12000 results for "cancer rna-seq"

in 31.48 milliseconds.

• Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A063 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A063 with 80 high quality cells sequenced (75 blast and 5 normal)

  Dataset EGAD00001011328

• Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A067 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A067 with 78 high quality cells sequenced (73 blast and 5 normal)

  Dataset EGAD00001011330

• ATAC-seq of spermatogonia

  Raw sequencing reads of ATAC-seq of spermatogonia in FASTQ format, comprising 6 samples sequenced on the Illumina HiSeq 4000 platform.

  Dataset EGAD00001007759

• RCC ATAC-seq data

  ATAC-seq data 72cases

  Dataset EGAD00001009868

• Dataset to study clonal evolution in iAMP21 patient SJBALL030072using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJBALL030072with 66 high quality cells sequenced (61 blast and 5 normal)

  Dataset EGAD00001010288

• non-IVF MeDIP-seq bam files

  Bam files consisting of aligned MeDIP-seq reads from cord blood cells and cord blood mononuclear cells of twins not conceived through in vitro fertilisation

  Dataset EGAD00001003159

• Neuroblastoma Cell Line Circle-seq Data

  This dataset comprises Circle-seq data for 12 neuroblastoma cell lines supporting Koche et al. Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma (2020).

  Dataset EGAD00001006579

• Aberrant RNA-splicing (neojunctions) offers a new source for targets, and our neoantigen discovery platform (SNIPP) characterizes a novel class of clonally-expressed splicing-derived neoantigens that elicit a CD8+ T-cell-mediated tumor killing response.

  RESULTS: Our pipeline identified 789 public neojunctions, with 32 neojunctions concurrently identified in transcriptomic and proteomic glioma data and predicted to be presented by HLA-A*02:01 with high confidence. IVS and subsequent 10x VDJ scRNA-seq identified TCR clonotypes reactive against neojunctions in RPL22 (n=7) and GNAS (n=1), the latter being highly intratumorally-conserved (detected in > 90% of spatially-mapped biopsies across 17/56 patients (26.78%)). TCR-transduced T-cells demonstrated recognition and immunogenic activation against endogenously processed and presented neoantigens in multiple GBM PDX cell lines. Furthermore, IDH1-mutant oligodendroglioma samples demonstrated significantly elevated expression of neojunctions over IDH1-mutant astrocytoma and IDH1wt subtypes. Differential gene expression (DESeq2) identified decreased expression of splicing factors due to oligodendroglioma-specific co-deletion of Chromosomes 1p/19q. siRNA knockdown of these splicing factors (e.g. SF3A3, SNRPD2) in IDH1wt glioma cells resulted in significantly increased expression of corresponding neojunctions.

  Study EGAS00001007986

• 1M-scBloodNL

  Here we present the 1M-scBloodNL study, in which we performed single-cell RNA-seq on 120 individuals of the Northern Netherlands population cohort Lifelines. For each individual peripheral blood mononuclear cells (PBMCs) were sequenced in an unstimulated condition, and after 3 and 24 hour in vitro stimulation with C. albicans (CA), M. tuberculosis (MTB) and P. aeruginosa (PA), totalling approximately 1.3 million cells. scRNA-seq was conducted with the 10X Genomics 3'-end v2 (72 libraries) and v3 (33 libraries) technology. In general, each library contains PBMCs from 8 donors and 2 different stimulation-timepoint combinations. Donors were demultiplexed using a combination of SoupOrCell (https://www.nature.com/articles/s41592-020-0820-1) and genotype information to assign the correct donor to a donor-specific cell cluster.

  Dataset EGAD00001007764

• Bulk RNA Sequencing of 86 Human Donor Lungs

  The goal of this study was to characterize the effect of age on gene expression in normal human lung. We collected distal lung samples from 86 human donors distributed in age between 16 and 76 years and extracted RNA for Illumina-based sequencing.

  Study phs002484

• metastatic uveal melanoma tumour biopsies

  Tumour biopsies were obtained from uveal melanoma patients pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system.

  Study EGAS50000000864

• metastatic uveal melanoma tumour biopsies (n=35)

  Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system.

  Study EGAS50000000836

• RNA004 Nanopore DRS of peripheral blood

  Direct RNA Sequencing offers the capability of standard transcriptomic analyses + RNA modification analysis, which holds promising applications for future clinical workflows. To this end, we tested the newly available RNA004 kit on human peripheral blood and provide orthogonal GLORI measurement for benchmarking of m6A-detection.

  Study EGAS50000001201

• Spatial RNA-sequencing of metastatic melanoma

  We performed RNA sequencing of 48 different regions sub-sampled from a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. RNAseq was performed on samples with a minimum RNA integrity number (RIN) of 5.5 except for two cases (6A10 and 8A3) with RINs greater than 3. A minimum of 700ng of RNA were required for all samples undergoing RNAseq. Paired-end transcriptome reads were aligned using TopHat2, to the UCSC hg19 reference genome.

  Dataset EGAD00001005820

• Microbiomic and immunogenic biomarkers of adjuvant chemotherapy efficacy in stage III colorectal cancer

  The standard treatment for stage III colorectal cancer (CRC) is surgery, followed by adjuvant chemotherapy (AC). However, the efficacy of AC is limited, and approximately 30% of patients experience recurrence. Therefore, easily assessable molecular biomarkers that can predict response to AC are needed. Here, we aimed to identify predictive biomarkers of response to AC using tumor transcriptomic data. Tumor specimens from 253 patients who underwent surgery for stage III CRC between 1997 and 2019 were analyzed using RNA sequencing. Transcriptional subtyping and analyses of gut microbiome, immune cell fractions, and T-cell receptor (TCR) were performed to identify factors associated with recurrence-free survival (RFS) in patients treated with or without AC. Of 253 patients, 118 (46.6%) received AC. Twenty phyla and 799 species of the microbiomes were identified, among which Fusobacteria were identified in 247 patients (97.6%). Multivariable Cox proportional hazards regression analysis of patients who received AC showed that intratumoral Fusobacterium and M1 macrophage abundance and diversity of TCR alpha and delta (TRAD) were independently associated with RFS. Fusobacterium and M1 macrophage abundance, and TRAD diversity were associated with the response to AC, suggesting that these factors could serve as biomarkers for personalized treatment in stage III CRC.

  Study JGAS000875

• MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

  Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long non-coding RNAs (lncRNAs), on the way MYC is able to influence cellular transcriptome. To this aim we have intersected RNA-sequencing data from two MYC-inducible cell lines and from a cohort of 91 mature B-cell lymphomas carrying, or not carrying, genetic variants resulting in MYC over-expression. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, for MYC-Induced long Non-Coding RNA, showing a strong correlation with MYC expression in MYC-positive lymphomas and also in pancreatic ductal adenocarcinomas. To understand its cellular role we performed RNA interference (RNAi) experiments and found that MINCR knock-down is associated with a reduction in cellular viability, due to an impairment in cell cycle progression. Differential gene expression analysis following RNAi showed a strongly significant enrichment of cell cycle genes among the genes down-regulate following MINCR knock-down. Interestingly these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of MYC transcriptional program. Accordingly, following MINCR knock-down, we observed a reduction in the binding of MYC to the promoters of selected cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes.

  Dataset EGAD00001001441

• Bulk RNA sequencing of hematological toxicity following CAR-T cells injection

  Bone marrow aspirations obtained from patients treated with CAR-T cells were analyzed using bulk RNA sequencing (CD3+, CAR T+, CD34+ sorted populations).

  Study EGAS50000000777

• Extracellular Vesicle miRNA Sequencing with Qiaseq and NextSeq 550

  This dataset includes small RNA sequencing data from extracellular vesicle-derived RNA. miRNA libraries were prepared using the Qiaseq miRNA Library Kit with adaptations for low RNA input and sequenced on the Illumina NextSeq 550 platform

  Dataset EGAD50000001504

• RNA sequencing of skin tissue and peripheral blood mononuclear cells from patients with atopic dermatitis and healthy controls.

  We performed RNA-sequencing of skin tissue obtained from patients with atopic dermatitis, psoriasis and controls in Japanese population.

  Study JGAS000780

• Pediatric B-cell precursor acute lymphoblastic leukemia RNA sequencing

  This dataset included 33 childhood B-cell precursor acute lymphoblastic leukemia RNA sequencing samples. All samples were subjected to Illumina pair-end sequencing.

  Study EGAS50000000763

• Single-cell RNA-sequencing for peripheral blood mononuclear cells from COVID-19 patients and healthy controls of Japanese

  We performed single-cell RNA-sequencing of peripheral blood mononuclear cells obtained from COVID-19 patients and healthy controls.

  Study JGAS000593

• Single-cell RNA-sequencing for peripheral blood mononuclear cells from COVID-19 patients and healthy controls of Japanese

  We performed single-cell RNA-sequencing of peripheral blood mononuclear cells obtained from COVID-19 patients and healthy controls.

  Study JGAS000543

• Single cell RNA-sequencing of GSCs and GBM tumours

  Characterization of glioblastoma tumors and glioblastoma stem cell (GSCs) lines with single cell or single nuclei RNA-sequencing.

  Study EGAS00001004656

• RNA sequencing of AD, MCI and control OM cells

  Total RNA sequencing of cultured OM cells derived from patients with Alzheimer's disease (AD), individuals with mild cognitive impairment (MCI) and cognitively healthy controls.

  Study EGAS00001006195

• Bulk RNA from sorted CD8+ T cells after 48h co-culture with human Mito-DsRed MSCs.

  For human samples, total cellular RNA was isolated from post-sorted Mito+ and Mito CD8+ cells using the RNeasy Mini Kit (Qiagen). Stranded RNA libraries were created using SMARTSeq Stranded.

  Dataset EGAD00001011082

• RNA seq on 19 samples of Radiation-Induced Meningiomas

  Purpose: Majority of pediatric cancers require the irradiation of the central nervous system (CNS), and as more patients survive into adulthood from improved oncological therapy the sequelae of brain radiation are increasing in prevalence. Radiation-induced meningiomas (RIMs), one such secondary effect, demonstrate a clinically more aggressive behaviour than sporadic meningiomas (SMs). We aimed to describe the genomic mutational landscape of RIMs.Methods: We analyzed a principal cohort of 18 RIMs, with 31 RIMs overall, from patients who received childhood radiation therapy and 30 SMs, as a comparator population. We performed a multiplatform integrative genomic analysis; including methylation, whole exome and RNA sequencing. Results: RIMs exhibited a five-fold increase in copy number alterations, commonly the loss of chromosome 1p (17/18 RIMs) and 22q (17/18 RIMs), which was significantly more than observed in sporadic meningiomas. Furthermore, RNA sequencing data revealed an NF2 gene fusion event in 35.3% of RIMs. In all 6 cases, there was a complete NF2 exon spliced into a complete exon of a reciprocal gene, suggesting that the breakpoints of genomic rearrangement are intronic. All tumours with the NF2 fusion also possessed monosomy of chromosome 22q, rendering the cells with homozygous disruption of NF2. Clinically, RIMs with the NF2 fusion exhibited ill-defined borders and a tendency to develop in anatomic frontal location. Also, targeted sequencing panel confirmed that RIMs had fewer nonsynonymous NF2 mutations (6.5% vs. 30% in SM) and absence of mutations in TRAF7, SMO, KLF4, PIK3CA and AKT1, genes traditionally involved in SMs.Conclusion: Our study demonstrates that RIMs have distinct genomic drivers of oncogenesis as compared to SMs, specifically NF2 inactivation through fusion event. Radiation therapy possibly triggers genomic structural rearrangements through error-prone repair of double-stranded DNA breaks.

  Study EGAS00001002318

• RNA-Seq of Whole Blood from Patients with Intracranial Aneurysms

  Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size. However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imaging on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. We hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. We propose to use whole blood transcriptomes to develop a "one-stop" diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to develop and validate biomarkers to predict risk, as calculated by the currently-used metric of aneurysm size, the clinical PHASES score, and the RRS. Here, we collected blood samples from consented individuals who were receiving cerebral imaging at the Gates Vascular Institute (Buffalo, NY) for intracranial aneurysm. RNA extracted from blood samples (n=43) was subjected to RNA-sequencing and added to our existing database (n=44). When combined with our previous data, we had transcriptome data from 68 aneurysms (after additional sample filtering). This dataset was stratified into low- and high-risk according to IA size, PHASES score, and RRS score. Differentially expressed genes were identified and used to construct predictive models. Fastq files and basic demographic information for the 43 newly-sequenced intracranial aneurysm samples on this project will be available through dbGaP.

  Study phs003072

• CTCF scD&D-seq of IDH2 CHIP

  CTCF single-cell D&D-seq with GoT-ChA targeted genotyping of IDH2 R140Q CHIP variant from primary blood sample

  Dataset EGAD50000002273

• The genomic landscape of acute lymphoblastic leukemia with intrachromosomal amplification of chromosome 21

  Use scRNA-seq data from 4 iAMP21 patients to study the clonal evolution of iAMP21.

  Study EGAS00001006577

• Single-cell CITE-seq from MDS patients with SF3B1 mutations

  Single-cell CITE(cellular indexing of transcriptomes and epitopes)-seq from MDS (n = 2, MDS02 in 2 replicates). cDNA from 10x Genomics 3' V3.

  Dataset EGAD00001011281

• Mapping the epigenomic landscape of human monocytes following innate immune activation reveals context-specific mechanisms driving endotoxin tolerance

  Background Monocytes are key mediators of innate immunity to infection, undergoing profound and dynamic changes in epigenetic state and immune function which are broadly protective but may be dysregulated in disease. Here, we aimed to advance understanding of epigenetic regulation following innate immune activation, acutely and in endotoxin tolerant states. Methods We exposed human primary monocytes from healthy donors (n=6) to interferon-γ or differing combinations of endotoxin (lipopolysaccharide), including acute response (2hr) and two models of endotoxin tolerance: repeated stimulations (6+6hr) and prolonged exposure to endotoxin (24hr). Another subset of monocytes was left untreated (naïve). We identified context-specific regulatory elements based on epigenetic signatures for chromatin accessibility (ATAC-seq) and regulatory non-coding RNAs from total RNA sequencing. Results We present an atlas of differential gene expression for endotoxin and interferon response, identifying widespread context specific changes. Across assayed states, only 24-29% of genes showing differential exon usage are also differential at the gene level. Overall, 19.9% (6884 of 34616) of repeatedly observed ATAC peaks were differential in at least one condition, the majority upregulated on stimulation and located in distal regions (64.1% vs 45.9% of non-differential peaks) within which sequences were less conserved than non-differential peaks. We identified enhancer-derived RNA signatures specific to different monocyte states that correlated with chromatin accessibility changes. The endotoxin tolerance models showed distinct chromatin accessibility and transcriptomic signatures, with integrated analysis identifying genes and pathways involved in the inflammatory response, detoxification, metabolism and wound healing. We leveraged eQTL mapping for the same monocyte activation states to link potential enhancers with specific genes, identifying 1,946 unique differential ATAC peaks with 1,340 expression associated genes. We further use this to inform understanding of reported GWAS, for example involving FCHO1 and coronary artery disease. Conclusion This study reports context-specific regulatory elements based on transcriptomic profiling and epigenetic signatures for enhancer-derived RNAs and chromatin accessibility in immune tolerant monocyte states, and demonstrates the informativeness of linking such elements and eQTL to inform future mechanistic studies aimed at defining therapeutic targets of immunosuppression and diseases.

  Study EGAS00001007362

• TRACERx 100: whole exome data of the first 100 TRACERx tumours

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

  Study EGAS00001002247

• Dataset for melanoma-RNA

  Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008858

• Dataset for hematopoietic_malignancy-RNA

  Rare cancer sequencing data of 47 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008860

• Dataset for gynecologic_cancer-RNA

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008856

• Whole exome sequencing data of tumor/normal pairs for the study "TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells"

  Tumor DNA was extracted from formalin-fixed and paraffin embedded tumors of a large cohort of bladder cancer patients before treatment with anti-PD-L1. Normal DNA was extracted from matched PBMCs. Whole exome sequencing was performed. This is a subset of patients for which RNA sequencing is also provided (with more detailed phenotypic information).

  Dataset EGAD00001004218

• Human embryo ATAC+RNA single cell sequencing samples DAC (Linnarsson)

  DAC for human embryo ATAC+RNA single cell sequencing samples

  Dac EGAC50000000657

• A Multimodal Atlas of Human Brain Cell Types 2021 Data

  Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This dataset consists of transcriptome samples collected during Patch-seq recordings from layer 5 pyramidal neurons in the human middle temporal gyrus.

  Study phs002697

• Whole-genome-sequencing, Whole-exome-sequencing and RNA-sequencing in Sporadic ALS

  To identify the genetic cause and modifiers of Sporadic ALS, we performed Whole-genome-sequencing, Whole-exome-sequencing and RNA-sequencing of Sporadic ALS patients.

  Study JGAS000393

• ICR_RNASeq_pHGG

  RNA sequencing of paediatric high grade gliomas and diffuse intrinsic pontine gliomas. RNA was sequenced from fresh frozen surgical material or from primary cells cultured under stem cell conditions. RNA was subjected to Illumina whole transcriptome paired end sequencing. Data is provided as paired-end FASTQ files

  Dataset EGAD00001004116

• Gene Expression and Biomarker Utility in Post-Mortem Samples

  The FAA Functional Genomics Team examined the feasibility of analyzing gene expression profiles using post-mortem brain, lung, muscle, and blood samples collected from aviation accident fatalities, with the goal of validating post-mortem extracted RNA for use in RNA sequencing. We compared the RNA sequencing results obtained from THC-positive and THC-negative samples to determine whether RNA sequencing on samples collected from aviation accident fatalities was possible and if any differences in gene expression associated with THC consumption were detectable post-mortem. The study population included 57 males of indeterminant age who perished in general aviation accidents and for whom post-mortem toxicological testing identified delta-9-THC or its primary or secondary metabolites, as well as negative controls. We determined that RNA sequencing on post-mortem aviation accident fatality samples is possible, and further identified genes showing differential expression in lung and muscle between THC-positive and THC-negative samples. We conclude that post-mortem tissue samples collected from aviation accident fatalities are suitable for gene expression profiling, but caution researchers that such samples have low RNA integrity numbers and some degree of microbial contamination is both probable and to be expected. Raw sequencing files (.fastq) from this study are available in dbGaP.

  Study phs003546

• scATAC-seq of sorted CD45+ cells from blood and tissues

  scATAC-seq by 10xGenomics Droplet Sequencing from two human donors. scATAC sequences are available for FACS-sorted CD45+ cells from blodd, skin and vat (visceral adipose tissue)

  Dataset EGAD50000000510

• Cell subtypes subsets from subcortical MS snRNA-seq atlas

  Curated subsetting of cell subtypes derived from the 9 principal cell types within our subcortical Multiple Sclerosis (MS) lesions snRNA-seq atlas.

  Dataset EGAD50000000522

• CIRCLE-seq of PDO

  CIRCLE-seq data of PDAC 1 patient-derived organoid (PDO) - Unmapped reads, libraries were sequenced using the Illumina NextSeq500 with the NextSeq 500/550 Mid Output Kit v2.5 (300 Cycles), generating around 10M paired end 150bp reads per sample

  Dataset EGAD50000000281

• Chromatin accessibility profiling of primary human hepatocytes

  The chromatin accessibility profiling of primary human hepatocytes using Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq).

  Study EGAS50000001230

• A distinct monocyte cellular state links systemic immune dysregulation to pulmonary impairment in long COVID

  single cell multiome dataset (snRNA-seq + snATAC-seq) from PBMC of patients with long COVID disease.

  Dataset EGAD50000001729

• 4C-seq data

  4C-seq data was generated for regions of interest to confirm enhancer-gene promoter interactions

  Dataset EGAD00001001847

• ATAC-seq dataset

  This dataset contains ATAC-seq data performed in MM.1S cell line in ETOH (control) or Dexamethasone condition (Treatment)

  Dataset EGAD00001011135

• UCSF brain tumor data

  Single Nuclei ATAC seq data from GBM tumor samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005314

• Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

  DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

  Study EGAS00001001191

• 41 fibroblast RNAseq samples of pediatric patients with childhood epilepsy and developmental delay

  We used RNA sequencing of patient fibroblasts to find a genetic diagnosis in patients with exome-negative childhood epilepsy. RNA extracted from 41 individuals' cultured fibroblasts (passage 3-6) was collected and sequenced at a depth of 90-110 paired reads per sample.

  Study EGAS50000000792

• Whole genome sequencing of matched patient sample sets of normal and tumor DNA

  Sixteen matched, male and female patient sample sets, each comprising normal DNA, tumor DNA, and RNA, were processed for storage comparison studies. Upon receipt, 10 μl quality control aliquots were prepared from each sample. DNA samples were characterized using Qubit dsDNA High Sensitivity assay for quantification, Genomic DNA TapeStation for integrity assessment (DIN scores), and NanoDrop for purity evaluation. RNA samples were analyzed using Qubit RNA High Sensitivity assay, RNA TapeStation (RIN scores), and NanoDrop. Each sample was divided equally by volume for parallel processing.

  Dataset EGAD50000002441

• 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.

  Study EGAS00001007181

• T-cell receptor sequencing of tumor-infiltrating lymphocytes (TIL) in breast cancer

  The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing patients’ tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating widely available archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of various tumor environments. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and revealed higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top ten dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is readily applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

  Study EGAS00001007125

• Identifying Novel Small RNA Biomarkers Unique to Patients with Gastric Cancer

  The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented. Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: 30097497 DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States).

  Study phs001767

• cell-free Nucleosome ChIP-seq

  Dataset includes cell-free ChIP-seq data of 268 samples (from 61 self-declared healthy donors, four patients with acute myocardial infarction, 29 patients suffering from autoimmune, metabolic, or viral liver diseases and 56 metastatic colorectal carcinoma (CRC) patients). DNA libraries preparation is documented in the methods section. Libraries were paired end sequenced by Illumina NextSeq 500 and aligned to the human genome (hg19) using bowtie2 (2.3.4.3) with ‘no-mixed’ and ‘no-discordant’ flags. This dataset includes fastq and BAM files of all samples.

  Dataset EGAD00001006811

• scRNA-seq dataset of patient with immune dysregulation

  scRNA-seq dataset on a patient (P_IKZF2-het) presenting with immune dysregulation. This dataset contains raw and processed files from scRNA-seq performed on samples using the 10x Genomics Chromium Controller with the Chromium Single Cell 3′ Reagent Kit (v3 chemistry). There are three paired-end (75 bp) fastq files (I1, R1, R2) and three processed files generated with 10x Genomics Cell Ranger v3.0.2 software against GRCh38 human reference transcriptome (scrnaseq_P_IKZF2-het_barcodes.tsv.gz, scrnaseq_P_IKZF2-het_features.tsv.gz, scrnaseq_P_IKZF2-het_matrix.mtx.gz).

  Dataset EGAD00001008443

• TARGET-seq+ single-cell genotyping

  Single-cell genotyping data for bone marrow samples from 9 cases with clonal hematopoiesis and 1 control sample. The TARGET-seq+ protocol was used to generate plate-based 3' transcriptome data. For details on cell sorting and the TARGET-seq+ protocol see the methods section of the manuscript. One FASTQ file is provided per cell. Cells are named with their plate and well IDs and the subject ID. Empty wells (no-cell controls) are named "blank". Corresponding transcriptome files use the same naming with the "_transcriptome" suffix.

  Dataset EGAD00001011150

• BLUEPRINT September 2016, ChIP-Seq for conventional dendritic cell from cord blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002948

• BLUEPRINT September 2016, ChIP-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002949

• BLUEPRINT September 2016, ChIP-Seq for memory B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002950

• BLUEPRINT September 2016, ChIP-Seq T-cell Acute Lymphocytic Leukemia from capillary blood, on Genome GRCh38

  ChIP-Seq data for 4 sample(s) T-cell Acute Lymphocytic Leukemia from capillary blood, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002952

• RNA sequencing data from visceral and abdominal subcutaneous adipose tissue from morbidly obese women with normal glucose tolerance or type 2 diabetes

  The study group consisted of 17 obese women with normal glucose tolerance and 15 obese women with T2DM. Adipose tissue specimens were taken from the epigastric region of the abdominal wall (SAT) and from the major omentum (VAT). RNA was isolated and RNA sequencing was used to analyse the transcriptome. Dharuri H et al, Diabetologia. 2014;57(11):2384-92.

  Study EGAS00001001872

• RNA sequencing of a glioblastoma PDX cohort

  Patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In this project, we molecularly characterized a comprehensive panel of glioma PDX models with well conserved molecular and pathological features over multiple passages. PDX samples were subjected to next generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in glioblastoma. In summary, we reported a newly established and molecularly characterized panel of glioma PDX models with high relevance for translational preclinical research.

  Study EGAS00001007119

• TSO500 on RNA

  TruSight Oncology 500 RNA probes panel on case 521

  Dataset EGAD50000000271

• Therapy and RNA group Ghent DAC

  This is a Data Access Committee for datasets of the Therapy and RNA group Ghent (TaRGeT, Belgium).

  Dac EGAC50000000491

• TST170 Pilot RNA BAM

  TST170 Pilot RNA BAM files

  Dataset EGAD00001006044

• Human iPSC-derived brain cell RNA sequencing data DAC at UEF (DAC-hiPSC)

  RNA sequencing data from human iPSC-derived cell model systems

  Dac EGAC50000000949

• ATAC-seq in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  ATAC-seq performed in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives to profile alterations in chromatin accessibility associated with constitutional MLH1 epimutation.

  Dataset EGAD50000000714

• scDNA-seq

  Single cell DNA-seq data (CLL gene panel - Tapestri single-cell DNA CLL panel, Mission Bio)

  Dataset EGAD00001008960

• scRNA-seq of monocultures and co-cultures of PDAC-PDOs and CAFs

  scRNA-seq of monocultures and co-cultures of patient-derived PDAC organoids and matched CAFs. 3 sample sets per patient.

  Dataset EGAD00001009655

• Human tumor scATAC-seq

  We profiled 4 high-grade gliomas patient brain tumor samples by single-cell ATAC-seq using the 10X Chromium 3' technology. The raw fastq and index files are provided.

  Dataset EGAD00001008347

• McGill EMC Release 4 for assay "ATAC-seq"

  McGill EMC Release 4 for assay "ATAC-seq": Sequencing of transposase-accessible chromatin as described by Buenrostro et al. (Nature Methods 10, 1213?1218 (2013) doi:10.1038/nmeth.2688)

  Dataset EGAD00001001300

• BLUEPRINT: WGBS-seq for monocytes and neutrophils

  WGBS-seq for monocytes and neutrophils

  Dataset EGAD00001000673

• RNA sequencing

  For RNA sequencing: All sample numbers starting with 6717 are tumor samples which has been sequenced using transcriptomics (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata). RNA sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000383

• Paired RNA sequencing of Thymic epithelial tumors - Additional Dataset

  Paired RNA sequencing of additional samples of Thymic epithelial tumors. Uploaded are the paired fastq files, sequencers were Illumina HiSeq 2500, HiSeq 4000, NovaSeq 6000 and HiSeq X Ten. The kits used were Illumina Truseq RNA and Illumina Truseq stranded mRNA.

  Dataset EGAD50000000324

• Cohort A RNA sequencing

  Cohort A includes glioma tumors of varied grading and pathology from male and female individuals. RNA was isolated from fresh frozen glioma tissue of each sample tumor block from Cohort A.

  Study EGAS50000000950

• Cohort B RNA sequencing

  Cohort B includes IDH-wild type, EGFR amplified, surgically derived glioblastoma tissue samples from male and female individuals. RNA was isolated from FFPE glioma tissue of each sample from Cohort B.

  Study EGAS50000000953

• MATISSE bulk RNA-sequencing data

  Tumor availability: Bulk RNA sequencing was performed on tumor biopsies of 48 patients at baseline and 45 patients across time points (baseline n=48, week 1 n=38, week 2 n=34, week 4 n=37), including lymph node metastasis that were sequenced in addition to the primary tumor. Tumor RNA was extracted from formalin-fixed paraffin-embedded (FFPE) primary tumor and lymph node metastasis sections containing at least 10% viable tumor cells present in the sample, except for on-treatment samples with a complete pathological response in which we isolated samples with at least 10% immune-infiltration with no viable tumor cells. A pathologist (LS) scored the tumor percentage and indicated the most tumor-dense region on a hematoxylin and eosin (H&E) stain slide for subsequent RNA isolation. According to the manufacturer's protocol, five to 10 FFPE slides (10 µm) were used for RNA isolation using the AllPrep DNA/RNA FFPE isolation kit (Qiagen, 80234) and the QIAcube. Genetic Diagnostics and Sequencing Services (CeGaT) performed RNA sequencing in Germany. Data processing: Demultiplexing of the sequencing reads was performed with Illumina bcl2fastq (v2.20). Adapters of the reads (Pico v2 SMART adapter, first three nucleotides of the second sequencing read) were trimmed with Skewer (v0.2.2), without quality trimming. RNA-sequencing data was aligned to GRCh38 (Ensembl v109) using STAR (v2.7.9) in 2-pass mode with default settings. Gene counts were generated with the HTSeq (v2.0.2). FastQC (v0.12.1) and MultiQC (v1.14) were used for assessing data quality, on FASTQ files and intermediate processing steps.

  Dataset EGAD50000001470

• RNA sequencing of myxofibrosarcoma

  RNA sequencing (fastq files) of 29 samples of myxofibrosarcoma

  Dataset EGAD00001004102

• Gene expression adaptation of metastases to their host tissue

  The adaptation of metastatic cells to their host tissue critically determines the pathogenicity of a cancer and therefore patient survival. Yet, it remains elusive to what extent the host environment drives gene expression programs in metastatic cells. Here we identify adaptive mechanisms that enable metastases to establish themselves in a novel tissue context. We performed single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis to deduce tissue adaptive expression patterns. A novel computational approach identified genes and pathways that consistently adapted to the host tissue at the transition from the primary tumor to the paired metastasis across donors. This analysis revealed that the majority of expression changes in the metastasis reflect an expression signature reminiscent of benign liver epithelial cells. Cellular processes adapting to the liver environment include basic cellular functions such as energy metabolism, as well as tissue-specific pathways such as the regulation of lipid metabolism by PPAR-α. These adaptations potentially increase the pathogenicity of the metastatic cells and may provide new therapeutic strategies.

  Study EGAS50000000817

• 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. (Companion proteomic data is available in the ProteomeXchange Consortium, PRIDE: PXD026570).

  Study EGAS00001005786

• TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

  We examined tumours from a large cohort of patients with metastatic urothelial bladder cancer (mUC) treated with an anti–PD-L1 agent (atezolizumab) and identified major determinants of clinical response and immune escape. Whole transcriptome profiles were generated for 368 patients using TruSeq RNA Access technology (Illumina). Somatic mutations were determined via whole exome sequencing for a subset of these patients. - Response was associated with CD8+ T effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden (TMB). On the other hand, lack of response was associated with a transforming growth factor β (TGF-β) signature, particularly in patients with CD8+ T cells preferentially residing in collagen-rich matrix surrounding tumours. Integration of these three independent biological features provided the best basis for understanding outcome in this setting. -

  Study EGAS00001002556

• Mesenchymal inflammation drives genotoxic stress in hematopoietic stem cells and predicts disease evolution in human pre-leukemia

  Mesenchymal niche cells may drive tissue failure and malignant transformation in the hematopoietic system but the molecular mechanisms and their relevance to human disease remain poorly defined. We demonstrated that perturbation of mesenchymal cells in a mouse model of the preleukemic disorder Shwachman-Diamond syndrome induces mitochondrial dysfunction, oxidative stress and activation of DNA damage responses in hematopoietic stem and progenitor cells. In this study we demonstrate, through massive parallel RNA sequencing of highly purified mesenchymal cells in a range of human preleukemic syndromes, TP53-S100A8/9-TLR4 inflammatory signaling as a common driving mechanism of genotoxic stress, which could be attenuated by TLR4 blockade. S100A8/9 expression in mesenchymal cells predicted outcome in myelodysplastic syndromes, the principal human preleukemic condition, independent of known prognostic variables. Collectively, findings reveal a concept of mesenchymal niche-induced genotoxic stress in heterotypic stem and progenitor cells through inflammatory signaling as an actionable determinant of disease outcome in human preleukemia. The data further provide novel conceptual and mechanistic insights into the intimate link between inflammation and cancer.

  Study EGAS00001001926

• MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

  Despite the established role of the transcription factor MYC in cancer, little is known about the involvement of lncRNAs in mediating MYC’s function. Here we have intersected RNA-sequencing data from MYC-inducible cell lines, from a cohort of 91 mature B-cell lymphomas and from sorted germinal-center B-cells. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, showing a strong correlation with MYC expression in MYC-positive lymphomas and in pancreatic ductal adenocarcinomas. RNAi experiments showed that MINCR controls cellular viability by influencing the expression of MYC-regulated cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR acts as a modulator of MYC transcriptional control of cell cycle genes.

  Study EGAS00001001199

• HipSci - Congenital Hyperinsulinia - RNA Sequencing - July 2017

  HipSci - Congenital Hyperinsulinia - RNA Sequencing - July 2017

  Dataset EGAD00001003534

• HipSci - Embryonic Stem Cells - RNA Sequencing - April 2016

  HipSci - Embryonic Stem Cells - RNA Sequencing - April 2016

  Dataset EGAD00001002000

• CRC cell line ATAC-seq

  ATAC-Seq data for C32, CACO2, CL11, HT29, SW403, SW480, SW948 MSS CRC cell lines, and HCEC-1CT normal colon cell line

  Dataset EGAD50000000296

• Two scRNA-seq datasets from control and irradiated organoids.

  Dataset includes two scRNA-seq samples from control and irradiated organoids. Files included in the dataset are Fastq files. Sample libraries produced with Chromium X were sequenced on an Illumina NovaSeq 6000 sequencer.

  Dataset EGAD50000001933

• ctDNA mutation analysis using the SiMSen-seq approach

  Mutation analysis in plasma samples with low ctDNA levels using a molecular barcoding technology, i.e. the single target approach SiMSen-seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing).

  Dataset EGAD00001006104

• Results of scRNA-seq analysis of a PBMC collected from a male with a mosaic 45,X/48,XYYY karyotype

  Results of scRNA-seq analysis of a PBMC collected from a male with a mosaic 45,X/48,XYYY karyotype

  Dataset EGAD00001008645

• BLUEPRINT September 2016, ATAC-seq for bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002710

• CLL ATAC Seq of Untreated and IBET762 treated samples

  CLL PBMC cells were isolated using ficoll gradient. They have been treated with IBET762 or DMSO as solvent control and ATAC Seq has been performed on them.

  Dataset EGAD00001008723

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Dataset EGAD00001009964

• CITE-seq

  This dataset contains the raw sequencing data (Runs) from all of the 10x Genomics single-cell CITE-seq Experiments, as well as the demultiplexed cell-donor identities matrices which were generated with Vireo (Analysis).

  Dataset EGAD00001009820

• Dataset to study clonal evolution in iAMP21 patient SJBALL021901 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJBALL021901 with 71 high quality cells sequenced (67 blast and 4 normal)

  Dataset EGAD00001009755

• BLUEPRINT: WGBS-seq of B cells

  Whole Genome Bisulfite-seq of four B cell samples

  Dataset EGAD00001000710

• release_2: ICGC PedBrain: whole exome sequencing and Target-Seq

  release_2: ICGC PedBrain: whole exome sequencing and Target-Seq

  Dataset EGAD00001001624

• Epigenetic profiles of neuroblastoma PDXs

  This dataset contains bam files for ChIP-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft). It includes the bam files for the H3K27ac mark as well as the bam files of the corresponding input DNA for each sample.

  Dataset EGAD00001003394

• Single-cell ATAC-Seq (Chromium Next GEM Single Cell ATAC kit v1.1 from 10X Genomics )

  Human data for chromatin accessibility (scATAC-Seq) in CD34+ B cell precursors.

  Dataset EGAD00001010910