2965 results for "愛の戦士完全破壊2-re-imagination-version-鞭首絞め・電撃・ヘソか"

in 25.70 milliseconds.

• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney’s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women’s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,  Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - RNA-seq

  B-cell prolymphocytic leukemia (B-PLL) is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

  Study EGAS00001003274

• Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - WXS

  B-PLL is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

  Study EGAS00001003275

• Targeting FGFR1 for treatment of soft-tissue sarcoma (H021)

  Purpose: Altered FGFR1 signaling has emerged as therapeutic target in various epithelial malignancies. In contrast, the role of FGFR1 in soft-tissue sarcoma (STS) has not been established. Prompted by the detection and subsequent therapeutic inhibition of amplified FGFR1 in a patient with metastatic leiomyosarcoma, we investigated the oncogenic properties and potential as drug target of FGFR1 in STS.Experimental Design: The frequency of FGFR1 amplification and overexpression, as assessed by fluorescence in situ hybridization, microarray-based comparative genomic hybridization and mRNA expression profiling, SNP array profiling, and RNA sequencing, was determined in three independent patient cohorts. The sensitivity of STS cell lines with or without FGFR1 alterations to genetic and pharmacologic FGFR1 inhibition and the signaling pathways engaged by FGFR1 were investigated using short-term viability assays, long-term colony formation assays, and biochemical analysis.Results: Increased FGFR1 copy number was detected in 74 of 190 (38.9%; Cohort 1), 13 of 79 (16.5%; Cohort 2), and 80 of 254 (31.5%; Cohort 3) patients. FGFR1 overexpression occurred in 16 of 79 (20.2%, Cohort 2) and 39 of 254 (15.4%; Cohort 3) patients. Targeting of FGFR1 by short hairpin RNA-mediated knockdown and different small-molecule inhibitors (PD173074, AZD4547, BGJ398) revealed that the requirement for FGFR1 signaling in STS cells is primarily dictated by FGFR1 expression levels, and identified the MAPK-ERK1/2 axis as critical FGFR1 effector pathway.Conclusion: These data identify FGFR1 as driver gene in multiple STS subtypes and support FGFR1 inhibition, guided by patient selection according to FGFR1 expression and monitoring of MAPK-ERK1/2 signaling, as therapeutic option in this challenging group of diseases.H021

  Study EGAS00001001844

• Genome Instability in Mammary Cells of Pathogenic BRCA1/2 Mutation Carriers

  It remains unknown if inherited germline mutations in the BRCA1 or BRCA2 gene increase the risk of breast and ovarian cancer by elevating mutation rate in mammary cells. Here we show, using a single-cell whole genome sequencing approach, that mammary luminal epithelial cells isolated from tissues obtained from preventive mastectomy surgeries in women with a pathogenic BRCA1/2 germline mutation, exhibit a statistically significant, increased mutation frequency as compared to age-matched controls without genetic risk of breast cancer.

  Study phs002411

• VitGene Generalized Vitiligo Genetics Study-Phase 2

  Generalized vitiligo is an autoimmune disease in which melanocyte loss results in patchy depigmentation of skin and hair. For this third GWAS of generalized vitiligo, SNPs were genotyped in 1,059 generalized vitiligo cases of European-derived white (EUR) ancestry using the Illumina Human OmniExpress BeadChip array. The data were combined with those of Phase 1 and Phase 2 to provide at least 85% power to detect associations with OR > 1.22 at genome-wide significance (P = 5 x 10-8) for MAF > 0.25.

  Study phs000224

• Single-cell RNA sequencing of sorted regulatory T cells

  Single-cell RNA sequencing of flow cytometry enriched CD4+ CD127- CD25+ regulatory T cells from 8 systemic lupus erythematosus patients (SLE_001 to SLE_007, and SLE_009) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform (incl. generation of TCR libraries). Samples from patients SLE_001, SLE_002, SLE_004, SLE_006 were collected and processed on the first day of experiment (Day 1), and samples from patients SLE_003, SLE_005, SLE_007, SLE_009 on the second day of experiment (Day 2). On each day, samples were pooled and distributed to four lanes on the chromium controller. Run ID 245269 and ID 245270 identify samples sequenced on separate flow cells. Provided are raw sequencing files.

  Dataset EGAD50000000663

• Epigenetic memory of SARS-CoV-2 mRNA vaccination in monocyte-derived macrophages

  Immune memory is key to effective antimicrobial responses, but the impact of mRNA vaccines on this process is not fully understood. Our research shows that SARS-CoV-2 mRNA vaccines alter the epigenetic profile of human macrophages, specifically enhancing histone acetylation, which is linked to immune training. Significant epigenetic changes, along with increased cytokine release, require two vaccine doses. However, these effects diminish over time but can be restored with a booster dose six months later, maintaining a strong pro-inflammatory response.

  Study EGAS50000000341

• Longitudinal Transcriptomic Profiling of Endothelial Progenitor Cells in Post-COVID-19 Patients: Insights at 3 and 6-Months Post-SARS-CoV-2 Infection

  Bulk RNA-sequencing analysis of endothelial cells isolated from post-COVID patients at 3 and 6 months post-infection, alongside healthy controls. This study aims to identify differentially expressed genes in endothelial cells from post-COVID patients—at both 3- and 6-month time points—compared to those from healthy individuals. The objective is to uncover upregulated and downregulated pathways potentially associated with long-term consequences of SARS-CoV-2 infection.

  Study EGAS50000000993

• Variability in immune response genes and prediction of severe SARS-CoV-2 infection (INMUNGEN-Cov2 project)

  Genetic factors may contribute to explain the variable clinical response to SARS-CoV-2 infection. To this end we sequenced the DNA of 392 COVID-19 patients from Spain. Whole Exome Sequencing (WES) was performed at two different sequencing centers. Half of the samples were sequenced at a commercial service, NIMGenetics, whereas the other half were sequenced by the EASI-Genomics consortium. Finally, Variant Call Format (VCF) files for each sample was also obtained.

  Study EGAS50000000066

• Mutational spectrum of highly differentiated, fusion-negative rhabdomyosarcoma (set 2).

  Pediatric PAX-FOXO1 fusion-negative rhabdomyosarcoma represents a diverse spectrum of tumors. In this study, the mutational spectrum of 22 fusion-negative rhabdomyosarcomas with high, rhabdomyoma-like levels of differentiation was evaluated using OncoPanel v.2 (OPv2), an Agilent SureSelect custom designed bait set consisting of the coding regions of 504 cancer-relevant genes. Corresponding normal tissue was not available. Discarded normal human skeletal muscle, obtained from 7 donors without tumor history, were also included in the sequencing run.

  Study EGAS00001002771

• Tumorigenic role of Musashi-2 in aggressive mantle cell lymphoma

  SOX11 is overexpressed in the highly aggressive conventional mantle cell lymphoma (MCL) but rarely in the indolent non-nodal MCL subtype. We performed RNA-seq of SOX11+ and SOX11- MCLs to search for SOX11-regulated genes that contributed to MCL clinical evolution, identifying Musashi-2 (MSI2) stem cell-related gene. By performing RNA-seq upon MSI2 knockdown or inhibition in MCL, we identified MSI2 as a potential target to inhibit drug resistance in aggressive MCLs.

  Study EGAS00001006613

• Patient tumour data (RNAseq, WGBS, ChIPseq, WGS)

  Content: 60 GB patient tumours and 4 normal brain samples combined in pairs by region (x2=8 total input samples). RNAseq: 1 lane per sample, total strand-specific rRNA-depleted (normal samples were combined = 2 lanes/samples per brain region). WGBS: 2 lanes per sample (normal samples were combined = 2 lanes/samples per brain region). ChIPseq (histone mark): a subset of 20 GB samples were profiled. For the same modification were multiplexed and sequenced on 4 lanes each (H3K27ac, H3K4me1) or a single lane (all others). WGS: used as matching input control for the 20 ChIPseq samples. Data type and technology: RNA-seq: PE 100bp sequenced on HiSeq2000. WGBS: PE 100bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000. WGS: PE 150bp sequenced on HiSeq X.

  Dataset EGAD00001005492

• Smart-seq 2 single cell sequencing of CD4 and CD8 T cells from the blood and synovial fluid of 4 psoriatic arthritis patients.

  This dataset was used to characterise T cell gene expression and clonality at sites of active inflammation within the joints of psoriatic arthritis (PsA) patients, and to compare these results with T cells from the peripheral blood of those same patients. Freshly sorted CD45RA negative CD3+CD4+ and CD3+CD8+ single cells from four patients were individually flow sorted into 96-well full-skirted plates (Eppendorf) containing 10µL of a 2% Dithiothreitol (DTT, 2M Sigma-Aldrich), RTL lysis buffer (Qiagen) solution. Cell lysates were sealed, mixed and spun down before storing at -80 ºC. Paired-end multiplexed sequencing libraries were prepared following the Smart-seq 2 protocol using the Nextera XT DNA library prep kit (Illumina). A pool of barcoded libraries from four different plates were sequenced across two lanes on the Illumina HiSeq 2500.

  Dataset EGAD00001006342

• scEC&T-seq manuscript data

  This dataset includes all data produced in the study describing "scEC&T-seq", a method for parallel sequencing of extrachromosomal circular DNA and transcriptome in single cells. This dataset includes: - Illumina scEC&T-seq Circle-seq data (scCircle-seq) for a total of 626 single cells / nuclei - bam files - Illumina scEC&T-seq RNA-seq data (scRNA-seq-Illumina) for the same single cells / nuclei - bam files - Nanopore scCircle-seq data for 18 single cells - bam files - Nanopore bulk WGS for 2 cell lines and 2 primary tumor samples - bam files - Illumina bulk WGS for 2 cell lines - bam files - Illumina bulk Circle-seq data from 1 cell line - bam file - Illumina ChIP-seq H3K27me3 data from 1 cell line - fasta files + peaks bed file + coverage bw file

  Dataset EGAD00001010071

• Affymetrix_Exon_Array

  Affymetrix Exon Array dataset

  Dataset EGAD00010000936

• Illumina_1M_SNP_Array

  Illumina 1M SNP Array dataset

  Dataset EGAD00010000939

• CyclomicsSeq_Healthy_Flongle

  Contains Healthy samples sequenced on Flongle flowcells

  Dataset EGAD00001010150

• SC_DDD-G-2

  Batch 2 of unfiltered genotype for DDD Study patients (N=8,286), some of which were used in the neurodevelopmental disorder discovery GWAS (Niemi et al., Nature 2018). Samples were genotyped on the Illumina InfiniumCoreExome Beadchip. QC'd data is available in release EGAD00010001604

  Dataset EGAD00010001600

• Transdisciplinary Studies of Genetic Variation in Colorectal Cancer(CORECT): Axiom GWAS

  This study is part 1 of 2 for Schumacher et al, Nat Commun. 2015 Jul 7;6:7138. Part 1 is the original GWAS data for 9,259 participants on the Affymetrix Axiom platform of the studies listed below in the Inclusion Criteria.

  Study phs001856

• Reconstructed VDJ sequences from Smart-seq2 data

  The dataset contains reconstructed VDJ sequences (fasta files) and accompanying metadata for each cell (csv file) from scRNA-seq data generated with the Smart-seq2 protocol. The VDJ sequences were reconstructed with the computational tool BraCeR using raw fastq files as input. The dataset contains sequences from 355 IgA+ peripheral blood B-lineage cells of two untreated celiac disease patients. The sequences comprise both IgA+ transglutaminase 2-specific and other IgA+ B cells.

  Dataset EGAD50000000341

• WES profiles from the CheckMate-274 clinical trial

  The dataset contains WES profiles of 487 patients from the CA209-274 clinical trial. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. Normalized WES libraries were pooled and sequenced on Illumina NovaSeq 6000 at a plex level appropriate to the coverage of tumor: 2 × 100 bp PE 100 M reads, germline: 2 × 100 bp PE 25 M reads.

  Dataset EGAD50000000792

• ICARUS-BREAST01-ExomeSeq

  Efficacy, safety and biomarker analysis of ICARUS-BREAST01: a phase 2 Study of Patritumab Deruxtecan in patients with HR+/HER2- advanced breast cancer. Whole-exome sequencing (WES) is available for 43 tumor samples and 43 blood samples collected at entry into the trial.

  Study EGAS50000000542

• Whole exome sequencing of trio with primary immunodeficiency (IL2RB)

  A novel homozygous mutation in human IL2RB results in decreased IL-2RB protein expression and dysregulated IL-2/15 signaling. This hypomorphic mutation leads to decreased regulatory T cell frequency and abnormal NK cell compartment, with clinical manifestations of autoimmunity and susceptibility to CMV.

  Study EGAS00001003599

• Whole exome sequencing of Finnish hereditary breast cancer families

  A remarkable proportion of factors causing genetic predisposition to breast cancer (BC) are unknown in non-BRCA1/2 families. Exome sequencing was performed for 13 high-risk Finnish hereditary breast and/or ovarian cancer (HBOC) families to detect variants contributing to BC susceptibility

  Study EGAS00001001835

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

  ChIP-Seq data for 2 osteoclast sample(s). 17 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 EGAD00001002391

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

  Bisulfite-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 30 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 EGAD00001002383

• BLUEPRINT release August 2016, Bisulfite-Seq for effector memory CD4-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 2 effector memory CD4-positive, alpha-beta T cell 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 EGAD00001002367

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

  Bisulfite-Seq data for 2 central memory CD8-positive, alpha-beta T cell sample(s). 36 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 EGAD00001002486

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC2392, on genome GRCh38

  ChIP-Seq data for 2 Acute Promyelocytic Leukemia - MC2392 sample(s). 14 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 EGAD00001002406

• Raw RNA-seq data for clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint. This dataset includes the raw RNA-seq data.

  Dataset EGAD00001006205

• BLUEPRINT release August 2016, Bisulfite-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  Bisulfite-Seq data for 2 mesenchymal stem cell of the bone marrow sample(s). 39 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002519

• Whole Genome sequencing of colorectal cancer patients (SG-BULK-2)

  Whole Genome sequencing of colorectal cancer patients (SG-BULK-2)

  Dataset EGAD00001008574

• BLUEPRINT release August 2016, Bisulfite-Seq for central memory CD4-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 2 central memory CD4-positive, alpha-beta T cell sample(s). 41 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 EGAD00001002364

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

  Bisulfite-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 35 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002294

• BLUEPRINT release August 2016, Bisulfite-Seq for precursor lymphocyte of B lineage, on genome GRCh38

  Bisulfite-Seq data for 1 precursor lymphocyte of B lineage sample(s). 11 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002291

• Processed RNA-seq data for clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint. This dataset includes the TPM and raw counts tables.

  Dataset EGAD00001006199

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

  ChIP-Seq data for 2 erythroblast 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 EGAD00001002377

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

  ChIP-Seq data for 2 monocyte - RPMI_LPS_T=4hrs 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 EGAD00001002399

• Papua New Guinean Genome Altitude Project Dataset 2

  The PGAP dataset 2 includes 82 whole genome sequences for Papua New Guinean individuals sampled in Daru (N=1), Port Moresby (N=64) and Mount Wilhelm (N=17). DNA was extracted from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer. The PGAP dataset provides Fastq, mapped cram files (GRCh38) and phenotype measurements.

  Dataset EGAD00001010142

• BLUEPRINT September 2016, ChIPmentation Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38

  ChIPmentation data for 2 sample(s) Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38. 12 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002935

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

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

  Dataset EGAD00001001470

• BLUEPRINT September 2016, ChIPmentation for memory B cell from venous blood, on Genome GRCh38

  ChIPmentation data for 2 sample(s) for memory B cell from venous blood, on Genome GRCh38. 6 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002923

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

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

  Dataset EGAD00001001574

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

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

  Dataset EGAD00001001168

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

  ChIP-Seq data for 2 mature eosinophil 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 EGAD00001001539

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

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

  Dataset EGAD00001001580

• BLUEPRINT September 2016, ChIPmentation for conventional dendritic cell from cord blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 4 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002940

• BLUEPRINT September 2016, ChIPmentation for regulatory T cell from venous blood, on Genome GRCh38

  ChIPmentation data for 2 sample(s) for regulatory T cell from venous blood, on Genome GRCh38. 14 run(s), 9 experiment(s), 9 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002942

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

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

  Dataset EGAD00001001592

• Using RNA-sequencing to characterize the resistance to lirafugratinib

  In addition to Exome-sequencing, we used RNA-sequencing to also characterize resistance to lirafugratinib with whole exome sequencing in patients with FGFR2-driven cancers, treated in the phase 1/2 ReFocus trial (NCT04526106) and enrolled in the UNLOCK program at Gustave Roussy

  Study EGAS50000001370

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

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

  Dataset EGAD00001002477

• Mtb infected and uninfected neutrophils after 1 and 6 hrs

  Fastq.gz files for mRNA sequenced from Mtb infected and uninfected neutrophils after 1 and 6 hrs. Samples were sequenced in 2 batched as indicated per experiment. Batch 1 was SE unstranded, 100bp on an Illumina HiSeq4000 sequencer and batch 2 unstranded, 150bp paired-end on an Illumina NovaSeq6000 sequencer. Phenotypic data for the samples is also included.

  Dataset EGAD00001010893

• Hi-C NTERA-2

  TGCT - GWAS loci Hi-C data

  Dataset EGAD00010001249

• RAGE engagement by SARS-CoV-2 enables monocyte infection and underlies COVID-19 severity

  Study EGAS00001007529

• RFX6-mediated dysregulation defines human β cell dysfunction in early type 2 diabetes

  Study EGAS00001006273

• CyclomicsSeq_PREDICT_R10

  Contains PREDICT samples sequenced on R10 flowcells

  Dataset EGAD00001010153

• Sequencing of rare human histiocytic tumour

  Sequencing of rare human histiocytic tumour

  Dataset EGAD00001002184

• TRAIP patients

  BAM files for two WES TRAIP patients

  Dataset EGAD00001001633

• Therapeutic Targeting of ATR Yields Durable Regressions in High Replication Stress Tumors

  Patients with relapsed or recurrent small cell lung cancer or extra-pulmonary small cell cancers were enrolled on an investigator-initiated, single-arm, phase 2 trial (NCT02487095) combining an ATR inhibitor M6620 (VX-970, berzosertib) administered at 210 mg/m2 intravenously over 60 minutes on day 2 and day 5, and topotecan 1.25 mg/m2 intravenously over 30 minutes every 23 hours on days 1 through 5, with a support of pegfilgrastim 6mg subcutaneously on day 6 in 21-day cycles. Tumor samples were collected either just before starting the treatment or before starting treatment prior to be enrolled in the trial. Whole exome and RNA were sequenced to evaluate genomic and transcriptomic characteristics associated with the response to the combination treatment.

  Study phs002327

• Whole exome sequencing in multiplex cleft families from a consortium

  Building upon our previous linkage and association studies, we will use whole exome sequencing studies of second and third degree affected relatives drawn from multiplex families. Our specific aims are: 1) To conduct whole exome sequencing on affected members (2° and 3° relatives) drawn from multiplex cleft families from a consortium to identify novel genes causing non-syndromic oral clefts; 2) To confirm and test the role of rare variants in these novel genes through confirmatory Sanger sequencing, plus linkage information using additional members available in these multiplex families. This whole exome sequencing approach will combine evidence from linkage studies and large scale sequencing to identify novel genes causing oral clefts in multiplex cleft families.

  Study phs000459

• Multidimensional and Longitudinal Immune Profiling of Sepsis in Uganda

  We conducted a prospective, observational cohort study of adults (RESERVE-U-2-TOR) admitted to Tororo General Hospital in eastern Uganda with severe, undifferentiated infection (i.e., suspected sepsis). Briefly, whole-blood samples were collected in PAXgene blood RNA tubes (PreAnalytiX, Qiagen, Germantown, MD, USA), from which RNA was extracted using PAXgene Blood RNA Kits (cat. no. 762164) (Qiagen). Sequencing libraries were constructed with the NEBNext Ultra II RNA Library Preparation Kit for Illumina, after which libraries were multiplexed and sequenced on the Illumina NovaSeq X Plus platform (Illumina, Inc, San Diego, CA). Data from this study available through dbGaP include raw RNA-Seq data generated from whole-blood samples collected upon RESERVE-U-2-TOR study enrollment (N=274).

  Study phs003914

• The acute effects of morning bright light on the human white adipose tissue transcriptome: exploratory post hoc analysis

  The circadian rhythm of the central brain clock in the suprachiasmatic nucleus (SCN) is synchronized by light. White adipose tissue (WAT) is one of the metabolic endocrine organs containing a molecular clock, and it is synchronized by the SCN; excess WAT is a risk factor for health issues including type 2 diabetes mellitus (DM2). We hypothesized that bright-light exposure would affect the human WAT transcriptome. Therefore, we analyzed WAT biopsies from two previously performed randomized cross-over trials (trial 1: lean healthy men, and trial 2: men with obesity and DM2). RNA sequencing results showed major group differences between men with obesity and DM2 and lean healthy men, as well as a differential effect of bright light exposure.

  Study EGAS50000001206

• single-cell RNA-seq Case-Control study of children progressing to Type1 diabetes

  Single-cell RNA sequencing was carried out on four selected PBMC samples of Finnish children at risk of developing Type 1 diabetes and their gender age and HLA matched control children using 10X genomic platform. All four Case children were positive for multiple islet specific autoantibodies and two of them also progressed to clinical disease during the follow up whereas the control children remain negative for all autoantibodies. Age at seroconversion for Case 2, 3, 5, and 9 children is 12, 18, 24, and 18 months, respectively. Age at sampling, in months, for the pairs was as follows (Case/Control): pair 2:24/24; pair 3: 12/18; pair 5: 12/12; pair 9:24/18.

  Study EGAS00001004070

• EGAD00010000130

  Cerebellar ataxia, mental retardation, and disequilibrium syndrome (CAMRQ) samples

  Dataset EGAD00010000130

• DNA sequencing of samples from normal tissue of colon biopsies

  Dataset EGAD00001000642

• DNA sequencing of samples from tumoural tissue of colon biopsies

  Dataset EGAD00001000643

• SMARCA4/2 loss inhibits chemotherapy-induced apoptosis by restricting IP3R3-mediated Ca2+ flux to mitochondria

  Study EGAS00001005448

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Buccal

  Targeted NanoSeq in buccal epithelium obtained longitudinally from a number of donors. A custom-designed panel of ~200 genes will be used to achieve high depth coverage (aiming for ~1000X at panel sites).As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 55 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015618

• Somatic mutation and selection at epidemiological scale - TwinsUK_ExomeNanoSeq_Buccal

  Exome NanoSeq in buccal swab samples obtained from patients with a wide range of clinical phenotypes. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015620

• RNA sequencing data for primary and recurrent ovarian granulosa cell tumors

  RNA sequencing dataset for primary and recurrent ovarian granulosa cell tumors consists of 24 .bam files with aligned reads, including 8 primary and 16 recurrent tumors. Total RNA was extracted from cryopreserved tissue of adult-type granulosa cell tumor samples. Libraries were prepared from cDNA using the NuGEN Ovation Ultralow Library System V2 (San Carlos, CA). Paired-end bulk RNA sequencing was performed on the Illumina HiSeq 2000 platform. RNA sequencing reads were aligned to the hg19/GRCh37 reference human genome using the STAR software (version 2.6.0b) with default parameters. Samples description: GCT001 Adult-type Granulosa Cell Tumor: recurrent tumor GCT002 Adult-type Granulosa Cell Tumor: primary tumor GCT003 Adult-type Granulosa Cell Tumor: recurrent tumor GCT004 Adult-type Granulosa Cell Tumor: primary tumor GCT005 Adult-type Granulosa Cell Tumor: recurrent tumor GCT006 Adult-type Granulosa Cell Tumor: recurrent tumor GCT007 Adult-type Granulosa Cell Tumor: primary tumor GCT008 Adult-type Granulosa Cell Tumor: recurrent tumor GCT009 Adult-type Granulosa Cell Tumor: recurrent tumor GCT010 Adult-type Granulosa Cell Tumor: recurrent tumor GCT011 Adult-type Granulosa Cell Tumor: primary tumor GCT012 Adult-type Granulosa Cell Tumor: recurrent tumor GCT013 Adult-type Granulosa Cell Tumor: recurrent tumor GCT014 Adult-type Granulosa Cell Tumor: recurrent tumor GCT015 Adult-type Granulosa Cell Tumor: recurrent tumor GCT016 Adult-type Granulosa Cell Tumor: recurrent tumor GCT017 Adult-type Granulosa Cell Tumor: recurrent tumor GCT018 Adult-type Granulosa Cell Tumor: primary tumor GCT019 Adult-type Granulosa Cell Tumor: recurrent tumor GCT020 Adult-type Granulosa Cell Tumor: primary tumor GCT021 Adult-type Granulosa Cell Tumor: primary tumor GCT022 Adult-type Granulosa Cell Tumor: recurrent tumor GCT023 Adult-type Granulosa Cell Tumor: recurrent tumor GCT024 Adult-type Granulosa Cell Tumor: primary tumor

  Dataset EGAD00001009108

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Blood

  Utilising Targeted NanoSeq, we hope to explore the driver landscape in unprecedented detail in donors from TwinsUK. These donors have paired buccal swabs and data from this will help contextualise that work. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015619

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedEMSeq_Buccal

  Development of a targeted methylation assay to determine the cell-type composition of a sample. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015622

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedEMSeq_Blood

  Development of a targeted methylation assay to determine the cell-type composition of a sample. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015623

• The Role of CTCF in the Organization of the Centromeric 11p15 Imprinted Domain Interactome

  Beckwith-Wiedemann Syndrome (BWS) is the most common human imprinting disorder and comprises a spectrum of overgrowth phenotypes. While approximately 35% of BWS cases are caused by isolated loss of methylation (LOM) at the human imprinting center 2 (IC2) on chromosome 11p15, only around 5% of patients develop BWS due to structural alterations to the IC2 domain. In this study, we identify a BWS-causing 7.6 kB familial deletion within the IC2 domain by performing Whole Genome Sequencing (WGS) on patient-derived human fibroblasts. Using a chromatin conformation capture technique, Capture C, on 3 control fibroblast samples, 3 BWS LOM fibroblast samples, and the single familial deletion sample, we investigate how the domain interactome changes in BWS patients. We find that high-strength interactions occur within the IC2 domain between the 5’ end of KCNQ1, KCNQ1 intron 2, and the 5’ end of CDKN1C in the control profile that are largely abrogated in the BWS samples, but some lower frequency contacts between the imprinting control region (ICR), KCNQ1 intron 2, and the 5’ end of CDKN1C are unaffected. We conclude that the strong KCNQ1-CDKN1C interactions are important in maintaining the domain imprint.

  Study phs002408

• W115 Deep Sequencing

  Dataset EGAD00001000779

• Whole-Genome Bisulfite Sequencing of a paired initial and recurrent glioma

  Dataset EGAD00001001616

• Recurrent adeno-associated virus 2-related insertional mutagenesis in human hepatocellular carcinomas

  Dataset EGAD00001001423

• SF6420

  Oligodendroglioma (WHO gr. 2)

  Dataset EGAD00001008306

• SF7233

  Astrocytoma (WHO gr. 2)

  Dataset EGAD00001008305

• SF4007

  Oligodendroglioma (WHO gr. 2

  Dataset EGAD00001008300

• Metastatic Prostate Follow Up 2

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000989

• CLUC complete genomics dataset

  Complete genomics data for VCaP and PC346c.

  Dataset EGAD00001002069

• DATA FILES FOR PCGP Dyer_iPSC WGS

  DATA FILES FOR PCGP Dyer_iPSC WGS

  Dataset EGAD00001001415

• Low Coverage Sequencing of rare human histiocytic tumour

  Sequencing of rare human histiocytic tumour

  Dataset EGAD00001002199

• SF10619

  Oligodendroglioma (WHO gr. 2

  Dataset EGAD00001008299

• SF6420

  Oligodendroglioma (WHO gr. 2)

  Dataset EGAD00001008308

• Lactobacillus rhamnosus GG ATCC (LGG) as an immune adjuvant for influenza vaccination in the elderly

  Double blind Randomized Controlled trial to evaluate the safety of Lactobacillus rhamnosus GG ATCC 53103 (LGG) vs placebo in elderly receiving Trivalent Inactivated Influenza Vaccine (TIV) (study 1) or Double blind Randomized Controlled trial to evaluate the safety of Lactobacillus rhamnosus GG ATCC 53103 (LGG) vs. placebo in elderly subjects receiving Live Attenuated Influenza vaccine (LAIV) (study 2). Healthy elderly volunteers, ages 65-80 were enrolled as outpatients in two clinical studies in which they received the TIV vaccine (study 1, n=28) or the LAIV vaccine (study 2, n=30). In each of the 2 studies, subjects were randomized to receive either LGG capsules containing 1 x 1010 CFU, twice daily for 28 days, or matching placebo capsules twice daily for the same period of time. The study subjects completed a daily diary, telephone calls, and study visits at the Massachusetts General Hospital Clinical Research Centers at baseline, days 21, 28 and 56 and month 5 for the TIV study and baseline, days 21, 28, and 56 for the LAIV study. During each visit, the subject diary, interim history, potential adverse effects and concomitant medications were reviewed and vital signs and a physical examination were performed. Routine blood tests were obtained to monitor for safety during visits and nasopharyngeal and stool samples were collected for microbiome analysis. Volunteers in both studies who were interested in participating in the effect of LGG probiotic on the Human whole Blood Transcriptome substudy also had blood drawn for DNA and RNA extraction, after signing the substudy consent form. The main objectives of the TIV and LAIV studies were to assess the safety and tolerability of 2 x 1010 CFU LGG administered orally to elderly subjects for 28 days after administration of TIV (study 1) or LAIV (study 2). Secondary objectives were to evaluate the richness and microbial diversity in nasopharyngeal and stool specimens using pyrosequencing, and to compare cytokine production in response to bacterial stimulation by following the kinetics of mRNA expression of pro and anti-inflammatory genes and different signaling pathways, in relation to changes in stool Bifidobacterium and Lactobacillus spp. The studies were reviewed and approved by the Partners Human Research Committee (TIV study IRB # 2010p001694 and LAIV study IRB # 2011p002849) and were registered at ClinicalTrials.gov (NCT01368029 and NCT01545349, respectively).

  Study phs000981

• RNA-seq of CML074 Tumor tissue; Timpepoint 1

  Dataset EGAD00001001259

• MT alignment

  Alignement including 83 MT AA sequences and 2 reference sequences, rCRS and RSRS

  Dataset EGAD00010001574

• Patient WGS for #198

  Whole genome sequencing of patient tumour and blood

  Dataset EGAD50000000217

• Broad Utility of Ultrasensitive Analysis of ctDNA Dynamics Across Solid Tumors Treated with Immunotherapy

  https://vhio.net/privacy-policy-2/

  Dac EGAC50000000723

• SF7003

  Oligodendroglioma (WHO gr. 2)

  Dataset EGAD00001008297

• BiSeqS

  Runs that contain data for the sensitivity and specificity experiments for BiSeqS.

  Dataset EGAD00001003323

• HCA Organoids | Colon - Cancer, Nanopore Sequencing Data

  Nanopore Sequencing Data

  Dataset EGAD00001015536

• Myelodysplastic cells in patients re-program mesenchymal stromal cells to establish a transplantable stem cell-niche disease unit.

  Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid neoplasms with defects in hematopoietic stem/progenitor cells (HSPCs) and possibly the HSPC niche. Here we show that patient-derived mesenchymal stromal cells (MDS MSCs) display a disturbed differentiation program and are essential for the propagation of MDS-initiating lin-CD34+CD38- stem cells in orthotopic xenografts. Overproduction of niche factors such as N-Cadherin, IGFBP2, VEGFA and LIF is associated with the ability of MDS MSCs to enhance MDS expansion. These factors represent putative therapeutic targets to disrupt critical hematopoietic-stromal interactions in MDS. Finally, healthy MSCs adopt "MDS-MSC like" molecular features when exposed to hematopoietic MDS cells, indicative of an instructive remodeling of their microenvironment. This patient-derived xenograft model therefore provides functional and molecular evidence that MDS is a complex disease involving both the hematopoietic and stromal compartments. The resulting deregulated expression of niche factors may well also be a feature of other hematopoietic malignancies.

  Study EGAS00001000716

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

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

  Study phs003294

• Molecular Epidemiology of Colorectal Cancer (MECC) Metastasis Study: A Germline Variant on Chromosome 4q31.1 Associates with Susceptibility to Developing Colon Cancer Metastasis

  This study compared Ashkenazi Jewish individuals with Stage IV metastatic colon cancer to those with non-metastatic Stage I or II colon cancers. A genome-wide association study, using a 2-stage design, identified a significant association with rs60745952.

  Study phs001045

• Gene expression matrix for Smart-seq2 data of peripheral blood B cells

  The dataset contains scRNA-seq gene expression matrix (csv file) and metadata (csv file) after quality control filtering for data generated with the Smart-seq2 protocol. Transcript expression was quantified with Salmon v0.11.3 using cDNA sequences from GRCh38.94 and k-mer length 25, and was aggregated to gene level and transcript-length-corrected using tximport v1.8.0. The dataset comprises IgA+ transglutaminase 2-specific and other IgA+ B cells from the peripheral blood of 355 cells from two untreated celiac disease patients.

  Dataset EGAD50000000338

• WES for CNV-verified CTCs enriched by high-throughout microfluidic device from entire cancer patient leukopak

  WES analysis (illumina platform, PE150, 100x coverage) was performed on a pool of copy number variation (CNV)-verified CTCs that were enriched using high-throughout microfluidic device from entire leukopak from patients with metastatic prostate cancer (GU-1 and GU-2).

  Study EGAS50000000724