the value of spatial profiling for revealing rare but clinically meaningful cellular communities.

  Study EGAS50000001474

• Circulating Tumor DNA Analysis Profiles of Repotrectinib in NTRK fusion–positive advanced solid tumors: a phase 1/2 trial

  The dataset contains circulating tumor DNA (ctDNA) profiles from frozen plasma samples of 593 patients from the TRIDENT-1 clinical trial. Plasma was processed with centrifugation and automated liquid handling systems, and cell-free DNA was extracted using the Qiagen QIAsymphony platform. ctDNA libraries were constructed with the Guardant360 2.11 assay, which used targeted, hybridization-based capture and barcoding of cfDNA fragments for digital analysis, followed by high-throughput sequencing on the Illumina NextSeq 550 instrument. Sequencing data were processed and interpreted using the Bioinformatics Pipeline (BIP v3.5.2 or later) for variant calling and quantification and managed within LabVantage LIMS (v3.7 or later) to support sample tracking and workflow integration. Aligned read files are provided in bam and bai formats.

  Dataset EGAD50000002249

• Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment

  Samples was collected at the Mayo Clinic. MM tumor samples were enriched using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). DNA from CD138+ MM cell (tumor) or peripheral blood samples (germline control) at Mayo Clinic (Rochester or Arizona) underwent WGS. For samples collected at Mayo Clinic Rochester, library preparation was completed using the NEB Ultra II (New England Biolabs, Ipswich, MA) and the Nextera Flex systems (Illumina, San Diego, CA) and sequenced at the Mayo Clinic Genome Analysis Core with an approximate depth of 30X for tumor samples and 60X for the germline control. For samples collected at Mayo Clinic Arizona, Novogene was used for WGS following random shearing of the DNA, end-repairs, A-tailed and ligated with Illumina adapters. Sequencing was performed on the Illumina Novaseq 6000 sequencer Reference Genome: GRCh38.

  Dataset EGAD50000002132

• Maastricht IBS 16S data

  Maastricht IBS cohort with biobank aims to identify subgroups of IBS according to phenotypical and genotypical characterization. This dataset represents 16S amlicon sequencing of the gut microbiome of case samples and matched controls. Fecal DNA was extracted using the Qiagen AllPrep kit with bead-beating step. Sequencing of bacterial 16S gene, domain V4, was performed using the Illumina MiSeq platform.

  Dataset EGAD00001007074

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Our probands A and B are boys-monozygotic twins with the clinical diagnosis of severe intellectual impairment, developmental stagnation, and dysphasia. They were diagnosed at the Department of Medical Genetics and Genomics (University Hospital Brno). Parents provided written informed consent, which was approved by the Research Ethics Committee of Masaryk University and Ethics Committee of University Hospital Brno. Peripheral blood samples were collected in sterile heparinized tubes for cytogenetic analysis. Genomic DNA samples were obtained from 1 ml peripheral blood in EDTA, according to the standard DNA isolation process using the MagNaPure system (Roche Diagnostics, Basel, Switzerland). Quality and quantity were checked using a DeNovix DS-11 Spectrophotometer (DeNovix Inc., Wilmington, DE, USA) and Qubit® 2.0 (Thermo Fisher Scientific, Inc., Waltham, MA, USA).

  Dataset EGAD00001007736

• Single cell transcriptomic data of human gut macrophages

  Cellular suspensions (∼15000 cells, with expected recovery of ∼7500 cells) of sorted CD45+ HLA-DR+ CD14+ macrophages from colonic mucosa and muscularis propria were loaded on the 10X Chromium Controller instrument (10X Genomics) according to the manufacturer’s protocol using the 10X GEMCode proprietary technology. All samples from individual patients were loaded in one batch. The Chromium Single Cell 3´ v2 Reagent kit (10X Genomics) was used to generate the cDNA and prepare the libraries, according to the manufacturer’s protocol. The libraries were then equimolarly pooled and sequenced on an Illumina NextSeq500 using HighOutput flow cells v2.5. A coverage of 400M reads per sample was targeted, in order to obtain 50 000 reads per cell. The raw data were then demultiplexed and processed with the Cell Ranger software (10X Genomics) v2.1.1.

  Dataset EGAD00001007765

• Disease specific alterations in the olfactory mucosa of patients with Alzheimer’s disease

  The sample AD_Library_1, AD_Library_2 and Control_Library were run on a Chromium Chip B with the Chromium Single Cell 3′ Library & Gel Bead Kit v3 kit (10x Genomics, CA, USA) . The 3’ gene expression libraries were sequenced at an approximate depth of 50,000 reads per cell using the NovaSeq 6000 S1 (Illumina, San Diego, CA, USA) flow cells. Cell Ranger v.3.0.2 was used to analyze the raw base call files. FASTQ files and raw gene-barcode matrices were generated and aligned human genome GRCh37 (hg19). The samples were integrated in R v.4.0.3 and generated Seurat objects, two related to AD samples and one to control samples, were analyzed using the Seurat package v.4.0.3 to perform downstream analysis, clustering of the cells and differential expression.

  Dataset EGAD00001008560

• Timing chromosomal amplification events using patterns of somatic mutations in high hyperdiploid acute lymphoblastic leukemia

  This dataset included 19 paired diagnostic and remission samples with high hyperdiploid acute lymphoblastic leukemia (ALL) that were collected from four different cohorts: the Division of Clinical Genetics, Lund University, Sweden. All samples were subjected to whole genome sequencing using the Illumina HiSeqX platform. Paired-end sequencing (2x150bp) was done to ~60x coverage for diagnostic samples and ~30x coverage for remission samples. The paired-end reads were aligned to the human reference genome GRCh37 (ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/vertebrate_mammalian/Homo_sapiens/all_assembly_versions/GCF_000001405.25_GRCh37.p13/GCF_000001405.25_GRCh37.p13_genomic.fna.gz) by the Burrows-Wheeler Aligner tool (version 0.7.17). Duplicate reads marking and local realignment were performed by GATK (version 4.0.11.0).

  Dataset EGAD00001010103

• Evaluating gene expression in aggressive B-cell lymphoma using a quantitative nuclease protection assay

  Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma (NHL), comprising 25-30% of all NHL in developed countries with an annual incidence in the USA of 7 cases/100000 persons/year. Collectively, DLBCL is classified based on a common morphological appearance of diffuse growth of large transformed B-cells, immunophenotype, high proliferation rate and aggressive behaviour. Despite these similarities, DLBCLs are a heterogeneous collection of malignancies with distinct clinical and molecular characteristics that do not always correlate with immunohistological features. This gene expression dataset includes transcriptomes of ABC-DLBCLs and of GCB-DLBCLs where cell of origin is determined by the HTG-EdgeSeq quantitative nuclease protection assay. Also included are clonality results from BCR profiling from high-grade B-cell lymphomas sequenced using a NOVA sequencer

  Dataset EGAD00001011309

• Variant calling analysis of cfDNA whole exome sequencing in neuroblastoma

  This dataset contains VCF files from a variant calling analysis of 19 neuroblastoma patients. WES or WGS data of the primary tumor were compared to WES cfDNA analysis at the time of diagnosis and at a 2nd timepoint (complete remission, partial remission, disease progression or relapse). For 4 patients, WGS of germline, tumor at diagnosis and tumor at relapse DNA was performed on Illumina HiSeq2500, with 100-bp paired-end reads. For the other patients, WES was performed using either an AgilentSureSelect Human All Exon v5 or a Roche Nimblegen SeqCap EZ Exome V3 kit on Illumina HiSeq2000, with 100-bp paired-end reads. SNVs observed in any of the primary tumors or cfDNA samples studied by WES were targeted using a capture sequencing panel at all intermediate time points.

  Dataset EGAD00001003803

• Data distribution Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue Here, we show the amount of data distributed by the EGA. Data Distributed / Live EGA Data Distribution / Live SFTP Aspera HTSGET lineChartLive("svg#ega-dist-live", document.querySelector("#ega-figure-dist-live figcaption")); Data Distributed The below figure represents the cumulative EGA data distribution via the download clients(v2 and v3.x api versions) using HTTPS, FTP, and download boxes using ASPERA. You can see cumulative values by clicking "Cumulative". EGA Data Distribution //lineChart('#ega-data-distribution svg.stats', 'https://stats.ega-archive.org/distribution', // ['Amount of Distributed Data', ['Aspera', 'Download Clients', 'Total']]) curveChart('#ega-data-distribution', [ { domId: 'stats-aspera', label: 'Aspera', url: 'https://stats.ega-archive.org/distribution/aspera' }, { domId: 'stats-sftp' , label: 'SFTP', url: 'https://stats.ega-archive.org/distribution/sftp' }, //{ domId: 'stats-htsget', label: 'HTSGET', url: 'https://stats.ega-archive.org/distribution/htsget' }, { domId: 'stats-streamer' , label: 'Download Client', url: 'https://stats.ega-archive.org/distribution/streamer' }, { domId: 'stats-total' , label: 'Total', url: 'https://stats.ega-archive.org/distribution/total' } ] );

  Documentation about/statistics/distribution

• Validation_of_Exome_sequencing_of_S7RE_iPSC_lines

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. 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/

  Study EGAS00001000423

• Deep_sequencing_of_S7EPC_genome

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. 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/

  Study EGAS00001000437

• Genomic and epigenomic insights into the origin, pathogenesis and clinical behavior of mantle cell lymphoma subtypes

  Mantle Cell Lymphoma can be subdivided into conventional (cMCL) and leukemic non-nodal MCL (nnMCL), which differ in the cell of origin, gene expression, biological characteristics and clinical evolution. Using genomic, epigenomic and transcriptomic data we identified common and particular alterations in the two subtypes, either point mutations, copy number alterations or structural variants some of them with prognostic impact.

  Study EGAS00001004165

• Sequencing of heritable Bleeding and Platelet Disorders

  The BRIDGE-BPD study aims to discover new causal genes for Bleeding and Platelet Disorders (BPD) by high throughput sequencing using cluster analyses based on improved and standardized deep phenotyping of cases. BPD is one of the 13 Rare Disease projects under the NIHR BioResource Rare Diseases BRIDGE consortium, which is a collaboration aiming to discover the genetic sequence variants underlying unresolved inherited disorders and to improve identification of already identified high penetrance variants.

  Study EGAS00001001172

• Validation_of_SNVs_found_by_Exome_seq_in_S2_SF1___SF5_and__SF9_hiPSCs

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. 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/

  Study EGAS00001000464

• Subclonal_analysis_in_S7RE2_and_S7RE14_iPS_cells

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. 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/

  Study EGAS00001000441

• IgCaller

  IgCaller is a python program designed to fully characterize the immunoglobulin (IG) gene rearrangements and oncogenic translocations in lymphoid neoplasms from whole-genome sequencing (WGS) data. Using a cohort of 331 patients comprising different subtypes of B-cell neoplasms, we demonstrate that IgCaller identifies both heavy and light chain rearrangements providing additional information on their functionality, somatic mutational status, class switch recombination, and oncogenic IG translocations. We provided here IG reads of the previously unpublished WGS.

  Study EGAS00001004298

• Exome sequencing of advanced hepatocellular carcinoma

  The aim of our project is to decipher the genomic of advanced hepatocellular carcinoma using whole exome sequencing. To this purpose, we aim to compare genetic landscape of advanced hepatocellular carcinoma with early tumor in order to understand the mechanisms of tumor progression. This work will also help to identify new therapeutic targets potentially useful to treat patients at advanced stage. This study contain whole exome sequencing aligned reads for 41 tumor with matched normal samples

  Study EGAS00001003130