12304 results for "cancer rna-seq"

in 73.04 milliseconds.

• Reference epigenome Islet-derived-iPSC01 h3k9me3 ChIP-Seq data generated from KEP study

  Islet-derived-iPSC01 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007441

• Reference epigenome Islet-derived-iPSC01 input ChIP-Seq data generated from KEP study

  Islet-derived-iPSC01 input ChIP-Seq paired end data

  Dataset EGAD00001007442

• Reference epigenome Islet-derived-iPSC02 h3k27ac ChIP-Seq data generated from KEP study

  Islet-derived-iPSC02 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007443

• Reference epigenome Islet-derived-iPSC02 h3k27me3 ChIP-Seq data generated from KEP study

  Islet-derived-iPSC02 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007444

• Reference epigenome Islet-derived-iPSC02 h3k36me3 ChIP-Seq data generated from KEP study

  Islet-derived-iPSC02 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007445

• Reference epigenome Islet-derived-iPSC02 h3k4me1 ChIP-Seq data generated from KEP study

  Islet-derived-iPSC02 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007446

• Reference epigenome Islet-derived-iPSC02 h3k9me3 ChIP-Seq data generated from KEP study

  Islet-derived-iPSC02 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007448

• Reference epigenome Islet-derived-iPSC02 input ChIP-Seq data generated from KEP study

  Islet-derived-iPSC02 input ChIP-Seq paired end data

  Dataset EGAD00001007449

• RNA-Sequencing of cervical cancers

  Question: Can we identify cervical cancer patients who are at risk for distant metastatic (DM) recurrence following treatment with radiotherapy, concurrent weekly cisplatin and brachytherapy (RTCT). Findings: An immune-based 55 gene risk score was developed using a cohort of 81 patients treated with RTCT that was strongly predictive of DM and cause-specific survival (CSS). The risk score was validated in two independent patient cohorts. A high immune metastatic risk score was associated with a high tumor mutational burden and a ‘cold’, immune-excluded tumor microenvironment at diagnosis. Meaning: The immune gene expression risk score may help to identify patients at risk of DM and potential targets for mitigating this risk.

  Study EGAS50000000087

• RNA sequencing of undifferentiated sarcomas

  Undifferentiated sarcomas (USARCs) of adults are diverse, rare, and aggressive soft tissue cancers. Recent sequencing efforts have confirmed that USARCs exhibit one of the highest burdens of structural aberrations across human cancer. Here, we sought to unravel the molecular basis of the structural complexity in USARCs by integrating DNA sequencing, ploidy analysis, gene expression, and methylation profiling. We identified whole genome duplication as a prevalent and pernicious force in USARC tumorigenesis. Using mathematical deconvolution strategies to unravel the complex copy-number profiles and mutational timing models we infer distinct evolutionary pathways of these rare cancers. In addition, 15% of tumors exhibited raised mutational burdens that correlated with gene expression signatures of immune infiltration, and good prognosis.

  Study EGAS00001003291

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

  DAC for human embryo ATAC+RNA single cell sequencing samples

  Dac EGAC50000000657

• ChIP-Seq files for PCGP ATRX study

  ChIP-Seq files for PCGP ATRX study paper titled "MYCN Amplification and ATRX Mutations are Incompatible in Neuroblastoma"

  Dataset EGAD00001004429

• Primary Neuroblastoma Circle-seq Data

  Circle-seq data for 21 primary neuroblastoma samples supporting Koche et al. Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma (2020).

  Dataset EGAD00001006580

• Single-cell DNA-seq

  Single-cell DNA sequencing (scDNA-seq) data.

  Dataset EGAD00001008779

• ATAC-seq

  This dataset contains the raw sequencing data (Runs) for all 10x Genomics single-cell ATAC-seq Experiment.

  Dataset EGAD00001009822

• ATAC-seq of cohesin-mutated and -wildtype adult AMLs

  ATAC-seq (Illumina TDE1 Transposase) to profile accessible chromatin regions of cohesin-mutated (STAG2 or RAD21 mutations) and -wildtype adult AMLs.

  Dataset EGAD00001011267

• 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

• 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

• 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

• Type 2 Diabetes Starr County GWAS and Exome Sequencing

  The T2D Seq GWAS Starr County Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs001166 T2D Seq GWAS Starr County Cohort. phs000143 CIDR T2D Hanis phs001099 T2D GENES Starr County

  Study phs001166

• Type 2 Diabetes in African Americans, GWAS and Exome Sequencing

  The T2D Seq GWAS AA Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001167 T2D Seq GWAS AA Cohort. phs000140 CIDR T2D Bowdens phs001102 T2D GENES AA

  Study phs001167

• Evolving Cell States and Oncogenic Drivers during the Progression of IDH-Mutant Gliomas

  The study aims to understand the changes in cell states during the progression of IDH mutant gliomas. We generated scATAC-seq data from tumor samples of patients with IDH mutant gliomas, ranging from grade 2 to grade 4, including both IDH mutant oligodendroglioma and IDH mutant astrocytoma samples. Additionally, we have generated scRNA-seq data from patient-derived organoids that were treated with a DNMT1 inhibitor.

  Study phs003697

• Gene regulation of human stimulated and cultured CD4+ Treg cells

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs) stimulated using PMA and ionomycin or cultured without stimulus for 18 hours. It includes whole genome sequence data for ChM-seq (18 H3K4me3, 20 H3K27ac and 3 inputs), ATAC-seq (42 samples) and whole transcriptome (39 samples). All individuals were genotyped using coreExome Illumina SNP chip array (included in EGAS00001003516).

  Study EGAS00001003515

• Asthma in the Lives of Families Today (ALOFT)

  Social interactions and the overall psychosocial environment have a demonstrated impact on health, particularly for people living in disadvantaged urban areas. Here we investigated the effect of psychosocial experiences on gene expression in peripheral blood immune cells of 251 children with asthma in Metro Detroit. Participants were included from an ongoing longitudinal study Asthma in the Lives of Families Today (ALOFT; recruited from November 2010-July 2018. The ALOFT project was established to identify the behavioral and biological pathways through which family social environments impact youth with asthma.In version 1 we used RNA-sequencing and a new machine learning approach to identify transcriptional signatures of 19 variables including psychosocial factors, blood cell composition and asthma symptoms. Using longitudinal data collected from a subset of the participants we showed that transcriptional signatures track the longitudinal changes in measured phenotypes. Importantly, we found 169 genes associated with asthma that are regulated by psychosocial factors, and 344 significant gene-environment interactions for gene expression levels. These results demonstrate that immune gene expression mediates the link between negative psychosocial experiences and asthma risk.In version 2, we focused on pubertal development. We identified substantial gene expression changes associated with age and pubertal development. We showed that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome.Version 3 uses single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.Version 4 adds scATAC-seq in activated peripheral blood mononuclear cells (PBMC) from 16 children with asthma with phytohemagglutinin (PHA) or lipopolysaccharide (LPS), and treated with dexamethasone (DEX), an anti-inflammatory glucocorticoid. We analyzed changes in chromatin accessibility, measured transcription factor motif activity, and identified treatment and cell-type specific transcription factors that drive changes in both gene expression mean and variability. We observed strong positive linear dependence between motif response and their target gene expression changes, but negative in variability changes. This result suggests that an increase of transcription factor binding tightens the variability of gene expression around the mean. We then annotated genetic variants in chromatin accessibility peaks and response motifs followed by computational fine-mapping of eQTL signals from a pediatric asthma cohort. We found that eQTLs were 5-fold enriched in peaks with response motifs and refined the credible set for 410 asthma risk genes, with 191 having the causal variant in response motifs. These results enhance the understanding of molecular mechanisms for asthma risk variants mediated by gene expression.

  Study phs002182

• Identification of Novel Therapeutic Targets for Calcific Aortic Valve Stenosis Using Integrative Genomics

  In order to identify novel therapeutic targets for calcific aortic valve stenosis, we have generated a large transcriptomic dataset from RNA sequencing of human aortic valve tissues from 500 individuals undergoing aortic valve replacement or heart transplant at the Institut universitaire de cardiologie et de pneumologie de Québec – Université Laval (QUEBEC-CAVS-RNA). This dataset represents a unique resource to understand the molecular mechanisms underlying aortic valve diseases.

  Study phs003541

• Mayo Clinic and Illumina Collaborative Early Stage Ovarian Cancer (ESOC) Study

  Twenty five patients with early stage carcinoma (Stage I and II) of the ovary were consented for this study. As part of a collaborative agreement with Illumina Inc, Tumor-DNA and patient matched normal DNA from blood underwent whole genome sequencing and microarray genotyping and RNA underwent RNASeq. Tissue also underwent IHC staining for TP53 mutations. The aim of the study was to profile the genomic landscape of these early tumors to discover biomarkers for early detection or subgrouping into different genomic or outcome subgroups. Analyses performed include somatic mutation analysis, RNASeq mutation analysis, LOH analysis, structural variant detection. The current release of this study focusses on 17 patients with serous carcinoma and stage 1 or 2 and with high grade (3 or 4).

  Study phs000897

• 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

• 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

• BLUEPRINT September 2016, ChIP-Seq for thymocyte from thymus, on Genome GRCh38

  ChIP-Seq data for 5 sample(s) for thymocyte from thymus, on Genome GRCh38. 17 run(s), 17 experiment(s), 17 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 EGAD00001002947

• ChIP-Seq on multiple myeloma and plasma cell leukaemia cell lines

  ChIP-seq data (H3K4Me1, H3K4Me3, H3K27Ac histone modifications) in experimental triplicates on multiple myeloma cell line KMS11 and plasma cell leukaemia cell lines L363 and JJN3. ChIP reactions were performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal Kit. ChIP libraries were generated using HTP Illumina library preparation kit, and sequenced using Illumina HiSeq 2000 with 100 bp single-ended reads. ChIP-seq files are in BED format.

  Dataset EGAD00001003349

• ATAC-seq data from primary AML samples with t(3;8)

  Open chromatin regions in the MYC super-enhancer region were investigated by ATAC-seq in t(3;8) AML. ATAC-seq was performed as described (Buenrostro et al, 2013) with a modification in the lysis buffer (0.30 M sucrose, 10 mM Tris pH 7.5, 60 mM KCl, 15 mM NaCl, 5 mM MgCl2, 0.1 mM EGTA, 0.1% NP40, 0.15 mM Spermine, 0.5 mM Spermidine, 2 mM 6AA) to reduce mitochondrial DNA contamination.

  Dataset EGAD00001007910

• ATAC-seq dataset of patient and healthy donors

  ATAC-seq dataset on a patient (P) presenting with defects of immunity and two (C5, C6) healthy donors. This dataset contains raw and processed files from ATAC-seq chromatin accessibility analysis. There are 3 single-read (50 bp) fastq files (1 per patient/ donor). Processed files consist of narrowPeak files (1 per patient/ donor) and one file that contains read counts in consensus peaks.

  Dataset EGAD00001008370

• 3D-GSC_expression_profiles

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

  Study EGAS00001007182

• small RNA-sequencing and RNA-sequencing of human brain tissue with temporal lobe epilepsy

  This data set contains the raw .fastq files from two RNA-sequencing experiments and two small RNA-sequencing experiments. Both control brain tissue and tissue from sufferers of mesial temporal lobe epilepsy were sequenced. Two different brain regions were sequenced; the cortex and the hippocampus. For more details please see: Mills, James D., et al. "Coding and non-coding transcriptome of mesial temporal lobe epilepsy: Critical role of small non-coding RNAs." Neurobiology of disease 134 (2020): 104612.

  Dataset EGAD00001005735

• Single-Cell Multi-Omic Analysis of the Vestibular Schwannoma Ecosystem Uncovers a Nerve Injury-Like State

  Vestibular schwannomas are benign tumors that can lead to significant morbidity, including hearing loss, facial nerve paralysis and obstructive hydrocephalus. The genomic landscape of vestibular schwannomas is relatively bland and the molecular pathophysiology of vestibular schwannomas is poorly understood. Therefore, we performed single cell RNA sequencing on 15 sporadic vestibular schwannomas, with paired single cell ATAC sequencing (n = 6) and whole exome sequencing (n = 12) to perform a detailed characterization of the vestibular schwannoma tumor microenvironment at the transcriptional and epigenetic level. We validated our results by analyzing bulk RNA sequencing data from 22 newly sequenced vestibular schwannomas and 173 previously sequenced bulk RNA sequencing data from 195 vestibular schwannomas. Data available in dbGaP include whole exome sequencing of 12 tumors and matched blood samples. Matching single cell RNA sequencing and single cell ATAC sequencing data is available via NCBI GEO.

  Study phs003318

• DAC for "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling"

  This is the DAC for the study "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling" of PD Dr. Aurélie Ernst (a.ernst@dkfz.de) B420, DKFZ.

  Dac EGAC50000000452

• ATAC-seq samples from 9 cHL cell lines

  The dataset contains 21 ATAC-seq samples from 9 cHL cell lines. Files within the dataset are raw fastq files for each cell line.

  Dataset EGAD50000001273

• IVF MeDIP-seq bam files

  Bam files consisting of aligned MeDIP-seq reads from cord blood cells and cord blood mononuclear cells of twins conceived through in vitro fertilisation

  Dataset EGAD00001003158

• TSO500 on RNA

  TruSight Oncology 500 RNA probes panel on case 521

  Dataset EGAD50000000271

• RNA sequencing of myxofibrosarcoma

  RNA sequencing (fastq files) of 29 samples of myxofibrosarcoma

  Dataset EGAD00001004102

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

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

  Study JGAS000783

• 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 and peripheral blood mononuclear cells obtained from patients with atopic dermatitis along with healthy controls in Japanese population.

  Study JGAS000628

• Long-read and short-read RNA sequencing of human normal liver organoid with or without SF3B4 overexpression

  There are 2 matched short and long read RNA sequencing samples. The project aims to find alternative splicing events and resulting transcript isoforms modulated by SF3B4

  Study EGAS50000001131

• Small RNA sequencing of human oocytes and early embryos

  This study looks at small RNA expression in human oocytes (n=12), zygotes (n=5), and embryos (n=10). The sample preparation and sequencing were done in two batches.

  Study EGAS50000000157

• 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

• Bulk RNA-sequencing of AML blasts pre and post culture

  This dataset contains 18 Fastq files from 9 samples (pre-culture (n=3), post culture in standard (n=4) or niche-llike (n=2) conditions) from 4 patients.They correspond to bulk RNA sequencing on Illumina instrument of libraries prepared using SMARTer Universal Low Input RNA Kit.

  Dataset EGAD00001008773

• 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

• 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

• WES and Panel-seq data of pediatric tumors

  Paired-end WES and targeted Panel-seq data from 140 pediatric tumor samples. Sequencing was performed on Illumina HiSeq 4000, MiSeq or HiSeq 2500.

  Dataset EGAD50000000577

• 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

• 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

• 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 SJE2A066 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A066 with 69 high quality cells sequenced (62 blast and 7 normal)

  Dataset EGAD00001011329

• 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

• 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

• RNA sequencing of Resistant BCC samples.

  RNA sequencing of Resistant BCC samples.

  Dataset EGAD00001000881

• Characterization of a human iPSC-derived islet differentiation model

  To explore the contribution of islet development to T2D pathogenesis, we characterised the transcriptomes of 3 human iPSC lines (from independent donors) differentiated along the islet development lineage. Whole transcriptome RNA-seq was performed at 7 developmental stages: definitive endoderm, primitive gut tube, posterior foregut (PF), pancreatic endoderm, endocrine progenitors, endocrine-like cells, and beta-like cells (BLC). Differentially-expressed (ΔExp) genes were assigned to the stage in which they were most upregulated (versus baseline iPSC profile), and used to assess the enrichment of T2D GWAS genes, as well as to predict the upstream transcription factors at each developmental stage.We found 9409 ΔExp genes across all stages, including known markers of islet development (NEUROG3, INS). Genes ΔExp in the most-differentiated (BLC) stage were significantly enriched for genes within the 99% credible sets of T2D GWAS loci. Despite this enrichment in BLC only, over 70% of genes mapping within the credible sets were ΔExp before this stage, highlighting the relevance of key T2D GWAS genes in islet development: e.g. expression of TCF7L2 peaked during the PF stage (log2FC=1.2; q=8.5×10-10). REST and LMNA are also highlighted by the analyses as having a potential function in islet development, considering their pattern of expression and those of the genes they regulate. Transcriptomic signatures derived from this iPSC differentiation model highlight T2D-associated GWAS loci, monogenic diabetes genes and potential master regulators of gene networks with plausible function in islet development. All these provide clues for developmental mechanisms contributing to T2D diabetes pathology.

  Study EGAS00001002721

• A unidirectional histone code in bidirectional promoters across cell types

  Recent studies indicate that thousands of genes are expressed from bidirectional promoters (BDPs). Gene regulation at BDPs is poorly understood, in particular how the cell is able to regulate them differently. Here we investigate the effect of histone Modifications in BDP regulation. In this study, we model the gene activity using different gene expression assays, such as RNA-Seq, GRO-cap, and CAGE around the BDP transcription start sites (TSSs) using different histone modifications in various cell types. We develop a new statistical approach that links histone modifications to gene expression at BDPs. It improves over previous methods, because it is able to capture spatial dependencies of histone modifications along a promoter and leads to more interpretable results. We predict a general histone code that is independent of transcript orientation, cell type, and promoter configuration. The histone code at BDPs reveals that promoters are regulated unidirectionally, such that the majority of histone marks associated with gene expression occur downstream of the gene's TSS. By contrasting associations of histone marks with steady-state levels of capped RNAs in CAGE and nascent capped RNAs in GRO-cap, we show which histone marks have a preference for initiating polymerases and actively elongating polymerases. Using single-cell data we show that the bidirectional histone signal of activating marks is often due averaging of a heterogeneous cell population. Our results have implications for other experiments where the relationship between histone modification and gene initiation or gene elongation is investigated on a genome-wide scale.

  Study EGAS00001001656

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Dataset EGAD50000000226

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. We performed multi-omic analysis including whole-exome, RNA and miRNA sequencing and quantification of 126 proteins in a series 34 LCCL coupled with a screening of 29 anti-cancer agents. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular "proliferation class" of HCC. Genomic alterations of the RAS-MAPK pathway correlated with trametinib sensitivity that was more potent than FGFR4 inhibitors in tumor cells depending on the FGF19/FGFR4 pathway. Moreover, we showed that FGF19 amplification was only functional in tumor cells that retained a hepatocyte differentiation program with expression of FGFR4, KLB and NR1H4 highlighting the complex interplay between the genomic and transcriptomic context in drug response. We also identified drugs/combination that could target efficiently the transcriptomic "progenitor subclass of HCC", as well as specific genetic contexts such as inactivating mutations in TSC1/TSC2 and TP53 associated with higher sensitivity to the mTOR inhibitor rapamycin and the AURKA inhibitor alisertib, respectively. LCCL represent relevant preclinical models for drug-biomarker discovery in HCC and enabled to identify molecular contexts linked with particular therapeutic vulnerabilities that may be useful to stratify patients in future clinical trials

  Study EGAS00001003536

• HipSci - Alport Syndrome - RNA Sequencing - July 2017

  HipSci - Alport Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003532

• HipSci - Battens Disease - RNA Sequencing - July 2017

  HipSci - Battens Disease - RNA Sequencing - July 2017

  Dataset EGAD00001003533

• HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

  HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003535

• HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

  HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

  Dataset EGAD00001003540

• HipSci - Macular Dystrophy - RNA Sequencing - July 2017

  HipSci - Macular Dystrophy - RNA Sequencing - July 2017

  Dataset EGAD00001003541

• HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

  HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

  Dataset EGAD00001003542

• HipSci - Usher Syndrome - RNA Sequencing - July 2017

  HipSci - Usher Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003543

• Osteosarcoma sequencing data

  This study shares DNA and RNA sequencing data from embryonal rhadbomyosarcoma patients

  Study EGAS00001005600

• RNA sequence of HUB_5 cell culture

  RNA sequence data for conditionally reprogrammed cells from patient HUB_5

  Dataset EGAD00001001923

• Title: Divergent levels of CD112 and INKA1 define a distinct subset of human long-term hematopoietic stem cells

  The data provided here was critical in establishing that human long-term hematopoietic stem cells (LT-HSC), previously described as the most primitive HSC population, is actually composed of distinct subsets that can be prospectively isolated. Via mechanistic studies centering around the Rho-GTPase effector kinase PAK4 and its inhibitor INKA1, we identified the immune checkpoint ligand CD112 as a marker for hematopoietic stem and progenitor cells, that is highest expressed on LT-HSC. More importantly, CD112 can be used to stratify functionally distinct subsets within LT-HSC: In response to regeneration-mediated stress, the CD112low subset exhibits a transient restraint (termed latency) before contributing to hematopoietic reconstitution, while the CD112high subset is primed to respond rapidly. High resolution RNA-seq of the CD112 surface expression spectrum within rare LT-HSC subsets (human umbilical cord blood) demonstrated that more genes are differentially upregulated in the deeper quiescent and less metabolic active subset. Genes enriched in this subset centre around cell adhesion and Rho-GTPase signaling. This is in agreement with the scRNAseq data from human G-CSF mobilized peripheral blood (mPB) generated here that was used as an model of in vivo activation/priming revealing via RNA-velocity and pseudo-time analysis that INKA1high versus PAK4high, CDK6high and CD112high enrichment are either detected early or late in diffusion pseudotime indicative of quiescent versus primed cell status, respectively. RNAseq following INKA1 overexpression in LT-HSC and ST-HSC revealed by GSEA an overall stemness preserving phenotype and particularly in LT-HSC, but not in short-term HSC (ST-HSC), suppression of transcriptional programs linked to activation. Collectively, our data decipher the molecular intricacies underlying HSC heterogeneity and self-renewal regulation and point to latency as an orchestrated physiological response that integrates quiescence control with HSC fate choices to preserve a stem cell reservoir.

  Dataset EGAD00001006541

• Single cell RNA sequencing of cerebrospinal fluid

  Single-cell RNA sequencing of cells isolated from cerebrospinal fluid from 81 individuals with multiple sclerosis (n=33) or other neurological disease (n=48) using 10x Genomics 3’ expression (v2 chemistry).

  Study EGAS00001007478

• RNA sequencing of OM-ALI cultures derived from control and AD individuals exposed to SARS-CoV-2

  RNA sequencing of air-liquid interface (ALI) cultures of olfactory mucosa (OM) cells derived from control (n=3) and AD (n=3) individuals exposed to SARS-CoV-2.

  Study EGAS50000000408

• Nasopharyngeal RNASeq Comparing SARS-CoV-2+ Patients and SARS-CoV-2 Negative Control Subjects

  The goal of this analysis was to compare RNAs enriched in the upper respiratory tract of SARS-CoV-2 patients and SARS-CoV-2 negative controls. RNA-sequencing of RNA isolated from the viral transport medium associated with nasopharyngeal swab samples from SARS-CoV-2+ patients and SARS-COV-2 negative controls.

  Study phs002433

• Genomic characterization of a patient with AGS and CdLS transcriptomic comparison of his monocytes against healthy and disease control samples

  In this study, we describe an extreme genetic phenotype of two simultaneous genetic lesions, leading to broad alterations in immunophenotype and transcriptome. Whole Exome Sequencing and RNA-Sequencing of CD14+ monocytes was performed on the case patient, and RNA-sequencing was also performed on disease (Systemic Lupus Erythematosus) and healthy controls.

  Study EGAS00001007829

• An Organoid Biobank of Rare Human Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping

  We performed whole genome sequencing and RNA-sequencing of neuroendocrine neoplasm. The aim of this study was to provide genetic landscape of neuroendocrine neoplasm, to construct available animal models, and to engineer neuroendocrine neoplasm from normal colon epithelium. The reference genomes used are GRCh37 for whole genome sequencing and GRCh38 for RNA-sequencing.

  Study JGAS000237

• Single nucleus and bulk transcriptomics in prefrontal cortex of individuals with alpha synucleinopathies

  We explore cell-specific changes in gene expression across different α-synucleinopathies. We perform single nucleus RNA sequencing using 10X Genomics, and bulk RNA sequencing from the prefrontal cortex of individuals with alpha synucleinopathies - Parkinson's Disese (PD), monogenic LRRK2 PD, and multiple system atrophy (MSA), together with neurologically healthy controls.

  Study EGAS50000000301

• Gene expression in brain (Schizophrenia) study

  The study included post-mortem brain tissue samples from 68 schizophrenia patients and 44 age and sex matched control subjects. Whole transcriptome poly-A selected paired-end RNA sequencing was performed on tissue from prefrontal cortex and orbitofrontal cortex. RNA expression differences were detected between case and control individuals, focusing both on single genes and pathways.

  Study EGAS00001004199

• 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

• Spatial Transcriptomics of Vaccine Therapy With or Without Cyclophosphamide in Treating Patients Undergoing Chemotherapy and Radiation Therapy for Stage I or Stage II Pancreatic Cancer That Can Be Removed by Surgery

  Pancreatic ductal adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. Here, spatial transcriptomics data were generated from 16 pancreatic cancer patients treated with GVAX, whose tumors presented with induced intratumoral TLS. Resected tumor specimens were embedded in OCT media and freshly frozen. Sections were cut into 6.5 x 6.5 mm dimensions compatible with Visium spatial transcriptomics slides. TLS-positive tumor sections from 14 patients (14 tumor samples in total) and lymph nodes from remaining patients (2 lymph node samples in total) were selected by an expert pathologist for profiling. We used 4 Visium slides and covered the 16 capture areas with sections cut in a cryostat at 10 µm. The fresh frozen Visium protocol was followed according to manufacturer's recommendations (10x Genomics Spatial 3' v1). Tissue permeabilization and library construction was carried out according to the manufacturer's protocols. Permeabilization time was optimized to 30 minutes. The captured tissue sections were permeabilized to allow RNA to be captured onto the slide where it reverse-transcribed to cDNA. The cDNA was then amplified, and sequencing libraries were prepared using the 10x Genomics Visium Spatial Gene Expression Reagent Kit for Library Preparation. The libraries were then sequenced using an Illumina NovaSeq sequencer. The raw data obtained from the sequencing were processed using the SpaceRanger (spaceranger-1.2.0) pipeline for alignment onto the GRCh38-2020-A reference transcriptome quantification of gene expression. Unsupervised learning generated a TLS-specific spatial gene expression signature that significantly associates with improved survival in PDAC patients. These analyses demonstrate TLS-associated intratumoral B cell maturation.

  Study phs003862

• Genomic features of Helicobacter pylori-na��ve diffuse-type gastric cancer.

  Helicobacter pylori (HP) is a major etiologic driver of diffuse-type gastric cancer (DGC). However, improvements in hygiene have led to an increase in the prevalence of HP-na��ve DGC; that is, DGC that occurs independent of HP. Although multiple genomic cohort studies for gastric cancer have been conducted, including studies for DGC, distinctive genomic differences between HP-exposed and HP-na��ve DGC remain largely unknown. Here, we employed exome and RNA sequencing with immunohistochemical analyses to perform binary comparisons between 36 HP-exposed and 27 HP-na��ve DGCs from sporadic, early-stage, and intramucosal or submucosal tumor samples. Among the samples, 33 HP-exposed and 17 HP-na��ve samples had been preserved as fresh-frozen samples. HP infection status was determined using stringent criteria. HP-exposed DGCs exhibited an increased single nucleotide variant burden (HP- exposed DGCs; 1.97 [0.48���7.19] and HP-na��ve DGCs; 1.09 [0.38���3.68] per megabase; p=0.0003) and a higher prevalence of chromosome arm-level aneuploidies (p<0.0001). CDH1 was mutated at similar frequencies in both groups, whereas RHOA���ARHGAP pathway misregulation was exclusive to HP-exposed DGCs (p=0.0167). HP-exposed DGCs showed gains in chromosome arms 8p/8q (p<0.0001), 7p (p=0.0035) and 7q (p=0.0354), and losses in 16q (p=0.0167). Immunohistochemical analyses revealed a higher expression of intestinal markers such as CD10 (p<0.0001) and CDX2 (p=0.0002) and a lower expression of the gastric marker, MUC5AC (p=0.0305) among HP-exposed DGCs. HP-na��ve DGCs, on the other hand, had a purely gastric marker phenotype. This work reveals that HP-na��ve and HP-exposed DGCs develop along different molecular pathways, which provide a basis for early detection strategies in high incidence settings.

  Study JGAS000575

• Wilm's tumor sequencing data

  This study shares DNA and RNA sequencing data from Wilm's tumor patients

  Study EGAS00001005690

• Alveolar Rhabdomyosarcoma sequencing data

  This study shares DNA and RNA sequencing data from alveolar rhadbomyosarcoma patients

  Study EGAS00001005387

• Embryonal Rhabdomyosarcoma sequencing data

  This study shares DNA and RNA sequencing data from embryonal rhadbomyosarcoma patients

  Study EGAS00001005502

• Epithelioid sarcoma sequencing data

  This study shares DNA and RNA sequencing data from Epithelioid sarcoma patients

  Study EGAS00001005983

• Rhabdoid tumor sequencing data

  This study contains sequencing DNA and RNA sequencing data for rhabdoid tumors

  Study EGAS00001006351

• HipSci - Monogenic Diabetes - RNA Sequencing - January 2016

  HipSci - Monogenic Diabetes - RNA Sequencing - January 2016

  Dataset EGAD00001001955

• HipSci - Monogenic Diabetes - RNA Sequencing - April 2015

  HipSci - Monogenic Diabetes - RNA Sequencing - April 2015

  Dataset EGAD00001001953

• Dataset for "Genomic landscape of oral cancers" (Illumina RNA)

  Dataset for "Genomic landscape of oral cancers" (Illumina RNA)

  Dataset EGAD00001004366

• RNA sequencing of uveal melanoma metastases.

  RNA sequencing of uveal melanoma metastases.

  Dataset EGAD00001007912

• SATB1 KO Treg and Teff cells: ATAC-seq

  To study the global effects of SATB1 on gene networks in fully differentiated, ex vivo expanded human CD4 T effector cells and Treg cells, we performed ATAC-seq. We systematically assessed the impact of SATB1 on the chromatin levels in mature human Treg and CD4 T effector cells.

  Study EGAS50000000876

• 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 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

• 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 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