11932 results for "cancer rna-seq"

in 96.27 milliseconds.

• 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 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, 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 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC2884 (4h), on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 (4h) 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 EGAD00001002372

• BLUEPRINT release August 2016, ChIP-Seq for Chronic Lymphocytic Leukemia, on genome GRCh38

  ChIP-Seq data for 106 Chronic Lymphocytic Leukemia sample(s). 174 run(s), 163 experiment(s), 162 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 EGAD00001002384

• BLUEPRINT release August 2016, ChIP-Seq for Mantle Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 5 Mantle Cell Lymphoma sample(s). 35 run(s), 35 experiment(s), 35 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 EGAD00001002397

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs sample(s). 8 run(s), 8 experiment(s), 8 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 EGAD00001002408

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC3324, on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC3324 sample(s). 2 run(s), 1 experiment(s), 1 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 EGAD00001002431

• BLUEPRINT release August 2016, ChIP-Seq for neutrophilic metamyelocyte, on genome GRCh38

  ChIP-Seq data for 4 neutrophilic metamyelocyte sample(s). 32 run(s), 23 experiment(s), 23 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 EGAD00001002435

• BLUEPRINT release August 2016, ChIP-Seq for mature eosinophil, on genome GRCh38

  ChIP-Seq data for 2 mature eosinophil sample(s). 14 run(s), 14 experiment(s), 14 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 EGAD00001002477

• BLUEPRINT release August 2016, Bisulfite-Seq for CD38-negative naive B cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD38-negative naive B cell sample(s). 51 run(s), 5 experiment(s), 8 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002520

• mRNA-seq of in vitro differentiation from induced pluripotent stem cells to hepatocyte-like cells

  Fastq files of mRNA-seq data of induced pluripotent stem cells (iPSC), definitive endoderm (DE) and hepatocyte-like cells (HLC). The dataset comprises data from the in vitro differentiation protocol Cellartis (Takara Bio, "CEL", n = 4) and several interventions (11x3 replicates).

  Dataset EGAD00001005935

• Seminal Plasma RNA DAC

  Dac EGAC00001002111

• Single-cell RNA sequencing of blood immune cells before and after interleukin-2 immunotherapy

  Single-cell RNA sequencing of flow cytometry sorted human CD45+ immune cells from 3 systemic lupus erythematosus patients (SLE_002, SLE_004, and SLE_006) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform. Samples from all 3 patients were pooled and loaded on 3 lanes of the chromium controller, resulting in 1 raw sequncing file for each lane.

  Dataset EGAD50000000662

• HipSci RNA sequencing for embryonic stem cell control lines

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNA sequencing on commercially available embryonic stem cell lines as control samples against which to compare HipSci's iPS cell lines.

  Study EGAS00001001727

• Single cell RNA sequencing of bone marrow mononuclear cells

  Bone marrow aspirates were obtained from patients with relapsed/refractory large B cell lymphoma (rrLBCL), mononuclear cells isolated by ficoll density-gradient centrifugation, and loaded onto a 10X Chromium for single cell RNA-sequencing using 5’ chemistry without prior cryopreservation. Healthy donor bone marrow mononuclear cells were obtained from healthy allogeneic stem cell transplant donors and analyzed following viable cryopreservation.

  Study EGAS00001006836

• Gene-Specific RNA Sequencing in PLCG2-Associated Immune Dysregulation with Cold Urticaria

  This study utilized gene-specific RNA-sequencing of PLCG2 to screen for disease causing in-frame exon-skipping transcripts of PLCG2 in a collection of 9 subjects with cold urticaria, 2 subjects with known PLCG2-associated antibody deficiency and immune dysregulation (PLAID)-causing deletions of PLCG2 (positive controls) and 3 healthy subjects (negative controls). Full length cDNA of PLCG2 was generated using gene specific reverse transcription of peripheral blood mononuclear cell RNA. The full length PLCG2 cDNA was used as the template to create Illumina sequencing libraries. To identify the underlying genetic basis for the exon-skipping transcripts, trio-based whole genome sequencing was performed for probands in whom in-frame exon-skipping transcripts of PLCG2 were identified.

  Study phs003807

• 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

• 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

• Dataset for urologic_cancer-RNA

  Rare cancer sequencing data of 75 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008851

• 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

• A developmental cell atlas of the human thyroid gland - RNA

  The thyroid gland produces hormones essential for health from embryogenesis to adulthood. Thyroid disorders, including congenital hypothyroidism and thyroid carcinoma, are prevalent and pose significant health challenges. Congenital hypothyroidism often results from thyroid dysgenesis or impaired hormone synthesis, is particularly prevalent in trisomy 21 (T21), while thyroid carcinoma is the most frequent endocrine malignancy, affecting both paediatric and adult populations. Understanding the molecular basis of these conditions requires deeper insights into fetal thyroid development. We generated a spatiotemporal atlas of the human thyroid during early pregnancy, revealing key cell types, including hormone-producing thyrocytes. Thyroid follicular cells are heterogeneous, with two functional cell states (fTFC1, fTFC2) that persist into adulthood, with fTFC2 characterised by elevated PAX8 expression. We demonstrated that T21 thyroids displayed dysgenesis with disrupted follicular morphology, and altered extracellular matrix interactions, and that the fTFC2 signature was enriched in paediatric papillary thyroid cancer compared to adults. These findings uncover thyrocyte heterogeneity across the lifespan, advancing understanding of thyroid development and disease.

  Dataset EGAD00001015448

• 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

• National Cancer Institute (NCI) Biospecimen Pre-analytical Variables (BPV) Analysis

  The Biospecimen Pre-analytical Variables (BPV) Program is a National Cancer Institute-sponsored study to systematically assess the effects of pre-analytical factors on the molecular profile of biospecimens. A robust biospecimen collection infrastructure was established to prospectively collect biospecimens using rigorous standard operating procedures to control for most variables while introducing experimental conditions to study specific biospecimen handling issues, including the cold ischemic time (delay to formalin fixation), time in formalin, freezing methods, and storage temperatures and durations. RNA and DNA from biospecimens collected under these conditions was analyzed on multiple molecular platforms. The potential effects of these pre-analytical conditions on protein integrity and detection of metabolites were also examined. Data from this study will be used to develop evidence-based biospecimen standard operating procedures and best practices for fit-for-purpose collection, processing, and storage of biospecimens. The BPV Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following sub-studies below or in the "Substudies" box located on the right hand side of this top-level study page phs001304 BPV Cohort. The substudy links will be active once they are released by dbGaP. Preanalytical Impacts on Global Metabolite Profiling - plasma (MassSpec by Metabolon) This study was to evaluate the impact of the storage temperature (s) (-80°C and LN2 vapor) and the length of storage on human plasma quality using LC-MS/MS (liquid-chromatography-mass spectrometry/mass spectrometry) based global metabolite profiling. The study includes 240 plasma samples collected from 40 donors. Investigate the effect of the delay to fixation on the proteome and phosphoproteome -FFPE (MassSpec by Caprion). The study is to do proteome and phosphoproteome analysis on Delay to fixation was carried out using FFPE tumor samples from colon and ovarian cancer patients comparing 2, 3, and 12hr delay to fixation to the 1hr time point. The study includes 100 samples 20 donors. Investigate the effect of storage conditions of tumor specimens on the proteome and phosphoproteome profiling- Frozen tissue and plasma (MassSpec by Caprion). The study was to evaluate the effects of storage conditions on tumor specimens. Plasma samples from 40 cancer patients stored at two different temperatures (-80°C and LN2) for a given period (0-2, 6-8, and 12-14 months) were evaluated. Frozen kidney tumor samples from 20 patients were compared for effects of different snap frozen (dry ice vs. LN2) and storage temperatures (-80°C and LN2). The study includes 100 tissue and 240 plasma samples from 60 donors. Preanalytical Impacts on Genomic Sequencing by Next Generation Sequencing (NGS) technology (mRNA/miRNA and WES by Expression Analysis). The goal of the study is to determine the effects of cold ischemic delay-to-fixation (4 time points) and formalin preservation (FFPE) on the nature and quality of genomic profiles using the matched freshly frozen sample as the gold standard, which including WES, RNAseq. The study includes 395 samples from 37 donors. Preanalytical Impacts on Copy Number Variation (CNV) Detection by aCGH technology (aCGH by Georgetown University). This study was to use aCGH to evaluate the effect of variation in cold ischemia time and time in formalin fixation on CNV in DNA extracted from kidney cancer specimens. The study includes 235 samples from 40 donors. Evaluation of frozen conditions on mRNA profiling by TaqMan assay (mRNA expression by Georgetown University). This study was to utilize gene expression profiling, using custom TaqMan arrays, to compare the molecular profiles of RNA from frozen tumor samples collected using two freezing methods (dry ice or LN2), two storage temperatures (-80°C or LN2 vapor), as well as Optimal Cutting Temperature (OCT) compound and non-OCT embedded. The study includes 100 samples from 20 donors. mRNA signature for stratification by cold ischemia time (mRNA expression by IBBL). The study was to determine the effects of cold ischemic time (delay-to-fixation) and formalin preservation (FFPE) on mRNA detection by Taqman assay using tumor tissue specimens from kidney, colon and ovarian cancer patients. There are160 samples from 40 donors. The Biospecimen PV cohort is utilized in the following dbGaP individual studies. To view molecular data, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001304 Biospecimen PV cohort. phs001634 CIT mRNA phs001635 CNV aCGH phs001636 Fixation Delay phs001637 Global Metabolite Profiling phs001638 mRNA TaqMan phs001639 NGS phs001640 Tumor Storage

  Study phs001304

• Single-cell Kinnex sequencing of Alzheimer's disease isoform profile

  Alzheimer’s disease (AD) is the most common cause of dementia, yet its molecular causes remain incompletely understood. RNA diversity in part arising from dysregulated splicing may contribute to AD pathogenesis; however, the ability to interrogate the resulting full-length isoforms in single brain cells has been technologically limited. Here we report the use of PacBio Kinnex long-read sequencing combined with 10X Genomics single-cell preparations to identify both annotated and unannotated RNA isoforms. Eight AD and seven non-diseased post-mortem human brains yielded ~70,000 single nuclei showing diverse, differentially expressed, and switched transcripts in multiple genes. Cell-type-specific isoform expression and variants with intra-exonic junctions associated with reverse transcriptase-mediated somatic gene recombination were also detected. Novel isoforms, including CHI3L1 and SEPTIN4, were altered in AD. Kinnex sequencing of RNA isoforms from single nuclei detected vast isoform diversity amongst brain cell types, representing an under-explored element in AD and other brain disorders.

  Study EGAS50000001476

• Identification of gene mutations and fusion genes in patients with Sézary Syndrome

  Sezary syndrome (SS) is a leukemic form of cutaneous T-cell lymphoma (CTCL) with an aggressive clinical course. The goal of our study is to understand the genetic basis of the disease by looking for driver gene mutations and fusion genes in 15 erythrodermic patients with circulating Sezary cels, fourteen of them fulfilling the diagnostic criteria of SS. Peripheral blood samples were collected for each patient and CD4+ T-lymphocytes and Granulocytes were isolated. DNA and RNA was extracted for matched normal and tumor materials. Whole exome sequencing was performed on matched normal and tumor tissues of 12 patients and RNA sequencing was performed on 10 patients. For 7 of these patients, we have both exome as well as RNA sequencing data. In this study, we present a complex genomic landscape of Sezary syndrome with several point mutations, copy number variations and fusion events which could contribute to the pathogenesis of SS.

  Study EGAS00001001706

• RNA sequencing of undifferentiated sarcomas

  Dac EGAC00001001055

• Human Biofluid RNA Atlas DAC

  Dac EGAC00001001338

• scRNA-seq of patient-derived PDAC organoids

  Dataset EGAD00001006448

• ChIP_3PEAKS

  Third batch of ChIP-seq narrowPeaks. Software: MACS2 v2.1.2

  Dataset EGAD00010002155

• Adipocytes Regulate Fibroblast Function and Their Loss Contributes to Fibroblast Dysfunction in Inflammatory Diseases

  We profiled live synovial cells from 16 individuals with no diagnosed arthritis using single-cell RNA sequencing. Our study was designed to provide a reference single cell RNA sequencing dataset for researchers interested in studying arthritic synovium, providing sequencing data on healthy synovial cells for comparison to cells from diseased synovial tissues. Synovial tissue was collected post-mortem from three different sources between 2019-2021: the National Disease Research Interchange, a collaboration with Rush University and the Gift of Hope, and the Brigham and Women's Hospital Autopsy Department. To be included in the study, patients had to be between the ages of 18 to 72 and have no diagnosed arthritis or autoimmune diseases. Additionally, this study includes bulk RNA sequencing data of cultured primary synovial fibroblasts isolated from three rheumatoid arthritis patents. Cells were stimulated with either cortisol, fat conditioned media, TGFβ, TNFα, fat conditioned media with mifepristone, TGFβ with fat conditioned media, or TNFα with fat conditioned media. Cells were harvested 4 or 22 hours later and lysates collected for sequencing. Data from this study submitted to the Gene Expression Omnibus (GEO) may be accessed via accession number GSE233504.

  Study phs003304

• 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 of AD OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from individuals diagnosed with Alzheimer's disease exposed to traffic-related ultrafine particles (UFPs) for 24-h and 72-h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Dataset EGAD50000000648

• miRNASeq profiles from Indian HFrEF Cohort

  The dataset contains miRNA profiling from a cohort of 49 HFrEF patients. The myocardium samples were collected from these patients during heart transplant of LVAD implantation procedure. The RNA samples were collected in RNAlater. Small RNA libraries were prepared using QIAseq miRNA Library Kit, Qiagen and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001194

• Single-cell RNA-sequencing on malignant and benign tissue samples

  Single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis was performed in order to deduce tissue adaptive expression patterns of the disease. Matching tissue from five donors with untreated CRC and liver metastasis were sampled.

  Dataset EGAD50000001203

• Data from Shea et al Can Research 2025

  This dataset contains single cell RNA sequencing (192 fastq files for 59 samples), whole exome sequencing (20 BAM files -hg38- for 20 samples) and bulk RNA sequencing (138 paired-end fastq files and 17 single-end fastq files for 8 samples)

  Dataset EGAD50000001334

• Dicer and/or ADAR1 depleted HEK293-LGP2 cells

  This dataset includes bulk RNA-sequencing data from HEK293-L cells subjected to siRNA-mediated knockdown of Dicer and/or ADAR1. In total, 12 samples are included, representing four experimental groups with triplicate biological replicates. RNA was extracted using TRIzol according to standard protocols and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD50000002044

• Total NF1 sequence in the patients with neurofaibromatosis type1

  We analyzed whole NF1 gene region at DNA (including whole exon and intron sequences) and RNA (full length cDNA of leukocyte) level for 20 patients with neurofibromatosis type 1.

  Study JGAS000288

• 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

• 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

• Presence of bacterial infection in brains of patients with Parkinson's disease (PD)

  Isolation of bacteria in infected brains in patients with Parkinson's disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis).

  Study EGAS00001003643

• Presence of bacterial infection in brains of patients with Huntington's disease (HD)

  Bacterial isolation in infected brains in patients with Huntington's disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis)

  Study EGAS00001003678

• 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

• 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

• 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

• Sequencing component for the whole genome methylation analysis in PBMCs and cell subsets (pilot study)

  DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip

  Dataset EGAD00001000394

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• ATAC

  ATAC-seq non-overlapping fixed width peaks with score normalization. Software: MACS2 v2.1.2

  Dataset EGAD00010001928

• prDLBCL WXS/RNA Data Commitee

  Dac EGAC50000000284

• A Randomized Trial of Combined PD-L1 and CTLA-4 Inhibition with Targeted Low-Dose or Hypofractionated Radiation for Patients with Metastatic Colorectal Cancer

  Brief SummaryThis randomized phase II trial studies the side effects of durvalumab and tremelimumab to see how well they work with or without high or low-dose radiation therapy in treating patients with colorectal (CRC) or non-small cell lung cancer (NSCLC) that has spread to other parts of the body (metastatic). Immunotherapy with durvalumab and tremelimumab may induce changes in body's immune system and may interfere with the ability of tumor cells to grow and spread. Radiation therapy uses high energy x-rays to kill tumor cells and shrink tumors. Giving durvalumab and tremelimumab with radiation therapy may work better in treating patients with colorectal or non-small cell lung cancer.Detailed DescriptionPRIMARY OBJECTIVES:I. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 (durvalumab) and tremelimumab alone or with high or low-dose radiation in non-small cell lung cancer (NSCLC). (NSCLC Cohort) II. To compare the overall response (excluding the irradiated lesion[s]) between combined checkpoint blockade with MEDI4736 and tremelimumab alone or combined checkpoint blockade with low or high dose radiation. (NSCLC Cohort) III. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 and tremelimumab with high or low-dose radiation. (Colorectal Cohort) IV. To determine the overall response rate (excluding the irradiated lesion[s]) with combined checkpoint blockade with MEDI4736 and tremelimumab with either low or high dose radiation. (Colorectal Cohort)SECONDARY OBJECTIVES:I. To estimate median progression-free survival and overall survival. (NSCLC Cohort) II. To determine local control within the irradiated field(s) and abscopal response rates. (NSCLC Cohort) III. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells and overall response. (NSCLC Cohort) IV. To explore changes in PD-L1 expression, circulating T-cell populations, T-cell infiltration, ribonucleic acid (RNA) expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (NSCLC Cohort) V. To estimate median progression-free survival and overall survival. (Colorectal Cohort) VI. To determine local control within the irradiated field and abscopal response rates. (Colorectal Cohort) VII. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+ CD8+ T-cells and overall response. (Colorectal Cohort) VIII. To evaluate changes between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells induced by targeted low or high dose radiation. (Colorectal Cohort) IX. To explore changes in circulating T-cell populations, T-cell infiltration, RNA expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (Colorectal Cohort)OUTLINE: Patients are assigned to 1 of 2 cohorts. NOTE: This Study is only for Cohort 2. Please see phs003295 for Cohort 1COHORT 1: Patients with NSCLC are randomized to 1 of 3 arms.ARM A: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.ARM C: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses.COHORT 2: Patients with CRC are randomized to 1 of 2 arms.ARM A: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.After completion of study treatment, patients are followed for up to 12 weeks.Official TitleA Phase 2 Study of MEDI4736 (Durvalumab) and Tremelimumab Alone or in Combination With High or Low-Dose Radiation in Metastatic Colorectal and NSCLC Conditions Metastatic Colorectal CarcinomaMetastatic Lung Non-Small Cell CarcinomaStage IV Colorectal Cancer AJCC v7Stage IV Lung Non-Small Cell Cancer AJCC v7Stage IVA Colorectal Cancer AJCC v7Stage IVB Colorectal Cancer AJCC v7 Intervention/Treatment Biological: DurvalumabRadiation: Radiation TherapyBiological: Tremelimumab Other Study ID Numbers NCI-2016-01325NCI-2016-01325 ( Registry Identifier ) (REGISTRY: CTRP (Clinical Trial Reporting Program))17-71910021 ( Other Identifier ) (OTHER: Dana-Farber - Harvard Cancer Center LAO)10021 ( Other Identifier ) (OTHER: CTEP) Molecular Technologies/AssaysIHCmIFOlinkCyTOFRNAseqWES

  Study phs003294

• Durvalumab Plus Tremelimumab Alone or in Combination with Low-Dose or Hypofractionated Radiotherapy in Metastatic Non-Small-Cell Lung Cancer Refractory to Previous PD(L)-1 Therapy: an Open-Label, Multicentre, Randomised, Phase 2 Trial

  Brief SummaryThis randomized phase II trial studies the side effects of durvalumab and tremelimumab and to see how well they work with or without high or low-dose radiation therapy in treating patients with colorectal or non-small cell lung cancer that has spread to other parts of the body (metastatic). Immunotherapy with durvalumab and tremelimumab, may induce changes in body's immune system and may interfere with the ability of tumor cells to grow and spread. Radiation therapy uses high energy x-rays to kill tumor cells and shrink tumors. Giving durvalumab and tremelimumab with radiation therapy may work better in treating patients with colorectal or non-small cell lung cancer.Detailed DescriptionPRIMARY OBJECTIVES:I. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 (durvalumab) and tremelimumab alone or with high or low-dose radiation in non-small cell lung cancer (NSCLC). (NSCLC Cohort) II. To compare the overall response (excluding the irradiated lesion[s]) between combined checkpoint blockade with MEDI4736 and tremelimumab alone or combined checkpoint blockade with low or high dose radiation. (NSCLC Cohort) III. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 and tremelimumab with high or low-dose radiation. (Colorectal Cohort) IV. To determine the overall response rate (excluding the irradiated lesion[s]) with combined checkpoint blockade with MEDI4736 and tremelimumab with either low or high dose radiation. (Colorectal Cohort)SECONDARY OBJECTIVES:I. To estimate median progression-free survival and overall survival. (NSCLC Cohort) II. To determine local control within the irradiated field(s) and abscopal response rates. (NSCLC Cohort) III. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells and overall response. (NSCLC Cohort) IV. To explore changes in PD-L1 expression, circulating T-cell populations, T-cell infiltration, ribonucleic acid (RNA) expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (NSCLC Cohort) V. To estimate median progression-free survival and overall survival. (Colorectal Cohort) VI. To determine local control within the irradiated field and abscopal response rates. (Colorectal Cohort) VII. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+ CD8+ T-cells and overall response. (Colorectal Cohort) VIII. To evaluate changes between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells induced by targeted low or high dose radiation. (Colorectal Cohort) IX. To explore changes in circulating T-cell populations, T-cell infiltration, RNA expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (Colorectal Cohort)OUTLINE: Patients are assigned to 1 of 2 cohorts. NOTE: This Study is only for Cohort 1. Please see phs003294 for Cohort 2COHORT 1: Patients with NSCLC are randomized to 1 of 3 arms.ARM A: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.ARM C: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses.COHORT 2: Patients with CRC are randomized to 1 of 2 arms.ARM A: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.After completion of study treatment, patients are followed for up to 12 weeks.Official TitleA Phase 2 Study of MEDI4736 (Durvalumab) and Tremelimumab Alone or in Combination With High or Low-Dose Radiation in Metastatic Colorectal and NSCLC Conditions Metastatic Colorectal CarcinomaMetastatic Lung Non-Small Cell CarcinomaStage IV Colorectal Cancer AJCC v7Stage IV Lung Non-Small Cell Cancer AJCC v7Stage IVA Colorectal Cancer AJCC v7Stage IVB Colorectal Cancer AJCC v7 Intervention/Treatment Biological: DurvalumabRadiation: Radiation TherapyBiological: Tremelimumab Other Study ID Numbers NCI-2016-01325NCI-2016-01325 ( Registry Identifier ) (REGISTRY: CTRP (Clinical Trial Reporting Program))17-71910021 ( Other Identifier ) (OTHER: Dana-Farber - Harvard Cancer Center LAO)10021 ( Other Identifier ) (OTHER: CTEP) Molecular Technologies / AssaysCyTOFIHCmIFOlinkRNAseqWES

  Study phs003295

• 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

• 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

• 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

• Parallel Genomic Alterations of Antigen and Payload Targets Mediate Polyclonal Acquired Clinical Resistance to the Antibody Drug Conjugate Sacituzumab Govitecan

  Sacituzumab Govitecan (SG), a novel antibody drug conjugate (ADC) incorporating the anti-TROP2 antibody hRS7 conjugated to a topoisomerase-1 inhibitor (SN-38) payload, is the first ADC to be approved for advanced triple negative breast cancer (TNBC). However, mechanisms governing therapeutic resistance to SG are not known. We sought to identify mechanisms of de novo and acquired resistance to SG through unbiased whole-exome sequencing (WES) and RNA sequencing analysis of pre-treatment and multi-site post-progression (autopsy) tumor specimens. We examined three metastatic TNBC cases exhibiting (1) de novo progression, (2) stable disease, and (3) a deep response followed by progression, then mapped the temporal and spatial genomic evolution of acquired resistance in the responding patient. We then conducted additional pre-clinical experiments to validate the observed resistance mechanisms. TROP2 RNA and gene copy number were associated with de novo resistance, as case (1) was found to have absent TROP2 expression in all specimens, case (2) expressed TROP2, while case (3) exhibited both expression and focal genomic amplification of the TACSTD2/TROP2 locus. The genomic phylogeny tree inferred from case (3) post-progression specimens revealed one branch harboring an acquired canonical E418K resistance mutation in TOP1 (encoding topoisomerase 1) and a subsequent sub-clonal TOP1 inactivating frameshift mutation, while a distinct branch exhibited acquisition of a novel T256R missense mutation in TACSTD2 (encoding TROP2). Both the TOP1- and TACSTD2-mutant clones seeded multiple distinct metastatic sites. Through reconstitution experiments in TROP2 negative cells we found that TROP2 T256R is a stable protein with defective cell membrane localization and reduced cell surface binding by RS7 compared to wild-type TROP2. Collectively, these findings underscore TROP2 as a determinant of initial response to SG, and they reveal parallel and mutually exclusive polyclonal molecular mechanisms of acquired resistance involving the direct antibody target and drug payload target in distinct metastatic subclones of a single patient. While further research is needed to extend these novel findings, this study highlights the specificity of SG and illustrates how identifying such mechanisms will inform rational therapeutic strategies to overcome ADC resistance.  

  Study phs002555

• Custom long non-coding RNA capture DAC

  Dac EGAC00001002198

• GLASS-NL RNA-sequencing Study

  Study EGAS00001007551

• 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

• Multi-omics analysis of CUD in the VS

  The aim was to molecularly characterize the human ventral striatum in CUD. For this, we generated epigenomic, transcriptomic, and proteomic datasets at the bulk-level, performed integrative multi-omics analyses and further analyzed CUD-associated transcriptomic changes at a cell type-specific level using snRNA-seq.

  Study EGAS50000000623

• snRNA-seq on patient tumours

  snRNA-seq performed on patient tumours (n = 6 patients, one biopsy sample each sequenced) using the 10x technology. Single nuclei were acquired from six frozen mCRPC biopsies (4 lymph node, 2 liver metastases) obtained from consenting patients treated at the Royal Marsden Hospital between 2018 and 2023 under an institutional review board approved research protocol (Research Ethics Committee approval number: 04/Q0801/60). All six patients had previously received androgen-receptor signalling inhibitor(s) and five of six patients had previously received taxane(s).

  Dataset EGAD50000000874

• (ATAC-seq) Shifted assembly and function of mSWI/SNF family subcomplexes underlie targetable dependencies in endometriod carcinomas

  Raw and processed ATAC-seq data from the VOA1066 undifferentiated endometrial carcinoma cell-line (10 samples). Samples were treated with DMSO, dBRD9, or compound 12, without doxycycline; some samples instead received doxycycline-induced ARID1A treatment, or doxycycline alone. Samples were sequenced on Illumina NextSeq 500 using 37 bp paired-end sequencing parameters. Raw fastq fastq files, bigwig files giving normalized genomic coverage per region, and called broad peaks are included for each sample.

  Dataset EGAD50000001472

• Chromatin accessibility analysis of epidermal keratinocytes from psoriatic, clinically healed, and healthy control skin

  This study uses ATAC-seq to analyze epidermal keratinocytes from psoriatic lesions, clinically healed skin of the same patients, and healthy control skin. The aim is to elucidate chromatin accessibility changes associated with psoriasis pathogenesis and remission from 6 lesional, 6 healed, and 5 control samples.

  Study JGAS000844

• snRNA-seq data of 11 regionally sampled GBM tissue for 4 patients

  This dataset contains snRNA-seq data of 11 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed in an unbiased manner without any sorting procedure. Nuclei were dissociated from frozen tissue using Chromium Nuclei Isolation Kit. Nuclei barcoding, cDNA preparation, and library construction were performed following the Evercode WT or WT mini User Manual, by combinatorial barcoding to assign a unique barcode to each cell.

  Dataset EGAD50000000778

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_T=24hrs sample(s). 7 run(s), 7 experiment(s), 7 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 EGAD00001002474

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs sample(s). 8 run(s), 8 experiment(s), 8 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 EGAD00001002388

• BLUEPRINT release August 2016, ChIP-Seq for conventional dendritic cell, on genome GRCh38

  ChIP-Seq data for 1 conventional dendritic cell sample(s). 4 run(s), 4 experiment(s), 4 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 EGAD00001002310

• BLUEPRINT release August 2016, ChIP-Seq for unswitched memory B cell, on genome GRCh38

  ChIP-Seq data for 1 unswitched memory B cell sample(s). 7 run(s), 7 experiment(s), 7 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 EGAD00001002282

• BLUEPRINT release August 2016, ChIP-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 2 run(s), 2 experiment(s), 2 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 EGAD00001002494

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - T=0days, on genome GRCh38

  ChIP-Seq data for 2 monocyte - T=0days sample(s). 7 run(s), 7 experiment(s), 7 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 EGAD00001002491

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=1hr, on genome GRCh38

  ChIP-Seq data for 2 monocyte - RPMI_BG_T=1hr 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 EGAD00001002297

• BLUEPRINT release August 2016, ChIP-Seq for inflammatory macrophage, on genome GRCh38

  ChIP-Seq data for 9 inflammatory macrophage sample(s). 58 run(s), 58 experiment(s), 58 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 EGAD00001002515

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=24hrs_RPMI_T=5days, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs_RPMI_T=5days sample(s). 7 run(s), 7 experiment(s), 7 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 EGAD00001002517

• DNA-seq BAM files from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by HPAH

  Paired-end DNA-seq BAM files from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by hereditary pulmonary arterial hypertension (HPAH). Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). FASTQ files were processed at the CNAG (Barcelona) using the GEM short-read aligner on the human genome version hs37d5, producing a total of 16 BAM files.

  Dataset EGAD00001005757

• BLUEPRINT release August 2016, ChIP-Seq for germinal center B cell, on genome GRCh38

  ChIP-Seq data for 4 germinal center B cell sample(s). 24 run(s), 22 experiment(s), 22 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 EGAD00001002442

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_T=1hr, on genome GRCh38

  ChIP-Seq data for 2 monocyte - RPMI_T=1hr sample(s). 4 run(s), 4 experiment(s), 4 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 EGAD00001002453

• BLUEPRINT release August 2016, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 run(s), 23 experiment(s), 23 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 EGAD00001002454

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MS-275 (20h), on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MS-275 (20h) sample(s). 5 run(s), 5 experiment(s), 5 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 EGAD00001002493

• BLUEPRINT release August 2016, Bisulfite-Seq for CD3-positive, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  Bisulfite-Seq data for 2 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 29 run(s), 2 experiment(s), 4 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002325

• BLUEPRINT release August 2016, ChIP-Seq for segmented neutrophil of bone marrow, on genome GRCh38

  ChIP-Seq data for 4 segmented neutrophil of bone marrow sample(s). 24 run(s), 23 experiment(s), 23 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 EGAD00001002390

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - Attached_T=1hr, on genome GRCh38

  ChIP-Seq data for 3 monocyte - Attached_T=1hr sample(s). 8 run(s), 7 experiment(s), 7 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 EGAD00001002415

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=4hrs sample(s). 8 run(s), 8 experiment(s), 8 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 EGAD00001002368

• BLUEPRINT release August 2016, ChIP-Seq for immature conventional dendritic cell - GM-CSF_IL4_T=6_days, on genome GRCh38

  ChIP-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days sample(s). 20 run(s), 20 experiment(s), 20 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 EGAD00001002485

• BLUEPRINT release August 2016, ChIP-Seq for memory B cell, on genome GRCh38

  ChIP-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 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 EGAD00001002510

• BLUEPRINT release August 2014, ChIP-Seq for CD14-positive, CD16-negative classical monocyte

  ChIP-Seq data for 9 CD14-positive, CD16-negative classical monocyte sample(s). 59 run(s), 55 experiment(s), 55 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 EGAD00001000913

• Comparison of protocols for deriving pancreatic progenitors from hPSCs (ATAC-seq)

  This dataset contains 27 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared ATAC-seq libraries for the 27 samples, and sequenced them on Illumina HiSeq4000.

  Dataset EGAD00001004824

• BLUEPRINT release August 2016, Bisulfite-Seq for effector memory CD8-positive, alpha-beta T cell, terminally differentiated, on genome GRCh38

  Bisulfite-Seq data for 2 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 34 run(s), 3 experiment(s), 4 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002346

• BLUEPRINT release August 2016, ChIP-Seq for regulatory T cell, on genome GRCh38

  ChIP-Seq data for 2 regulatory T cell sample(s). 2 run(s), 2 experiment(s), 2 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 EGAD00001002293

• BLUEPRINT release August 2016, ChIP-Seq for Activated B-Cell-Like Diffuse Large B-Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Activated B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 12 run(s), 12 experiment(s), 12 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 EGAD00001002307

• BLUEPRINT release August 2016, ChIP-Seq for mature neutrophil, on genome GRCh38

  ChIP-Seq data for 10 mature neutrophil sample(s). 105 run(s), 86 experiment(s), 86 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 EGAD00001002449

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs sample(s). 7 run(s), 7 experiment(s), 7 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 EGAD00001002512

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days sample(s). 7 run(s), 7 experiment(s), 7 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 EGAD00001002448

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

  ChIP-Seq data for 6 CD38-negative naive B cell sample(s). 20 run(s), 20 experiment(s), 20 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 EGAD00001001594