14977 results for "cancer studies using rna-seq"

in 256.63 milliseconds.

• Comprehansive analysis of somatic mutations and genetic variations with whole genome sequencing

  Indetification of stractural variations by using of long read whole genome sequencing data

  Study JGAS000516

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

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

  Dataset EGAD50000000648

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

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

  Dataset EGAD50000001203

• Data from Shea et al Can Research 2025

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

  Dataset EGAD50000001334

• Total NF1 sequence in the patients with neurofaibromatosis type1

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

  Study JGAS000288

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

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

  Dataset EGAD00001003600

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

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

  Study EGAS00001003643

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

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

  Study EGAS00001003678

• Primary_DIPG_expression_profiles

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

  Dataset EGAD00001011080

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

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

  Study EGAS00001006203

• Illumina HiSeqX whole genome sequence data on 58 samples including 54 with known HTT triplet repeat expansions (2 premutation and 52 full expansions)

  Whole genome sequence (WGS) data was generated on 58 samples with validated repeat lengths for the CAG repeat associated with Huntington disease, These samples were sequenced using 2x150bp reads on an Illumina HiSeqX sequencer and the repeat expansions were called using ExpansionHunter to demonstrate the ability to call large repeats from high throughput, WGS data.

  Study EGAS00001002593

• The BEACCON study: tumour sequencing

  This dataset consists of paired-end DNA sequencing (whole exome and targeted-capture) of tumours for the BEACCON study. There are 240 unique samples consisting of 92 matched tumour-germline pairs and 56 unmatched tumours totalling 148 patients. There are 33 paired and 6 unpaired tumours sequenced using the Agilent SureSelect All Human Exon v6 libraries, 1 paired and 8 unpaired tumours sequenced using Agilent SureSelect All Human Exon v7 libraries and 48 paired and 3 unpaired tumours sequenced using Twist Bioscience Comprehensive Human Exome v1 libraries totalling 176 whole exome samples. There are 3 paired and 58 unpaired tumours sequenced using a custom Agilent SureSelectXT library totalling 64 targeted capture samples.

  Dataset EGAD00001009299

• Investigating low frequency variants in CAD/MI cases, controls and pedigrees using whole exome sequencing and custom pulldowns

  The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

  Dataset EGAD00001000400

• ATAC

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

  Dataset EGAD00010001928

• prDLBCL WXS/RNA Data Commitee

  Dac EGAC50000000284

• Targeted resequencing of Cardiomyopathies associated genes

  In this study, we present the results of a custom “pan-cardiomyopathy panel” in a molecular screening of 38 unrelated patients, 16 affected by DCM, 14 by HCM, and 8 by ARVC. The panel was designed using the Design Studio Tool (Illumina, San Diego, CA,USA). Coding regions and intron–exon boundaries of 115 genes, known to be associated with 7 DCM, HCM, and ARVC as well as channelopathies, were selected for targeted gene enrichment. For genes with multiple transcripts, all exons included in transcripts expressed in cardiac muscle were considered in the gene panel design. Total DNA was extracted from peripheral blood samples using the Wizard Genomic DNA Purification Kit (Promega, Mannheim, Germany) according to the manufacturer’s instructions, quantified, and qualitatively checked using NanoDrop 2000c (Thermo Fisher Scientific, Waltham, MA, USA). Custom targeted gene enrichment and DNA library preparation were performed using the Nextera Capture Custom Enrichment kit (Illumina) according to the manufacturer’s instructions. Targeted regions were sequenced using the Illumina MiSeq platform, generating approximately two millions of 150-bp paired-end reads for each sample (Q30 ≥90%).

  Dataset EGAD00001003359

• Mapping and phasing of structural variation in patient genomes using nanopore sequencing

  We whole genome sequence 2 patients with congenital abnormalities and known complex de novo chromosomal rearrangements using the Nanopore MinION. We show how we can detect most previoulsy detected de novo rearrangements as well as uncover a few new ones. Furthermore, we perform genome-wide analyses showing the accuracy of SV detection and of phasing, using long reads. The files uploaded here are the whole genome Nanopore data for each of the two patients used, as well as the corresponding whole genome illumina data, used in our comparisons.

  Study EGAS00001002333

• Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype

  The metabolic profile of dendritic cells (DCs) shapes their phenotype and functions. Carboxylestrase 1 (CES1) enzyme is highly expressed in mononuclear myeloid cells however its exact role in DCs is elusive. We used a CES1 inhibitor (WWL113) and genetic overexpression to explore the role of CES1 in DCs differentiation in inflammatory models. CES1 expression was analyzed during CD14+ monocytes differentiation to DCs (MoDCs) using quantitative PCR. CES1 Inhibitor (WWL113) was applied during MoDCs differentiation. Surface markers, secreted cytokines, lactic acid production, phagocytic and T cell polarization capacity were analyzed. Transcriptomic and metabolic profile were assessed with RNA-sequencing and mass spectrometry. Cellular respiration was assessed with seahorse respirometry. Transgenic mice were used to assess CES1 overexpression in DCs in inflammatory models. CES1 expression peaks early during MoDCs differentiation. Pharmacological inhibition of CES1 led to higher expression of CD209, CD86 and MHCII. WWL113 treated MoDCs secreted higher quantities of IL6, IL8, TNF and IL10 and demonstrated stronger phagocytic ability and higher capacity to polarize Th17 differentiation in autologous DCs-T cells co-culture model. Transcriptomic profiling revealed enrichment of multiple inflammatory and metabolic pathways. Functional metabolic analysis shows impaired maximal mitochondrial respiration capacity, increased lactate production and decreased intracellular amino acids and TCA intermediates. Transgenic human CES1 overexpression in murine DCs generated less inflammatory phenotype and increased resistance to T cell mediated colitis. In conclusion, CES1 inhibition directs DCs differentiation towards more inflammatory phenotype, that shows stronger phagocytic capacity and supports Th17 skewing. This is associated with disrupted mitochondrial respiration and amino acids depletion.

  Study EGAS50000000230

• Transposable Elements in FTLD-TDP and ALS-TDP

  Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease involving the rapid and progressive loss of motor neurons. While a number of inherited mutations have been identified as causing ALS, the vast majority of cases are sporadic with no family history of disease. This has led to the model that ALS may be a complex syndrome with an unknown number of causal molecular pathways. However, nearly all ALS patient tissues display aggregates of the RNA binding protein TDP-43 (TARDBP/TAR DNA-binding protein), and mutations in the gene encoding this protein are known to cause ALS. We show that one of the normal functions of TDP-43 is to bind and regulate retrotransposons, repetitive sequences in the genome that are normally silent, due in part to the function of TDP-43. Furthermore, we demonstrate that many ALS patients with TDP-43 pathology also display de-silencing of retrotransposon RNAs, consistent with a loss of normal TDP-43 function. Those ALS patients that exhibit high levels of retrotransposon expression form a distinct subset of ALS subjects that also show other correlated alterations to the transcriptome. Using unsupervised machine learning algorithms, we identified three distinct molecular subtypes from the whole genomes and transcriptomes of a large cohort of 148 ALS patient samples. The retrotransposon re-activated subset formed 20% of ALS samples; two additional groups displayed signatures of oxidative stress (61%), and glial dysfunction (19%), respectively. Together these results demonstrate that retrotransposon re-activation is common in a subset of ALS patients with TDP-43 pathology.

  Study phs001889

• Non-Coding Autoimmune Risk Variant Defines Role for ICOS in T Peripheral Helper Cell Development

  Our fine-mapping of 76 non-MHC loci associated with risk for rheumatoid arthritis (RA, 11,475 cases, 15,870 controls) has recently identified rs117701653, a non-coding single nucleotide polymorphism (SNP) in the CTLA4/CD28/ICOS locus, as the variant most likely to modulate RA risk within this region, with the minor allele C showing disease protection compared to the major allele A. We found that this SNP exhibits allele-specific protein binding and transcriptional modulation, further supporting its regulatory nature. Here, we aimed to determine whether the functional non-coding variant rs117701653 modulates the expression of genes within the CD28/CTLA4/ICOS locus. To address this question, we employed low-input RNA sequencing using the Illumina SmartSeq2 platform on resting total CD4+ T cells from the blood of 24 healthy subjects (8 AA, 8 AC, 8 CC) recruited based on genotype from the Mass General Brigham biobank. We performed a targeted cis-eQTL mapping analysis for protein coding genes with transcription start sites (TSS) within a 1MB window of SNP rs117701653. These genes included WDR12, NBEAL1, CYP20A1, ABI2, RAPH1, CD28, CTLA4, ICOS, and PARD3B. Surprisingly, allelic variation at rs117701653 correlated strongly with expression of ICOS. This suggests that individuals carrying the protective allele C at rs117701653 express lower levels of ICOS, implicating ICOS as a plausible target gene influenced by this protective allele. The raw sequence data from the 24 healthy individuals are available through dbGAP. Gene expression matrices have been deposited to GEO accession GSE235868.

  Study phs003448

• Structure and evolution of double minutes in diagnosis and relapse brain tumors

  Double minute chromosomes are extrachromosomal circular DNA fragments frequently found in brain tumors. To understand their evolution, we characterized the double minutes in paired diagnosis and relapse tumors from a pediatric high-grade glioma and four adult glioblastoma patients. We determined the full structures of the major double minutes using a novel approach combining multiple types of supporting genomic evidence. Among the double minutes identified in the pediatric tumor, only one carrying EGFR was maintained at high abundance in both samples, whereas two others were resent in only trace amounts at diagnosis but abundant at relapse, and the rest were found either in the relapse sample only or in the diagnosis sample only. For the EGFR-carrying double minutes, we found a secondary somatic deletion in all copies at relapse, after erlotinib treatment, but this was rare at diagnosis, suggesting potential resistance to the EGFR inhibitor. This mutation caused an in-frame RNA transcript to skip exon 16, a novel transcript absent in EST database and in about 700 brain tumors that we reviewed. We observed similar patterns involving longitudinal copy number shift of double minutes in another four pairs (diagnosis / relapse) of adult glioblastoma. Overall, in three of five paired tumor samples, we found that although the same oncogenes were amplified at diagnosis and relapse, they were amplified on different double minutes. Our results suggest that double minutes readily evolve, increasing tumor heterogeneity rapidly. Understanding patterns of double minute evolution can shed light on future therapeutic solutions to brain tumors carrying such variants.

  Study EGAS00001003212

• Molecular Genetics of Heroin Dependence in China

  Our principal goal was to determine the chromosomal locations of genetic variations associated with increased vulnerability to heroin dependence. This goal was attained by identifying specific DNA markers that are genetically linked to heroin dependence. We collected blood and diagnostic information (using a structured diagnostic interview) from 1230 people (sib-pairs) having DSM-IV defined heroin dependence as well as from their parents and other affected and unaffected siblings, when possible. Genotype and clinical data was archived using database software. We conducted a multipoint linkage analysis using the guidelines of Lander and Kruglyak to assert statistical significance, and followed up on regions of interest with a dense set of markers to evaluate candidate genes.

  Study phs001213

• Beyond BRCA deficiency: Clinical and molecular predictors of survival in patients with BRCA-deficient tubo-ovarian high-grade serous carcinoma

  Homologous recombination DNA repair deficient (HRD) tumors account for about 50% of tubo-ovarian high-grade serous carcinomas (HGSC) and are associated with a high response to platinum-based chemotherapy. However, a subset of patients with HRD tumors have unexpected resistance to chemotherapy and experience short survival. Our study compared BRCA-deficient and proficient HGSC among patients with short (<3 years, the lowest quartile of overall survival (OS)) versus longer-term (>3 year OS) to identify prognostic markers and potential therapeutic opportunities. Primary tumors from a cohort of patients with advanced-stage HGSC (n=154) enriched for those with HRD tumors and short survival (n=42) were analyzed using whole-genome sequencing, bulk RNA-sequencing, and DNA methylation profiling. A subset of HRD tumors (n=143) were characterized for immune cell densities by multiplex immunofluorescence. Clinicopathological features were assessed in 1,389 patients with HGSC, including 282 with pathogenic germline BRCA variants (gBRCApv). Findings were validated in two international HGSC cohorts: the Ovarian Tumor Tissue Analysis consortium (n=5,875) and Multisciplinary Ovarian Cancer Outcome Group (n=895). In gBRCApv-carriers, residual disease following surgical cytoreduction was not associated with shorter OS unlike in non-carriers where it was strongly associated. While most patients with gBRCApv had a more favorable OS compared to non-carriers, a survival advantage was not apparent in those with variants located outside of BRCA1 exon 10/23 and BRCA2 exon 11/27. Patient survival correlated with HRD score, such that those with a score ≥63 had significantly longer OS compared to those with HRD scores of 42-63 and <42. While higher HRD scores were associated with better survival outcomes, most gBRCApv carriers with a short survival had tumor HRD scores that exceeded the threshold typically considered predictive of a good response to carboplatin or PARP inhibitors. BRCA2-deficient HGSC with loss of the tumor suppressor NF1 was associated with exceptionally favorable outcome (median OS 17 years), whereas amplification of both PIK3CA and RAD21, was associated with poor outcome in BRCA2-deficient HGSC (median OS 2.9 years). The density of tumor-infiltrating CD8+ PD-1+ T cells was prognostic for OS in gBRCApv-carriers. In summary, rather than simply the presence or absence of a germline BRCA pathological variant influencing patient survival, the co-occurrence of specific somatic gene alterations, the extent of immune cell infiltration, the level of homologous recombination deficiency, and BRCA-variant location may modify clinical outcomes in patients with BRCA-deficient HGSC. Analysis of exceptional outcome patients, in this case gBRCApv-carriers with an atypically short survival, may identify determinants of outcome applicable to the wider HGSC patient population.

  Study EGAS00001008059

• Adaptive long-read and transcriptome sequencing detail a submicroscopic inv(15)(q14q15), generating two fusion transcripts and MEIS2 and NUSAP1 haploinsufficiency

  Study an inversion affecting MEIS2 using ONT adaptive sequencing.

  Study EGAS50000000632

• Transcriptome analysis of Hepatitis B for drug discovery and clinical applications

  We analyzed blood transcriptome of HBV positive untreated patients (men) using the CAGE technology.

  Study JGAS000053

• Targeted sequencing using SPET for Mesothelioma.

  Targeted sequencing using SPET for Mesothelioma.

  Dataset EGAD00001001916

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

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

  Study JGAS000631

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

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

  Study EGAS00001003449

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

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

  Study EGAS00001007117

• Natural Killer Cell Therapies for Hematologic Malignancies

  The "Natural Killer Cell Therapies for Hematologic Malignancies" study is an umbrella repository for data pertaining to multiple related clinical trials that aim to assess NK cell therapies as part of treatment strategies for a range of hematologic malignancies. Here, data from two trials, NCT03068819 and NCT02782546, are presented.Cytokine Induced Memory-like NK Cell Adoptive Therapy for Relapsed AML after Allogeneic Hematopoietic Cell Transplant in Children and Adults (NCT03068819)Pediatric and young adult (YA) patients with acute myeloid leukemia (AML) who relapse after allogeneic hematopoietic cell transplantation (HCT) have extremely poor prognosis. Standard salvage chemotherapy and donor lymphocyte infusions (DLI) have little curative potential. Previous studies showed that natural killer (NK) cells can be stimulated ex vivo with interleukin-12 (IL-12), IL-15, and IL-18 to generate memory-like (ML) NK cells with enhanced anti-leukemia responses. We treated nine pediatric/YA patients with post-HCT relapsed AML with donor ML NK cells on a phase I trial. Patients received fludarabine, cytarabine, and filgrastim followed two weeks later by infusion of DLI and ML NK cells from the original HCT donor. ML NK cells were successfully generated from haploidentical, matched-related and matched-unrelated donors. Following infusion, donor-derived ML NK cells expanded and maintained ML multidimensional mass cytometry phenotype for over 3 months. Furthermore, ML NK cells exhibited persistent functional responses as evidenced by leukemia-triggered IFN-gamma production. Following DLI and ML NK cell adoptive transfer, 4 of 8 evaluable patients achieved complete remission at day 28. Two patients maintained a durable remission for over 3 months with one patient in remission for greater than two years. No significant toxicity was experienced. This study demonstrates that in a compatible immune environment post-HCT, donor ML NK cells robustly expand and persist with potent anti-leukemic activity in the absence of exogenous cytokines. ML NK cells in combination with DLI present a novel immunotherapy platform for AML that has relapsed after allogeneic HCT. This trial was registered at https://www.clinicaltrials.gov/study/NCT03068819.A Phase II Study of Cytokine Induced Memory-like NK Cell Adoptive Therapy after Haploidentical Donor Hematopoietic Cell Transplantation (NCT02782546)Natural killer (NK) cells are innate lymphoid cells that eliminate cancer cells, produce cytokines, and are being investigated as a nascent cellular immunotherapy. Impaired NK cell function, expansion, and persistence remain key challenges for optimal clinical translation. One promising strategy to overcome these challenges is cytokine-induced memory-like (ML) differentiation, whereby NK cells acquire enhanced anti-tumor function following stimulation with IL-12, IL-15, and IL-18. Here, reduced-intensity conditioning (RIC) for HLA-haploidentical hematopoietic cell transplantation (HCT) was augmented with same-donor ML NK cells on Day 7 and 3 weeks of N-803 (IL-15 superagonist) to treat patients with relapsed/refractory acute myeloid leukemia (AML) in the clinical trial (NCT02782546). In 15 patients, donor ML NK cells were well-tolerated and 87% of patients achieved a composite complete response at Day 28, which corresponded with clearing high-risk mutations, including TP53 variants. NK cells were the major blood lymphocytes for two months post-HCT with prolific expansion (1104-fold) over 1-2 weeks. Multidimensional mass cytometry and CITE-seq identified donor ML NK cells as distinct from conventional NK cells and persisting for over two months. ML NK cells expressed CD16, CD57, and high granzyme B and perforin, along with a unique transcription factor profile. ML NK cells differentiated in patients had enhanced ex vivo function compared to conventional NK cells from both patient and healthy donors. Overall, same-donor ML NK cell therapy with 3 weeks of N-803 support safely augmented RIC haplo-HCT for AML, with ML NK cells demonstrating enhanced in vivo persistence and functionality, overcoming barriers in the field.

  Study phs002681

• Effective screening strategy for deafness using a new-genetation sequencing platform: a consecutive analysis

  The diagnosis of the genetic etiology of deafness contributes to the clinical management of patients. We performed the following four genetic tests in three stages for 52 consecutive deafness subjects in one facility. We used the Invade assay and Sanger sequencing for the GJB2 gene or SLC26A4 gene in the first stage test, TaqMan genotyping assay in second stage test, and targeted exon sequencing using the massively parallel DNA sequencing in third stage test. Overall, we identified the genetic cause in 40% (21/52) of patients. The diagnostic rates of the first-, second- and third-stage genetic testing were 17%(9/52), 9%(4/43) and 21% (8/39), respectively. The combination approach using these genetic tests appears to be useful as a diagnostic tool for deafness patients. We recommended that genetic testing for the screening of common mutations in deafness genes using the Invader assay or TaqMan genotyping assay be performed as the initial evaluation. For the remaining undiagnosed cases, targeted exon sequencing using MPS is clinically and economically beneficial. This data set was MPS reads data (fastq) for 39 sensorineural hearing loss patients.

  Study JGAS000032

• A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  We have carried out complete sequencing of the genome of the human male maligant melanoma cell line COLO-829 using the Illumina Genome Analyzer II. We generated a sequencing library with a median insert size of ~200 bp following random fragmentation and gel fractionation of the genomic DNA. We sequenced 75 bases from both ends of these templates to cover the COLO-829 genome to an average depth of more than 40x. We have carried out purity-filtering (PF) to remove mixed reads, where two or more different template molecules are close enough on the surface of the flow-cell to form a mixed or overlapping cluster. No other filtering of the data has been carried out prior to submission. We have also submitted sequence data for a lymphoblastoid control cell line COLO-829BL from the same individual.

  Study EGAS00000000052

• CNS Embryonal tumors

  The dataset represents a total of 58 DNA samples from 16 male and 12 female pediatric patients affected with embryonal central nervous system tumors. The samples were subject to whole genome sequencing, WGS, [48 samples, (representing 12 male and 11 female individuals)] and whole exome sequencing, WES, [10 samples, (representing 4 male and 1 female individuals)]. One tumor tissue sample and one peripheral blood sample were analyzed from each of 26 patients, whereas two tumor tissue samples and one peripheral blood sample were analyzed from two patients. The WGS samples were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument, and the WES samples were sequenced 2x100 bp paired-end on an Illumina HiSeq 2500 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 58 files in the CRAM format (lossless compression) with a total file size of ~8,8 TB. All CRAM files but one, are derived from one sequence run and one sample. P4551_227N_P4552_112N is a CRAM file where 2 sequence runs (P4551_227N and P4552_112N) from peripheral blood samples from the same individual, P019, were aligned into one single CRAM file. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

  Dataset EGAD50000000298

• Immediate Postoperative Minimal Residual Disease Detection with MAESTRO Predicts Recurrence and Survival in Head and Neck Cancer Patients Treated with Surgery

  We selected 24 patients with locally advanced head and neck squamous cell carcinoma (HNSCC) who were surgically treated. MAESTRO, our ultrasensitive, tumor-informed, mutation enrichment sequencing assay, was applied in a pooled format (MAESTRO-Pool) to plasma samples collected from these patients at baseline (pre-op) and postoperatively. We show that detection of circulating tumor DNA (ctDNA) 1 to 9 days after surgery is associated with significantly worse survival. Many plasma samples also had tumor fractions detected below 100 parts-per-million, the detection limit for first-generation commercial assays, highlighting the need for more sensitive ctDNA assays. Here we provide whole genome sequencing of matched tumor biopsy and normal germline DNA from 24 patients that were used to identify somatic single nucleotide variants (SNVs) to be tracked using our MAESTRO-Pool assay.

  Study phs003981

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

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

  Study phs002555

• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• Custom long non-coding RNA capture DAC

  Dac EGAC00001002198

• GLASS-NL RNA-sequencing Study

  Study EGAS00001007551

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

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

  Study phs001448

• The Genetic and Transcriptomic Evolution of Melanoma

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

  Study phs001550

• Whole Exome Sequencing of Uveal Melanoma

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

  Study phs001370

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

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

  Study phs003642

• Chromatin Landscape of BET Inhibitor-Treated CD8+ T-cells from Chronic Lymphocytic Leukemia Patients

  The pan-BET (bromodomain and extra-terminal) inhibitor, OPN-51107 (OPN5) was found to alleviate features of T-cell exhaustion in models of chronic lymphocytic leukemia (CLL). To evaluate if OPN5 treatment could relieve fixed chromatin states associated with terminal T-cell dysfunction, ATAC-sequencing was performed on CLL patient T-cells. Peripheral blood mononuclear cells (PBMCs) from 4 treatment-naïve CLL patients were treated ex vivo with 0.5 μM OPN5 or equivalent vehicle (DMSO) in the presence of T-cell activating stimuli (10 μg/mL anti-CD3 and 5 μg/mL anti-CD28) for 16 hours. Live CD8+ T-cells were then isolated via fluorescence-activated cell sorting, and approximately 100,000 viable CD8+ T-cells were subjected to ATAC-sequencing. Libraries were prepared using the Active Motif ATAC-seq kit and underwent paired-end sequencing (2 x 50 bp, 100 cycles) on an Illumina NovaSeq 6000 SP sequencer. Analysis of this data revealed that OPN5 treatment induces a unique chromatin landscape in CLL patient T-cells that is less like that of terminally exhausted T-cells and more like that of effector and memory T-cells. In particular, OPN5 treatment reduced chromatin accessibility at promoter regions of terminal exhaustion-associated genes (e.g., CD101, CCR5, LAG3, BATF3) and increased chromatin accessibility at promoter regions of genes associated with progenitor T-cell function (e.g., TCF7, IL2, CXCR5, IFNG). Individual raw sequencing (fastq) files and processed bigwig files (aligned to the hg38 human reference genome), as well as bigwig files for grouped OPN5- and vehicle-treated samples (aggregate of all 4 patient samples per treatment group) are available via authorized access request through dbGaP.

  Study phs003613

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

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

  Study EGAS00001006823

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

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

  Study JGAS000844

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

  ChIP-Seq data for 3 monocyte - RPMI_T=24hrs sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002474

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

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs sample(s). 8 run(s), 8 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002388

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

  ChIP-Seq data for 1 conventional dendritic cell sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002310

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

  ChIP-Seq data for 1 unswitched memory B cell sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002282

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

  ChIP-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002494

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

  ChIP-Seq data for 2 monocyte - T=0days sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002491

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

  ChIP-Seq data for 2 monocyte - RPMI_BG_T=1hr sample(s). 6 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002297

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

  ChIP-Seq data for 9 inflammatory macrophage sample(s). 58 run(s), 58 experiment(s), 58 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002515

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

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs_RPMI_T=5days sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002517

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

  ChIP-Seq data for 4 germinal center B cell sample(s). 24 run(s), 22 experiment(s), 22 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002442

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

  ChIP-Seq data for 2 monocyte - RPMI_T=1hr sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002453

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

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002454

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

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MS-275 (20h) sample(s). 5 run(s), 5 experiment(s), 5 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002493

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

  Bisulfite-Seq data for 2 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 29 run(s), 2 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002325

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

  ChIP-Seq data for 4 segmented neutrophil of bone marrow sample(s). 24 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002390

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

  ChIP-Seq data for 3 monocyte - Attached_T=1hr sample(s). 8 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002415

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

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=4hrs sample(s). 8 run(s), 8 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002368

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

  ChIP-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days sample(s). 20 run(s), 20 experiment(s), 20 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002485

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

  ChIP-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002510

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

  ChIP-Seq data for 9 CD14-positive, CD16-negative classical monocyte sample(s). 59 run(s), 55 experiment(s), 55 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000913

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

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

  Dataset EGAD00001004824

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

  Bisulfite-Seq data for 2 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 34 run(s), 3 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002346

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

  ChIP-Seq data for 2 regulatory T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002293

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

  ChIP-Seq data for 3 Activated B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 12 run(s), 12 experiment(s), 12 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002307

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

  ChIP-Seq data for 10 mature neutrophil sample(s). 105 run(s), 86 experiment(s), 86 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002449

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

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002512

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

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002448

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

  ChIP-Seq data for 6 CD38-negative naive B cell sample(s). 20 run(s), 20 experiment(s), 20 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001594

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_T=6days_LPS_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_T=6days_LPS_T=4hrs sample(s). 8 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002495

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

  ChIP-Seq data for 9 CD38-negative naive B cell sample(s). 48 run(s), 44 experiment(s), 44 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002524

• BLUEPRINT release January 2015, ChIP-Seq for CD4-positive, alpha-beta T cell

  ChIP-Seq data for 7 CD4-positive, alpha-beta T cell sample(s). 46 run(s), 45 experiment(s), 45 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001147

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

  ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 11 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001559

• BLUEPRINT release January 2015, ChIP-Seq for endothelial cell of umbilical vein (resting)

  ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 10 run(s), 10 experiment(s), 10 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001183

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

  ChIP-Seq data for 2 monocyte - RPMI_LPS_T=1hr sample(s). 8 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002376

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

  ChIP-Seq data for 7 alternatively activated macrophage sample(s). 50 run(s), 49 experiment(s), 49 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002317

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

  ChIP-Seq data for 3 class switched memory B cell sample(s). 21 run(s), 21 experiment(s), 21 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002430

• BLUEPRINT release August 2014, ChIP-Seq for CD4-positive, alpha-beta T cell

  ChIP-Seq data for 3 CD4-positive, alpha-beta T cell sample(s). 21 run(s), 21 experiment(s), 21 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000925

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

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days_LPS_T=4hrs sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002296

• BLUEPRINT release August 2016, ChIP-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002386

• BLUEPRINT release August 2016, ChIP-Seq for adult endothelial progenitor cell, on genome GRCh38

  ChIP-Seq data for 2 adult endothelial progenitor cell sample(s). 16 run(s), 14 experiment(s), 14 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002487

• BLUEPRINT release August 2015, ChIP-Seq for germinal center B cell, on genome GRCh38

  ChIP-Seq data for 2 germinal center B cell sample(s). 12 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001502

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

  ChIP-Seq data for 9 mature neutrophil sample(s). 48 run(s), 45 experiment(s), 45 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001508

• BLUEPRINT release January 2015, ChIP-Seq for central memory CD4-positive, alpha-beta T cell

  ChIP-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 6 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001144

• BLUEPRINT release January 2015, ChIP-Seq for CD14-positive, CD16-negative classical monocyte

  ChIP-Seq data for 10 CD14-positive, CD16-negative classical monocyte sample(s). 73 run(s), 69 experiment(s), 69 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001179

• BLUEPRINT release August 2016, ChIP-Seq for endothelial cell of umbilical vein (proliferating), on genome GRCh38

  ChIP-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 14 run(s), 14 experiment(s), 14 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002424

• BLUEPRINT release January 2015, ChIP-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  ChIP-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001182

• BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001568

• BLUEPRINT release January 2015, ChIP-Seq for effector memory CD8-positive, alpha-beta T cell

  ChIP-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001127

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

  Bisulfite-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001541

• BLUEPRINT release August 2014, ChIP-Seq for CD8-positive, alpha-beta T cell

  ChIP-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 13 run(s), 13 experiment(s), 13 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000936

• BLUEPRINT release January 2015, ChIP-Seq for CD8-positive, alpha-beta T cell

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 28 run(s), 28 experiment(s), 28 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001154

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

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

  Dataset EGAD00001001487

• BLUEPRINT release August 2015, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 18 run(s), 17 experiment(s), 17 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001511

• BLUEPRINT release August 2015, ChIP-Seq for alternatively activated macrophage, on genome GRCh38

  ChIP-Seq data for 4 alternatively activated macrophage sample(s). 22 run(s), 22 experiment(s), 22 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001514

• BLUEPRINT release August 2015, ChIP-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001584

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

  ChIP-Seq data for 7 inflammatory macrophage sample(s). 36 run(s), 36 experiment(s), 36 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001589

• Tapestri snDNA-seq data along with matched bulk data for validation

  Files from Tapestri snDNA-seq of archival tissue samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients. Matched bulk sequencing (whole-exome, whole-genome, MSK-IMPACT) data are attached for a subset of the patients.

  Dataset EGAD00001009735

• ATAC-Seq/Hi-C/4C-Seq dataset for Malignant rhabdoid study

  Study describing the dynamics of chromatin organization within malignant rhabdoid tumors. This study describes how this chromatin organization changes upon SMARCB1 rescue within patient-derived organoid models from malignant rhabdoid tumors. Identification of a novel super-enhancer of MYC and identification of patient-specific enhancer utilization to activate MYC expression in these tumors.

  Dataset EGAD00001011820

• BLUEPRINT release January 2015, ChIP-Seq for endothelial cell of umbilical vein (proliferating)

  ChIP-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 13 run(s), 13 experiment(s), 13 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001136

• BLUEPRINT release January 2015, ChIP-Seq for cytotoxic CD56-dim natural killer cell

  ChIP-Seq data for 4 cytotoxic CD56-dim natural killer cell sample(s). 16 run(s), 16 experiment(s), 16 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001158

• BLUEPRINT release January 2015, ChIP-Seq for CD38-negative naive B cell

  ChIP-Seq data for 4 CD38-negative naive B cell sample(s). 14 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001207

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

  ChIP-Seq data for 6 naive B cell sample(s). 34 run(s), 28 experiment(s), 28 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001519

• BLUEPRINT release August 2015, ChIP-Seq for adult endothelial progenitor cell, on genome GRCh38

  ChIP-Seq data for 1 adult endothelial progenitor cell sample(s). 8 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001554

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

  ChIP-Seq data for 12 macrophage sample(s). 49 run(s), 49 experiment(s), 49 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001576

• BLUEPRINT release August 2015, ChIP-Seq for segmented neutrophil of bone marrow, on genome GRCh38

  ChIP-Seq data for 4 segmented neutrophil of bone marrow sample(s). 20 run(s), 19 experiment(s), 19 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001588

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - T=10day_RANK_M-CSF, on genome GRCh38

  ChIP-Seq data for 1 monocyte - T=10day_RANK_M-CSF sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002420

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

  ChIP-Seq data for 15 naive B cell sample(s). 67 run(s), 59 experiment(s), 59 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002466

• BLUEPRINT release August 2016, ChIP-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 13 run(s), 13 experiment(s), 13 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002488

• Combining dasatinib and IFN-α in CML – immunomodulatory effects linked to treatment response and adverse events

  We pooled 100,000 cells from the 12 scRNA+TCRab-seq samples from peripheral blood from three time points (n=4, samples at 0, 3, and 12 months) to understand the landscape of immune subsets in CML during the course of dasatinib+IFN-α treatment

  Study EGAS00001005049

• WTCCC case-control study for Tuberculosis

  WTCCC genome-wide case-control association study for Tuberculosis (TB) using the African samples as controls.

  Study EGAS00000000027

• WES-based association study of cefaclor-induced anaphylaxis

  This study investigates the genetic factors associated with cefaclor-induced anaphylaxis using whole-exome sequencing (WES).

  Study EGAS50000001163

• ESGI___Whole_Genome_Sequencing_of_NSPHS_samples

  Whole genome sequencing of sampels from the NSPHS cohort. The samples are sequenced using the Illumina HiSeq X Ten system.

  Study EGAS00001001117

• Longitudinal ctDNA in Uveal Melanoma

  Assess the efficacy of using multi-modal ctDNA analysis to detect relapse in patients with uveal melanoma

  Study EGAS00001006373

• Resuscitation Outcomes Consortium (ROC) Prehospital Resuscitation Using an Impedance Valve and Early Versus Delayed Analysis (PRIMED) (ROC-PRIMED-BioLINCC)

  Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Objective: The purpose of this study was to examine two different treatments during a cardiac arrest that occurs outside of the hospital and whether either or both treatments would increase the number of people who lived to hospital discharge with satisfactory functional status. The first treatment involved using a device called the Impedance Threshold Device (ITD). The other treatment involved the amount of CPR given before the emergency medical services (EMS) providers first looked at the heart rhythm to determine if a shock is needed.Background: Out-of-hospital cardiac arrest is a common and lethal problem with a low survival rate, leading to an estimated 330,000 deaths each year in the United States and Canada. The traditional approach to out-of-hospital cardiac arrest has been to emphasize early analysis of cardiac rhythm, with delivery of defibrillatory shocks, if indicated, as quickly as possible. It has been suggested, however, that many participants may benefit from a period of CPR before the first analysis of rhythm.The impedance threshold device (ITD) is designed to enhance venous return and cardiac output during CPR by increasing the degree of negative intrathoracic pressure. Previous studies have suggested that the use of an ITD during CPR may improve survival rates after cardiac arrest. This effect is achieved by preventing the passive inflow of air into the chest during chest recoil between chest compressions without impeding active ventilation. The ITD has been found to improve hemodynamics, the perfusion of vital organs, and neurologically intact survival in studies in animals. The results of small, short-term clinical trials have suggested that the ITD can increase systolic blood pressure during resuscitation and improve short-term survival rates. Participants: In the ITD study, 4,345 participants were assigned to sham ITD and 4,373 to active ITD, while in the early versus later rhythm analysis, 5,290 participants were assigned to early cardiac rhythm analysis, and 4,643 were assigned to later cardiac rhythm analysis. This study qualified for exception from informed consent required for emergency research.Design: Most participants were enrolled simultaneously in both the early analysis versus later analysis component and the active ITD versus sham ITD component of the trial.The use of an active ITD was compared with that of a sham ITD in participants at 10 ROC sites in the United States and Canada. Participants, investigators, study coordinators, and all care providers were unaware of the treatment assignments. EMS personnel were trained in ITD function, proper use of the ITD, and all aspects of protocol implementation, with an emphasis on the optimal performance of CPR according to local guidelines. The first EMS responders to arrive at the scene of the arrest who were equipped with a randomly assigned ITD (active or sham) attached the device between the ventilation bag and face mask or between the bag and an advanced airway. Responders were encouraged to implement use of the device within 5 minutes after their arrival or as soon as clinically possible. Each of the 10 participating ROC centers was also divided into approximately 20 clusters. All episodes of cardiac arrest in a cluster were randomly assigned to one CPR strategy; after a set period of time, ranging from 3 to 12 months, all episodes in that cluster were then assigned to the other strategy. Participants in the early-analysis group were assigned to receive 30 to 60 seconds of chest compressions and ventilations (sufficient time to place defibrillator electrodes) before electrocardiographic (ECG) analysis, and those in the late-analysis group were assigned to receive 3 minutes of chest compressions and ventilations before ECG analysis. The start and stop times for CPR were recorded by the responders, and the information was supplemented by the recording of defibrillator time. Conclusions: All 10 sites halted enrollment in November 2009 when the data and safety monitoring board recommended termination because interim analysis showed that the findings were not likely to change with continuation of the study. Neither use of the ITD nor the amount of CPR given before cardiac rhythm analysis significantly improved survival with satisfactory function (i.e., a score of ≤3 on the modified Rankin scale) among participants with out-of-hospital cardiac arrest receiving standard CPR. There were also no significant differences in the secondary outcomes, including rates of return of spontaneous circulation on arrival at the emergency department, survival to hospital admission, and survival to hospital discharge.

  Study phs003825

• PEDS-PLAN - Pediatric Precision Laboratory Advanced Neuroblastoma Therapy

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

  Study phs002303

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

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

  Study EGAS50000000999

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

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

  Dataset EGAD00001005307

• Illumina 5'end RNA sequencing

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

  Dataset EGAD00001006838

• RNA data for medulloblastoma samples (ICGC)

  RNA sequencing data for 170 medulloblastoma tumor samples

  Dataset EGAD00001003279

• Small intestinal neuroendocrine tumors

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

  Study EGAS00001003358

• Blood and skin fibroblasts PSA study

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

  Dataset EGAD00001009069

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

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

  Dataset EGAD00001009086

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

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

  Dataset EGAD00001011068

• 3D-GSC_expression_profiles

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

  Dataset EGAD00001011079

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

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

  Dataset EGAD00001011134

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Uzbeks (DNA samples from the Institute of Immunology, Uzbek Academy of Sciences, Tashkent, Uzbekistan; Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology, Tashkent, Uzbekistan)

  Whole genome sequencing of 100 unrelated Uzbeks in order to impute genotypes into PE cases and controls from Uzbekistan and to provide genetic data and infrastructure for future genetic studies in Uzbekistan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology.

  Dataset EGAD00001005466

• H3K4me3, IgG, and Input ChIP-seq in overexpression of pLV Control, CS-FL and CS-ΔEx4 in SW1116 cells.

  none

  Study EGAS00001008121

• University of Illinois at Chicago (UIC) Autism Centers of Excellence (ACE) Exome Sequencing Analysis

  Autism spectrum disorder (ASD) is highly heritable with recent sibling recurrence risk estimates of 19% overall and 26% in males. The heritable phenotype of hyperserotonemia, or elevated levels of platelet serotonin (5HT), in ~35% of people with ASD is a well-established biomarker. The efficacy of drugs like risperidone and potent serotonin transporter inhibitors at treating behaviors related to Insistence on Sameness, along with evidence of the contribution of hyperserotonemia to autism susceptibility collectively support the hypothesis that dysfunction in the 5HT system is a significant etiological target for investigation of the genetic component to autism. ASD genetic architecture is complex; common variants of large effect do not contribute substantially to overall ASD risk, but there are clearly common variants with small effects and rare genetic/genomic variation of larger effect among ASD genetic risk factors. The NIH ARRA Autism Sequencing Consortium, including Dr. Sutcliffe and Dr. Cook among others, has initiated exome sequencing studies to identify more of the rare variants contributing to ASD. Data from our group and others reveal numerous rare de novo and inherited sequence mutations, and the number of de novo and other functional mutations that are found to affect molecules encoding 5HT signaling and its regulation further reinforces our hypothesis that regulation of serotonin levels is important in autism genetic susceptibility. Integrin receptor signaling pathways were prominently featured among identified de novo mutations, thus defining a set of interrelated gene networks that control 5HT signaling. We propose to extend our findings to date by conducting exome sequencing on ACE subjects, for whom we also have 5HT biochemical data, to identify rare variants (including CNVs) in 5HT-related gene networks. In total we propose to have exome sequencing completed on 523 samples. The purpose of the proposed research is two-fold: 1) we will conduct more extensive investigations to determine the support for the hypothesis that genetic variation at genes regulating platelet serotonin levels affect susceptibility to ASD and 2) we will combine the exome sequence data from these studies with sequence data for autism being accumulated in a variety of other research projects to further the goal of identifying and characterizing the genetic component to ASD.

  Study phs000712

• The Atherosclerosis Risk in Communities (ARIC) Study

  The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were reexamined every three years with the first screen (baseline) occurring in 1987-89, the second in 1990-92, the third in 1993-95, and the fourth and last exam was in 1996-98. Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, currently ongoing, these four communities are investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducts community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. ARIC is currently funded through January 31, 2012. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to atherosclerosis and cardiovascular disease through large-scale genome-wide association studies of well-characterized cohorts of adults in four defined populations. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000090