12214 results for "cancer rna-seq"

in 33.94 milliseconds.

• ICGC PedBrain: RNA sequencing

  ICGC PedBrain: RNA sequencing

  Dataset EGAD00001000328

• A method for multiplexed full-length single-molecule sequencing of the human mitochondrial genome

  Here we describe a method to target, multiplex and sequence full-length, native single-molecule the human mitochondrial genome utilizing the RNA-guided DNA endonuclease Cas9.

  Study EGAS00001006203

• Exome and RNA sequencing data for Diffuse Large B Cell Lymphomas

  Exome sequencing data for 1001 DLBCL patients and RNA sequencing data for 775 DLBCL patients

  Dataset EGAD00001003600

• Single-cell RNA sequencing of acute myeloid leukemia patients

  Single-cell RNA sequencing was performed on bone marrow mononuclear cells from 8 acute myeloid leukemia patients at diagnosis. The profiling was performed using 10x Genomics 3' (5 samples) and 5' (3 samples) platforms. The raw data are available as fastq files.

  Dataset EGAD00001006173

• Small molecule screen reveals synergy of cell cycle checkpoint kinase inhibitors with DNA-damaging chemotherapies in medulloblastoma (methylation dataset)

  human medulloblastoma xenograft isolated from mouse brain was frozen and genomic DNA or RNA was extracted. Bisulfite converted DNA was processed and hybridised to illumina EPIC or 450K arrays using standard protocols. RNAseq was performed on total RNA.

  Dataset EGAD00001006583

• Single cell RNA-sequencing of treatment naïve PDAC patient samples

  Single cell RNA-sequencing of treatment naïve PDAC patient samples. We have 10 samples, sequenced using the 10X genomics chromium platform with 3 prime chemistry. We are submitting FASTQ files representing the index files (I1), Read1 (R1) and Read2 (R2).

  Dataset EGAD00001008961

• Primary_DIPG_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

  Dataset EGAD00001011080

• Whole exome sequencing and RNA sequencing of lineage-switched acute myeloid leukemia with KMT2A-AFF1 rearrangement

  We performed whole exome sequencing and RNA sequencing of lineage-switched acute myeloid leukemia (LS AML) with KMT2A-AFF1 rearrangement to elucidate the feature and potential treatment targets. Notably, LS AML possessed gene expression signatures of monocytic myeloid derived suppressor cells (M-MDSCs). Several known genes related to MDSCs were highly expressed in LS AML, which could be novel treatment targets.

  Study JGAS000631

• Identification of Long Non-coding RNA Biomarker of Human Lupus Nephritis Disease Activity

  Total RNA sequencing was performed on whole blood samples from 74 Lupus nephritis (LN) patients and 20 healthy controls. Differential expression analysis and weighted gene co-expression network analysis were performed to characterise expression changes of long non-coding RNAs (lncRNAs) in LN and identify lncRNAs with a key role in disease activity that could be used as potential blood-based biomarkers.

  Study EGAS00001007117

• Single-cell RNA sequencing on single CD45+ immune cells isolated from peripheral blood, lymphnode, ascites, tumour and adjacent normal tissues from six hepatocellular carcinoma patients.

  Single-cell RNA sequencing on single CD45+ immune cells isolated from peripheral blood, lymphnode, ascites, tumour and adjacent normal tissues from six hepatocellular carcinoma patients. The transcriptional properties of these individual cells, were used to delineate the molecular subtypes, lineage, and functional properties of each cell group

  Study EGAS00001003449

• Seminal Plasma RNA DAC

  Dac EGAC00001002111

• Subtyping Sub-Saharan Esophageal Squamous Cell Carcinoma by Comprehensive Molecular Analysis

  Esophageal squamous cell carcinoma (ESCC) occurs as much as 20x more frequently in sub-Saharan Africa than Western countries. Through the UNC-Malawi project collaboration we obtained whole-exome matched tumor/normal and RNA sequencing of 59 ESCC from Malawi between 2011-2012. DNA analysis revealed similar mutations as other cohorts, while RNA analysis revealed three distinct subtypes. Mutational signature analysis revealed a pattern of mutation not previously reported in other cohorts or more broadly. Taken together this suggests the high prevalence of ESCC in the region is secondary to an as yet identified mutagen.

  Study phs001448

• The Genetic and Transcriptomic Evolution of Melanoma

  The overarching goal of the study was to better understand the evolution of melanoma. To do this, we collected archival tissue of melanomas adjacent to their intact, remnant precursor lesions. We also collected archival tissue of primary melanomas and their matching metastases. From the formalin-fixed paraffin-embedded (FFPE) blocks, we microdissected non-neoplastic (normal), precursor, and descendent portions of tissue. Both RNA and DNA were extracted from the microdissected tissues and subjected to next generation sequencing. In summary, we performed matched DNA/RNA sequencing of melanoma/precursor/normal trios, allowing us to trace the genetic and transcriptomic evolution of melanoma.

  Study phs001550

• Whole Exome Sequencing of Uveal Melanoma

  Uveal melanoma is a rare form of melanoma that occurs in the eye and has no effective treatment once metastatic. To further characterize the genomic events driving uveal melanoma, whole exome sequencing was performed on 61 primary tumors derived from enucleations, 3 liver metasases, and paired normal DNA. Recurrent somatic genetic alterations including point mutations, small insertions and deletions, as well as copy number variations were identified. In addition, RNA sequencing of uveal melanoma cell lines expressing shRNAs was performed from total RNA as well as polysome-associated mRNA in order to identify transcripts regulated by EIF1AX at the level of translation.

  Study phs001370

• Type I Interferon and Cycling Lymphocytes in Macrophage Activation Syndrome

  We performed immune profiling of peripheral blood mononuclear cells from patients with Still's disease and macrophage activation syndrome (MAS) using bulk RNA sequencing and single-cell RNA sequencing. Three groups were included in the study: healthy controls, patients with Still's disease without macrophage activation syndrome, and patients with Still's disease and macrophage activation syndrome. We found that macrophage activation syndrome is associated with transcriptomic signatures of interferon upregulation and cell cycling. We identified cycling lymphocytes within T cell and NK cell populations that are correlated with MAS disease activity. All sequencing data are available through dbGaP.

  Study phs003310

• Wnt Activity Reveals Context-Dependent Genetic Effects on Gene Regulation in Neural Progenitors

  In this study we aimed to identify context-dependent regulatory functions of common genetic variation after stimulation of the canonical Wnt pathway. Fetal cortical tissue between 14 and 21 gestation weeks was subjected to RNA-Sequencing (242 samples) and ATAC-Sequencing (222 samples) to profile expression and chromatin accessibility, respectively. Considering donor genotypes, we were able to identify eQTLs, caQTLs, as well as response QTLs of both categories. The dataset provided here includes 242 RNA-sequencing files in bam format and 222 ATAC-sequencing files in bam format. We also provide 83 donor genotypes in VCF format (hg38).

  Study phs003642

• Leucocyte eQTLs in autoimmune disease and health

  Peripheral blood was taken from healthy controls and patients with active autoimmune disease. CD4 T cells, CD8 T cells, monocytes, neutrophils, and B cells were separated using magnetic-activated cell sorting. RNA and genomic DNA was extracted from cell lysates using Qiagen Allprep kits. Genotyping of healthy controls and patients with inflammatory bowel disease was performed using the Illumina Human OmniExpress12v1.0 BeadChip at the Wellcome Trust Sanger Institute. 200 ng RNA was processed for hybridization onto Affymetrix Human Gene ST 1.1 microarrays. Gene expression and genotyping data was used to perform eQTL mapping.

  Study EGAS00001001251

• Profiling of childhood neuroblastoma and the immune microenvironment by single-cell sequencing of RNA and TCR

  Neuroblastoma tumor cells and their tumor microenvironment are studied by single-cell RNA sequencing of primary neuroblastoma tumors and neuroblastoma-infiltrated tissues/metastases. Both diagnostic samples, taken pre-treatment and samples taken after induction chemotherapy at surgical resection and biopsies from relapse samples are included.  For a number of patients single-cell RNA sequencing of blood samples (controls) are included and additionally we performed single-cell T cell receptor sequencing (TCR) on the tumor and blood samples. With this study, we will focus on identifying differences in tumor cells and their (immune) microenvironment 1) before and after treatment or at relapse and 2) between primary tumors and infiltrated tissues/metastases. Moreover, with TCR sequencing we aim to unveil immune cell dynamics in patients with neuroblastoma.

  Study EGAS00001006823

• snRNA-seq in white matter post-mortem tissue from MS and controls - DAC

  Dac EGAC00001001105

• DAC for scRNA-seq and scp-MS data on human bone marrow

  Dac EGAC00001003505

• whole exome seq

  whole exome sequencing data

  Dataset EGAD00001004464

• Comprehensive molecular profiling of ETMR

  ETMR RIPSeq

  Dataset EGAD00001004802

• Whole exome sequencing and RNA sequencing of cervical cancer

  We designed this study to identify molecular markers involved in the development and prognosis of cervical adenocarcinoma. In this study, we would like to elucidate the molecular biological characteristics of cervical adenocarcinoma in relation to the carcinogenesis of other cervical cancers (squamous cell carcinoma), vaginal and vulvar cancers. In addition, some squamous cell carcinomas of the cervix develop at a young age and have a poor prognosis. Furthermore, small cell carcinoma of the cervix also progresses rapidly and has a poor prognosis, making the establishment of diagnostic and therapeutic methods an urgent task.

  Study JGAS000586

• Whole exome sequencing and RNA sequencing of cervical cancer

  We designed this study to identify molecular markers involved in the development and prognosis of cervical adenocarcinoma. In this study, we would like to elucidate the molecular biological characteristics of cervical adenocarcinoma in relation to the carcinogenesis of other cervical cancers (squamous cell carcinoma), vaginal and vulvar cancers. In addition, some squamous cell carcinomas of the cervix develop at a young age and have a poor prognosis. Furthermore, small cell carcinoma of the cervix also progresses rapidly and has a poor prognosis, making the establishment of diagnostic and therapeutic methods an urgent task.

  Study JGAS000582

• Raw DNA and RNA data from breast cancer organoids, control samples and biopsies

  Whole genome sequencing data for primary tumors, matching control material from blood and their corresponding organoid. Whole transcriptome data for organoids.

  Dataset EGAD00001003751

• Whole-genome sequence data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Each tumor sample was cut into three pieces, yielding two end-pieces for cryovials and a middle portion placed in 10% buffered formalin. End pieces were homogenized manually and with a paddle blender (Stomacher). All paraffin-embedded blocks, including formalin-fixed tumor samples and molecular-fixed fallopian tubes, were sectioned and stained with hematoxylin and eosin prior to expert histopathological review to confirm the presence of high grade serous carcinoma. Homogenized end pieces were then flash frozen and later used for WGS. For all tumor and matched normal (peripheral blood) samples, DNA was extracted with the Qiagen AllPrep DNA/RNA kit (tumor samples from patients 25,26,28-32) or the Qiagen Blood and Tissue Extraction Kit (tumor samples from patients 1-4,7,9-17, and all blood samples). For all tumor and normal samples, DNA extraction was followed by library construction and sequencing using Illumina HiSeq2500 whole genome shotgun v4 chemistry with paired-end 125bp reads.

  Dataset EGAD00001003984

• Myeloid cell programming in patients with non-medullary thyroid carcinoma

  This dataset contains single-cell RNA sequencing data from patients with thyroid cancer (n=7), multinodal Goiter (n=3) and healthy individuals (n=5). Mononuclear cells were taken from both the peripheral blood and the bone marrow compartments. We used a pooled single-cell design where multiple individuals were pooled in a single sample for sequencing (NextSeq 500-V2) and later demultiplexed using their genotype data. Associated metadata contains information on the phenotypes per individual, the pooling design and the linkage between the supplied files and sequenced pools. Due to limitations from EGA in uploading single-cell data, the raw fastq files were processed as follows: (i) I1/I2/R1/R2 fast files were concatenated over the different lanes. (ii) Concatenated I1 and I2 files were interleaved, as were the concatenated R1 and R2 files to generate two fastq files per pool containing all the information. To interleave the fastq files, the BBmap tool bbmap/reformat.sh was used, which can also be used to de-interleave the files.

  Dataset EGAD00001008108

• Distinct embryonic phylogenies and driver events of infant Wilms tumor - RNA

  Cancers of adults typically arise through progressive rounds of clonal diversification and intratumoral selective sweeps which generate a long mutational trunk with shorter subclonal branches. Here, we investigated whether tumors of young children exhibit the same phylogenetic configuration. We studied three infants, including two newborns, with the childhood kidney cancer, Wilms tumour, through whole genome sequencing of bulk tissues, of single cell derived organoids, and of microdissections. All three cancers exhibited unusual driver events, with tumours of newborns harbouring FOXR2 rearrangements, delineating a distinct variant of Wilms tumour. Phylogenetic analyses suggest that tumors were seeded in an early, possibly confined window of development. Unusually, following seeding there was extensive polyclonal diversification with little evidence of clonal sweeps, leading to a distinct phylogenetic configuration more reminiscent of normal tissues rather than of adult cancers. These findings indicate that some childhood cancers may diversify via unorthodox phylogenetic pathways.

  Dataset EGAD00001009813

• Single Cell Genotypic and Phenotypic Analysis of Measurable Residual Disease in Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) is a group of blood cancers with high mortality. Even though complete remission is often achieved, majority of the AML patients still relapse. Measurable residual disease (MRD), defined as the population of cancer cells which persists following chemotherapy, is responsible for AML relapse. Understanding the biology enabling MRD clones to resist therapy is necessary to guide the development of curative treatments more effectively. Discriminating residual leukemic clones, preleukemic clones, and normal precursors remains a challenge with current MRD tools. We developed a single cell MRD (scMRD) assay by combining flow cytometric enrichment of the targeted precursor/blast population with integrated single cell DNA sequencing (scDNA-seq) and immunophenotyping (Tapestri, Missionbio). The platform utilizes a custom amplicon panel covering 109 amplicons across 31 genes frequently mutated in AML and a panel of 42 oligo-conjugated antibodies against surface makers. We applied our scMRD assay to sequence 30 MRD samples (multiplexed into 6) from 29 AML patients to study the clonal architecture and protein correlation. In addition, 2 MRD samples were sequenced with scDNA+protein sequencing technology without enrichment or multiplexing. Five patients with AML at diagnosis were also sequenced with scDNA+protein sequencing technology without enrichment or multiplexing. In order to establish the sensitivity of our scMRD assay, we spiked AML cells into normal bone marrow cells. We sequenced 12 such spiked samples after multiplexing.

  Study phs003233

• Genetic and epigenetic characterization of adenoid cystic carcinoma

  Translocation events are frequent in cancer and may create chimeric fusions or regulatory rearrangements that drive oncogene overexpression. Although regulatory rearrangements are increasingly recognized in hematopoietic and even solid tumors, the underlying mechanisms remain obscure. Here we identify super-enhancer translocations that drive overexpression of the oncogenic transcription factor MYB as a unifying theme in adenoid cystic carcinoma (ACC). Whole genome sequencing data and chromatin state maps for 13 primary tumors and xenografts reveal distinct chromosomal rearrangements that juxtapose super-enhancer clusters to the MYB locus. Chromosome conformation capture confirms that the translocated enhancers physically interact with the MYB promoter. Remarkably, the MYB product itself binds to the translocated enhancers, thus creating a positive feedback loop that sustains its own expression. MYB also binds a large number of active enhancers that drive opposing regulatory programs in alternate cell lineages in ACC. MYB cooperates with the transcription factor TP63 in the myoepithelial component of the tumors, but promotes a Notch program in the luminal epithelial component. Bromodomain inhibitors, which disrupt enhancer function, slow tumor growth in ACC primagraft models in vivo, but are ineffective against high grade tumors that harbor activating mutations in the Notch pathway. Thus, our study identifies super-enhancer translocations as a unifying feature of ACC, and provides insight into the mechanism by which sustained MYB overexpression drives alternate cell fates in this disease.Processed ChIP-seq data is available on GEO under accession number GSE76465.

  Study EGAS00001001457

• RNA sequencing of undifferentiated sarcomas

  Dac EGAC00001001055

• Human Biofluid RNA Atlas DAC

  Dac EGAC00001001338

• ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells-of-origin

  Cell-free DNA in human plasma provides access to molecular information about the pathological processes in the organs or tumors from which it originates. These DNA fragments are derived from fragmented chromatin in dying cells, and retain some of the cell of origin histone modifications. Here, we apply chromatin immunoprecipitation of cell-free nucleosomes carrying active chromatin modifications followed by sequencing (cfChIP-seq) to 268 human samples. In healthy donors, we identified bone marrow megakaryocytes, but not erythroblasts, as major contributors to the cfDNA pool. In patients with a range of liver diseases, we show that we can identify pathology-related changes in hepatocyte transcriptional programs. In metastatic colorectal carcinoma patients, we detected clinically relevant, and patient-specific information, including transcriptionally active HER2 amplifications. Altogether, cfChIP-seq using low sequencing depth, provides systemic and genome-wide information, can inform diagnosis, and facilitate interrogation of physiological and pathological processes using blood samples.

  Study EGAS00001004913

• ChIP-seq of plasma cell-free nucleosomes identifies cell-of-origin gene expression programs

  Dac EGAC00001001875

• Epitope-linked Ig-seq of self-reactive plasma cells in celiac disease

  Study EGAS00001003658

• Human Inflammatory Skin Disease scRNA-seq

  Study EGAS00001005271

• EGFR Mutant SCLC transformed exome seq

  Dataset EGAD00001001436

• ATRT ChIPSeq H3K27ac

  ATRT ChIPSeq H3K27ac

  Dataset EGAD00001004836

• Characterization of Structural Variants in Acute Myeloid Leukemia Patients

  Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and is expected to increase in frequency as the population ages. Most subtypes of AML are difficult to treat, in part due to a lack of understanding of possible molecular targets. Furthermore, the peak incidence of AML is in the sixth decade, and patients over the age of 65 do not tolerate chemotherapeutic regimens well. Moreover, AML has been highly studied as a model for other cancers. An RNA Biology Program is established aiming to develop comprehensive datasets through the profiling of all different classes of RNA expression, RNA editing, alternative splicing, and non-coding RNAs in CD34+ normal hematopoietic stem cells (HSC), their differentiated progeny, and AML clinical samples that could be utilized to understand leukemia. These datasets will allow us to computationally identify and characterize various RNA species and processes to enable the development of effective therapeutics to AML, leukemia and other types of cancers. Epigenetic factors such as methylation and histone modifications will also be characterized from these clinical samples allowing for integrated dataset analysis to look at the cross-talk between RNA and DNA/epigenomics in leukemia. The following is a subsidiary study of the above study description where whole genome sequencing was performed on two collected AML patients' samples using Illumina and Oxford Nanopore sequencing technologies. The aim is to characterize the roles of structural variants (SV) in RNA biology which are potentially important for AML development using our own established long-read SV characterization tool, NanoVar. The advent of Oxford Nanopore sequencing technologies has opened a new avenue for better SV characterization by having longer sequencing reads. NanoVar is an accurate and rapid SV characterization tool that utilizes low-depth Nanopore sequencing data. NanoVar makes use of split-reads and hard-clipped reads for SV discovery and employs a simulation-trained neural network classifier for true positive enrichment. NanoVar exhibited higher accuracy and faster computational speed amongst other long-read SV detection tools in simulated data. In AML patient data, NanoVar displayed excellent accuracy in SV characterization (16/16 SVs validated in two patients) by using only 4x depth sequencing data. In summary, NanoVar improves the accuracy and speed of SV characterization at a lower sequencing cost, an approach compatible with clinical studies.

  Study phs001847

• PEDS-PLAN - Pediatric Precision Laboratory Advanced Neuroblastoma Therapy

  A multi-center clinical trial for newly diagnosed high-risk neuroblastoma patients. Molecular tumor boards selected one of six targeted agents based on tumor-normal whole exome sequencing and tumor RNA sequencing data.

  Study phs002303

• Effects of GATA4-inhibiting compound 3i-2012 on HB-243 hepatoblastoma cells

  In order to study the effects of GATA4 inhibition, HB-243 hepatoblastoma cells were treated with GATA4-inhibiting compound 3i-2012 for 24 hours. Total RNA was extracted and sequenced.

  Study EGAS50000000999

• Small intestinal neuroendocrine tumors

  The goal of this study was to gain insights into the transcriptomes, mutations and copy number variants present in small intestinal neuroendocrine tumors. The present dataset contains RNA-sequencing performed on seven such tumors.

  Study EGAS00001003358

• MS meninges single nuclei RNA sequencing

  10X 3' (RNA) samples of isolated single nuclei from highly inflamed leptomeninges and adjacent grey matter from 3 MS patients used in the paper.

  Dataset EGAD50000001235

• Single-cell RNA-sequencing of peripheral blood mononuclear cells from patients with achalasia

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peripheral blood mononuclear cells (PBMC) from patients with achalasia. Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000250

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 4)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one ETV6::RUNX1 ALL patient (ALLK-132). Novogene's internal method was used in directional library preparation including rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq X Plus, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002590

• RNA sequencing and whole-genome mate-pair sequencing of osteosarcoma

  This data set includes 72 mate pair sequenced osteosarcomas (36 as part of a discovery cohort and 36 as part of a validation cohort). It also includes RNA-sequencing data on 67 osteosarcomas (mostly overlapping with the above mate pair sequenced cases) and 13 osteoblastomas used as controls for gene expression levels.

  Dataset EGAD00001005307

• RNA sequencing of Human Organoid Lines

  The study will use RNA sequencing to aid in benchmarking different culture conditions in a set of genetically annotated human organoid lines. The data will be used to assess whether there are any clonal differences introduced when culturing these lines in different conditions.

  Dataset EGAD00001007971

• Illumina 5'end RNA sequencing

  The dataset contains 200 fastq files of Illumina 5'end RNA sequencing data of 50 PBMC samples. The paired-end data includes 100 fastq files (R1 and R2) of 50 full-length cDNA sequencing libraries and 100 fastq files (R1 and R2) of 50 HLA amplicon sequencing libraries.

  Dataset EGAD00001006838

• Blood and skin fibroblasts PSA study

  This dataset contains RNA-sequencing of blood samples from Healthy Controls (n=7), PSA patients (n=27) and RA patients (n=9). It also contains RNA-sequencing data of skin fibroblasts from healthy controls (n=3) and PSA patients (n=3).

  Dataset EGAD00001009069

• Single-cell RNA sequencing of chronic-phase chronic myeloid leukemia patients

  Single-cell RNA sequencing of viably frozen cells from 12 samples from four chronic-phase chronic myeloid leukemia patients. The raw data is available as fastq files.

  Dataset EGAD00001009086

• Paired RNA sequencing of 30 samples RRMM (multiple myeloma)

  Paired RNA sequencing of 30 samples RRMM using Illumina TruSeq stranded mRNA kit and either HiSeq2000 or HiSeq X Ten for sequencing.

  Dataset EGAD00001009680

• Ovarian Carcinosarcoma DNA and RNA sequencing of patient samples in the UK cohort.

  Ovarian Carcinosarcoma DNA and RNA sequencing of patient samples in the UK cohort (n=18).

  Dataset EGAD00001011068

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Dataset EGAD00001011079

• RNA sequencing data from children with febrile illness and multisystem inflammatory syndrome in children (MIS-C)

  RNA sequencing data from children with febrile illness and multisystem inflammatory syndrome in children (MIS-C). Samples used were Whole Blood. Febrile illness controls include children with bacterial and viral infections and healthy controls. This dataset contains samples from patients recruited into the DIAMONDS study.

  Dataset EGAD00001011134

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

  Data supporting: "TBC" Ganguli et al (RNA for 394 samples)

  Dataset EGAD00001011190

• H3K27ac ChIP-seq in primary inflammatory (TPP) macrophages

  We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases, and identified the molecular mechanism by which the risk haplotype increases expression of the causal gene, ETS2. This mechanism was predicted to alter enhancer activity at the disease-associated locus. We therefore performed H3K27ac ChIP-seq in inflammatory macrophages from minor and major allele homozygotes at the causal allele and investigated the effect on enhancer activity. In doing so, we mechanistically delineated how the risk haplotype increases expression of ETS2.

  Study EGAS00001007562

• BLUEPRINT Bisulfite-seq (CNAG)

  Bisulfite-Seq

  Study EGAS00001000418

• prDLBCL WXS/RNA Data Commitee

  Dac EGAC50000000284

• scRNA-seq reveals alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease

  Dac EGAC00001001547

• ChIP_PEAKS

  ChIP-seq narrowPeaks. Software: MACS2 v2.1.2

  Dataset EGAD00010001923

• The paired FF/FFPE colon set, Exome-Seq

  Dataset EGAD00001000834

• Atezolizumab Plus Personalized Neoantigen Vaccination in Patients with Urothelial Cancer: a Phase 1 Trial

  This is a phase 1 single center clinical trial evaluating a multi-peptide personalized neoantigen vaccine, PGV001, in combination with atezolizumab for patients with urothelial cancer. Patients were enrolled in either the adjuvant or metastatic setting. Those in the adjuvant setting included patients considered high risk of recurrence (pathological stage ypT2-T4 or ypN+ for those treated with prior neoadjuvant chemotherapy or pT3-T4 or pN+ for those not treated with prior neoadjuvant chemotherapy). Those in the metastatic setting included patients progressing after prior chemotherapy or those with at least stable disease after chemotherapy treated as “switch maintenance” therapy. The primary endpoint was feasibility (including the number of neoantigens identified per patient, vaccine production time, the proportion of patients consenting to the vaccine development phase for whom a vaccine product was prepared, and the proportion of patients eligible for the treatment phase who completed the priming cycle 1 of PGV001 plus atezolizumab) and safety. Secondary endpoints included the objective response rate, progression-free survival or disease-free survival, overall survival, and immunomodulatory effects of treatment. Urothelial tumor tissue and normal tissue or peripheral blood specimens were utilized for DNA sequencing. HLA typing was performed utilizing genomic DNA isolated from whole blood, and RNA sequencing was performed utilizing tumor tissue specimens. Neoantigen prediction and final selection for incorporation into the vaccine was determined by the OpenVax computational pipeline. 12 patients were initially enrolled into the vaccine development phase and 10 patients initiated the treatment phase. PGV001 was administered with poly-ICLC and tetanus peptide on subsequent days for up to 10 doses, including an initial priming cycle 1. Atezolizumab was administered every 3 weeks for up to 1 year in the adjuvant setting or 2 years in the metastatic setting. The vaccine was feasible and safe, the median vaccine production time was 20.3 weeks, and 100% of patients that initiated the treatment phase completed the priming cycle. The most common treatment-related adverse events were local grade 1 injection site reactions, fever, and fatigue. Three of the 4 patients in the adjuvant setting remained disease-free at median follow-up of 39.5 months. There was a 40% objective response rate among patients with measurable disease in the metastatic setting. The single patient treated as “switch maintenance” therapy remained with no evidence of disease at 39.4 month follow-up. All patients demonstrated on-treatment neoantigen-specific T cell reactivity, as measured by ELISPOT and flow cytometry assays. Overall, PGV001 plus atezolizumab was feasible, safe, and warrants further investigation. Whole exome sequencing from tumor tissue and normal tissue or whole blood specimens and RNA sequencing from tumor tissue specimens will be available through dbGaP.

  Study phs003922

• Single-Cell RNA-Sequencing of Bone Marrow and Circulating Tumor Cells from Patients with Multiple Myeloma and its Precursor Conditions

  We performed single-cell RNA and V(D)J-sequencing of tumor cells from bone marrow and peripheral blood specimens and patients with Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), and Multiple Myeloma (MM), as well as healthy donors. In this study we aimed to shed light on the mechanisms underlying tumor cell circulatory capacity and dissemination.

  Study phs003855

• DNA and RNA sequencing data from Ovarian Carcinosarcoma patients from the Glasgow Cohort.

  In this study, we analysed DNA and RNA sequencing data from Ovarian Carcinosarcoma patients, from isolated carcinoma and sarcoma components and investigated DNA variants as well as gene expression. Genomic analyses from this data and further investigation from preclinical models of ovarian carcinosarcoma support the conversion theory for disease development and indicate that microtubule inhibitors could be used to suppress EMT and stimulate anti-tumour immunity.

  Study EGAS00001006605

• AML Proteogenomic Landscape Whole-transcriptome RNA-Sequencing

  Whole transcriptome RNA-sequencing of purified bone marrow blasts of 136 de novo, treatment naive AML patients. For further details, we refer to the manuscript "The Proteogenomic Landscape of AML" by Jayavelu, Wolf, Buettner et al. mRNA extraction and whole transcriptome sequencing For transcriptome analysis the TruSeq Total Stranded RNA kit was used, starting with 250ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (Illumina, San Diego, CA, USA). 100bp paired-end reads were sequenced on the NovaSeq 6000 (Illumina) with a median of 57 mio. reads per sample. RNA Data Analysis Data quality control was performed with FastQC v0.11.9. Reads were aligned to the human reference genome (Ensembl GRCh38 release 82) using STAR v2.6.1. Gene count tables were generated while mapping, using Gencode v31 annotations. All downstream analyses were carried out using R v4.0 and BioConductor v3.12 (Huber et al., 2015; R Core Team, 2020). Size-factor based normalization was performed using DESeq2 v1.28.1(Love et al., 2014).

  Dataset EGAD00001008484

• Custom long non-coding RNA capture DAC

  Dac EGAC00001002198

• GLASS-NL RNA-sequencing Study

  Study EGAS00001007551

• Single cell analyses of transcriptome and epigenome in neuroblastoma infiltrated bone marrow

  We report transcriptional and genome-wide ATAC-seq analyses at single cell resolution of 16 bone marrow samples with and without neuroblastoma infiltration. Our samples span across several neuroblastoma models, including MYCN amplified, ATRX mutated, and sporadic (lacking either alteration).

  Study EGAS00001006106

• EED inhibition of organoid development

  Transcriptomics and epigenomics after chemical inhibition of EED during early human brain organoid development. To investigate the role of H3K27me3 inhibition during neuroectoderm induction, we treated brain organoids with 3 concentrations of EED inhibitor (and control) during the transition of pluripotency to neuroepithelium. At the neuroepithelium stage, we profiled the organoids using scRNA-seq (transcriptome) and bulk Cut&Tag (H3K27me3, H3K27ac). Library preparation for scRNA-seq was carried out with the 10x genomics platform.

  Dataset EGAD50000000224

• snRNA-seq in white matter post-mortem tissue from MS and controls

  This Dataset is currently hosted by the European Nucleotide Archive. To access the data contained within the Dataset please follow the link below: https://www.ebi.ac.uk/ena/browser/view/PRJEB39323 Dataset consists of 20 snRNA-seq bam files from 10X v2. 5 samples from postmortem white matter tissue from non-neurological controls and15 samples from different MS lesions from the white matter tissue of 4 postmortem progressive MS patients.

  Dataset EGAD00001004544

• BLUEPRINT release August 2014, ChIP-Seq for mature neutrophil

  ChIP-Seq data for 7 mature neutrophil sample(s). 68 run(s), 50 experiment(s), 50 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000930

• BLUEPRINT release August 2014, ChIP-Seq for mature eosinophil

  ChIP-Seq data for 1 mature eosinophil sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000906

• BLUEPRINT release August 2014, ChIP-Seq for inflammatory macrophage

  ChIP-Seq data for 3 inflammatory macrophage sample(s). 21 run(s), 21 experiment(s), 21 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000940

• BLUEPRINT release August 2014, ChIP-Seq for alternatively activated macrophage

  ChIP-Seq data for 4 alternatively activated macrophage sample(s). 29 run(s), 28 experiment(s), 28 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000938

• BLUEPRINT release January 2015, ChIP-Seq for mature neutrophil

  ChIP-Seq data for 7 mature neutrophil sample(s). 78 run(s), 60 experiment(s), 60 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001149

• BLUEPRINT release January 2015, ChIP-Seq for alternatively activated macrophage

  ChIP-Seq data for 5 alternatively activated macrophage sample(s). 36 run(s), 35 experiment(s), 35 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001155

• BLUEPRINT release January 2015, ChIP-Seq for macrophage

  ChIP-Seq data for 13 macrophage sample(s). 55 run(s), 55 experiment(s), 55 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001196

• BLUEPRINT release January 2015, ChIP-Seq for inflammatory macrophage

  ChIP-Seq data for 6 inflammatory macrophage sample(s). 35 run(s), 35 experiment(s), 35 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001204

• BLUEPRINT release January 2015, ChIP-Seq for mature eosinophil

  ChIP-Seq data for 2 mature eosinophil sample(s). 12 run(s), 12 experiment(s), 12 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001168

• BLUEPRINT release August 2015, Bisulfite-Seq for effector memory CD4-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 1 effector memory CD4-positive, alpha-beta T cell sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001567

• BLUEPRINT release August 2015, ChIP-Seq for Acute lymphocytic leukemia - CTR, on genome GRCh38

  ChIP-Seq data for 1 Acute lymphocytic leukemia - CTR sample(s). 7 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001569

• BLUEPRINT release August 2015, Bisulfite-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD8-positive, alpha-beta T cell sample(s). 56 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001571

• BLUEPRINT release August 2015, ChIP-Seq for erythroblast, on genome GRCh38

  ChIP-Seq data for 2 erythroblast sample(s). 12 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001574

• BLUEPRINT release August 2015, ChIP-Seq for monocyte, on genome GRCh38

  ChIP-Seq data for 2 monocyte sample(s). 6 run(s), 6 experiment(s), 6 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001580

• BLUEPRINT release August 2015, Bisulfite-Seq for effector memory CD8-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 1 effector memory CD8-positive, alpha-beta T cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001583

• BLUEPRINT release August 2015, Bisulfite-Seq for CD38-negative naive B cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD38-negative naive B cell sample(s). 44 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001590

• BLUEPRINT release August 2015, Bisulfite-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh38

  Bisulfite-Seq data for 7 CD14-positive, CD16-negative classical monocyte sample(s). 101 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001591

• BLUEPRINT release August 2015, ChIP-Seq for Multiple myeloma, on genome GRCh38

  ChIP-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001592

• BLUEPRINT release August 2015, ChIP-Seq for plasma cell, on genome GRCh38

  ChIP-Seq data for 2 plasma cell sample(s). 13 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001470

• BLUEPRINT release August 2015, Bisulfite-Seq for cytotoxic CD56-dim natural killer cell, on genome GRCh38

  Bisulfite-Seq data for 2 cytotoxic CD56-dim natural killer cell sample(s). 24 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001473

• BLUEPRINT release August 2015, ChIP-Seq for Acute Myeloid Leukemia, on genome GRCh38

  ChIP-Seq data for 15 Acute Myeloid Leukemia sample(s). 75 run(s), 72 experiment(s), 72 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001481

• BLUEPRINT release August 2015, ChIP-Seq for Acute Myeloid Leukemia - SAHA, on genome GRCh38

  ChIP-Seq data for 3 Acute Myeloid Leukemia - SAHA sample(s). 11 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001485

• BLUEPRINT release August 2015, Bisulfite-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  Bisulfite-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001486

• BLUEPRINT release August 2015, ChIP-Seq for Acute promyelocytic leukemia, on genome GRCh38

  ChIP-Seq data for 6 Acute promyelocytic leukemia sample(s). 29 run(s), 27 experiment(s), 27 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001490

• BLUEPRINT release August 2015, ChIP-Seq for neutrophilic metamyelocyte, on genome GRCh38

  ChIP-Seq data for 4 neutrophilic metamyelocyte sample(s). 18 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001495

• BLUEPRINT release August 2015, Bisulfite-Seq for CD4-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 3 CD4-positive, alpha-beta T cell sample(s). 61 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001516

• BLUEPRINT release August 2015, Bisulfite-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  Bisulfite-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 14 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001509

• BLUEPRINT release August 2015, Bisulfite-Seq for endothelial cell of umbilical vein (proliferating), on genome GRCh38

  Bisulfite-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 36 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001510

• BLUEPRINT release August 2015, ChIP-Seq for neutrophilic myelocyte, on genome GRCh38

  ChIP-Seq data for 4 neutrophilic myelocyte sample(s). 14 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001517

• BLUEPRINT release August 2015, ChIP-Seq for Acute Myeloid Leukemia - CTR, on genome GRCh38

  ChIP-Seq data for 4 Acute Myeloid Leukemia - CTR sample(s). 21 run(s), 21 experiment(s), 21 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001533