13886 results for "Buy fc coins Buyfc26coins.com is EA Sports official for FC 26 coins I received very good service today..GnKh"

in 31.15 milliseconds.

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities WGS

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006865

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities RNA-Seq

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006866

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities DNA-Methylation

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006881

• Utlizing the RA signature to predict response to TNFi

  This study involves bulk RNA-seq analyses of blood cells from patients with rheumatoid arthritis who have had an inadequate response to methotrexate, collected before and 12 weeks after effective treatment with either etanercept or adalimumab. Peripheral blood mononuclear cells were stimulated with anti-CD3 for 24 hours and sorted into CD4+, CD19+, and CD4-CD19- (DN) populations for bulk RNA-seq.

  Study phs002562

• ICARUS-LUNG01 dataset

  A total of 46 frozen tumor biopsies underwent WES analysis, while 41 blood samples were used as germline controls.Tumor samples qualified for whole exome sequencing (WES) if they contained ≥10% tumor cells. For bulk RNA-seq, 20 paired baseline and on-treatment frozen tumor biopsies were analyzed. Tumor samples qualified if they contained ≥30% tumor cells. For GeoMx spatial transcriptomic study we used 7 patients from the ICARUS LUNG01 trial focusing on tumour and immune cell compartments. We selected 7 paired baseline and on-treatment patient samples for analysis. We selected up to 4 regions of interest (ROI) per sample tissue. We identified tumour and immune cell areas of illumination (AOI) using CK and CD45 antibodies respectively

  Dataset EGAD50000001014

• The landscape of somatic mutations in epigenetic regulators across 1000 pediatric cancer genomes

  To define the frequency and pattern of somatic mutations in epigenetic regulators in pediatric cancer, we sequenced 633 genes, encoding the majority of proteins involved in patterning the epigenome, in 1000 pediatric tumors spanning 21 different cancer subtypes. This analysis establishes an epigenetic landscape of pediatric cancer, which expands the knowledge for potential therapeutic targets and for developing personalized therapy.

  Study EGAS00001000449

• Subclonal evolution of four ER+ breast cancers determined by WGS and scRNA-Seq

  We analyzed the subclonal evolution of four ER+ breast cancers over 2-15 years using whole-genome sequencing (WGS) and single-cell RNA-Seq (scRNA-Seq). For each patient we analyzed 2-6 cancer samples, generally metastatic pleural effusions or ascites, by WGS, along with germline DNA. Two of the samples per patient were selected for single-cell RNA-Seq.

  Study EGAS00001002436

• Ancient nuclear genomes enable repatriation of Indigenous human remains

  For many decades Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return of their ancient people. By sequencing ten ancient nuclear genomes of Aboriginal Australians and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1,540 yr BP) of known provenance we demonstrate the feasibility of successfully identifying the geographic origins of unprovenanced ancestral remains using genomic methods.

  Study EGAS00001003359

• Test_of_PCR_library_method_on_whole_genmoe_samples

  We will sequence 2 whole genome pairs which have had the libraries prepared with a PCR step. The resulting sequence will be compared to teh same samples which have had sequence obtain using a no_PCR library method. the sequence obtained in this experiment may or may not be used in conjunction with the other sequence obtain for these samples in the search for novel cancer mutations.

  Study EGAS00001000214

• November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001007529

• HV31 - Read identifier list for local CCS, CLR, ONT and MGI reads

  This file contains read identifiers for local CCS, CLR, ONT and MGI reads for each of the eight selected genomic regions (HLA, KIR, IGH, IGK, IGL, TRA, TRD, andTRG). We extracted these reads by aligning whole-genome sequencing data to a draft whole-genome de novo assembly, and selecting reads that map to contigs representing each region. These reads were involved in the polishing and validation of the HV31 assembly. Please refer to the relevant manuscript (https://doi.org/10.1101/2021.02.03.429586) for additional details. Read identifiers are stored in JSON format. Along with the full FASTQ files, this file enables convenient re-analysis of the HV31 sequencing data in the eight selected regions.

  Dataset EGAD00001007761

• A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

  Dataset EGAD00001015535

• Chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from immune cells for healthy young and healthy old subjects

  Dataset consisting of: (1) N=234 genome-wide chromatin accessibility (ATAC-seq) profiles for distinct N=21 healthy old and N=28 healthy young subjects. ATAC-seq biological samples provided for the following tissues: PBMC (N=24), CD14+ monocytes (N=18), CD8+ memory T cells (N=7), CD8+ naive T cells (N=7), CD4+ memory T cells (N=7), CD4+ naive T cells (N=7), and naive B cells (N=7). (2) N=39 genome-wide transcription (RNA-seq) data for distinct N=15 healthy old and N=24 healthy young subjects' PBMCs.

  Dataset EGAD00001003602

• Genome-wide Association Study of Myasthenia Gravis

  The purpose of this project was to conduct a genome-wide associate study to search for the genetic factors that predispose to myasthenia gravis. The rationale for this study lies in the fact that, although the immunological and physiological processes affecting the neuromuscular junctions of myasthenia gravis patients are well understood, the spectrum of genetic factors that predispose to myasthenia gravis and influence its disease manifestations are not well known. Identification of the myasthenia gravis-related genes will shed light on the fundamental cellular events underlying myasthenia gravis, and will provide focus for research aimed at developing therapies that alter the natural course of the disease. A consortium of fourteen institutions in North America collected DNA samples from 1028 people diagnosed with autoimmune myasthenia gravis. Relevant clinical data have been collected for each patient, including age of onset, severity of disease, response to drug therapy, personal and family history of other autoimmune diseases. Genotyping of the case cohort was performed in the Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD. Genotyping of the case cohort was performed using the HumanOmniExpress-12v1_C SNP array manufactured by Illumina Inc. For the control cohort, we downloaded genotype data from dbGAP (accession phs000196.v2.p1) for 1,998 US neurologically normal individuals. The control cohort had been previously genotyped at the Center for Inherited Disease Research at Johns Hopkins University on HumanOmni1-Quad version 1.0B beadchips (Illumina) as part of the NeuroGenetics Research Consortium GWAS of Parkinson's disease. Analyses were confined to the 677,673 autosomal SNPs that were common to both chips. Of the 1028 samples which were genotyped, 21 samples were excluded due to mismatched genders, 9 were excluded due to low genotype call rate, 5 samples were excluded as duplicates, and 25 samples were excluded as ethnic outliers. The remaining 972 samples were used in analysis.

  Study phs000726

• OurHealth - Cardiovascular Disease in South Asians

  The OurHealth Study aims to build a biobank comprised of South Asian samples from participants residing in the United States. Primary objectives are to (1) identify genetic and non-genetic drivers of cardiometabolic disease in South Asians, (2) engage participants and researchers in scientific advances and research opportunities to accelerate discovery, and (3) assess the impact of returning polygenic risk scores for cardiovascular-related health conditions. Participants use a web-based platform to complete electronic informed consent, and contribute data via (1) online health surveys, (2) mailed saliva biospecimens for sequencing, and (3) optional electronic health record sharing. Surveys capture medical history, medication data, lifestyle factors, family history, mental health history, and detailed information about cultural and ancestral background. Biospecimens, procured via saliva self-collection kits, undergo DNA isolation and are sequenced using the "blended genome exome" (BGE) method, which consists of sequencing on the NovaSeqX 10B Flowcell followed by Dynamic Read Analysis for GENomics (DRAGEN) analysis for alignment to GRCh38, mapping, and variant calling. BGE uses low-coverage whole genome sequencing (lcWGS) (2-3x) combined with deep-coverage exome sequencing (30-40x), improving on SNP arrays for common variant imputation across European and non-European populations while also capturing rare coding variants. Relative to array genotyping, coverage, genotyping breadth, imputation generalizability, and cost are more optimal.BGE requires imputation for which the NHLBI TOPMed reference panel was used, and GLIMPSE2 was used for imputation emitting genotyping dosages (i.e., 0-2 multimodal continuous). Quality control (QC) included the following procedures. Sample QC excluded those with mean coverage 3% contamination from FREEMIX/VerifyBamID, sex aneuploidy and genotype/phenotype sex-mismatch due to potential phenotyping errors, fingerprinting discordance, and sample metric-level outliers were ancestry-aware, given expected distribution differences. Variant QC metrics including allele frequencies, imputation INFO scores, and Hardy-Weinberg Equilibrium (HWE) p-values are provided with the data; the genotype files provided are not filtered.

  Study phs003821

• Caregiving as a Natural Stressor in Studies of the Role of Genes That Affect Serotonin Function in Regulating Risk Factors for Coronary Heart Disease (CAREGIVER)

  The burden of caregiving for an ill relative has been shown to interact with existing comorbidities to increase risk of several health outcomes including metabolic syndrome and blood pressure reactivity. The CAREGIVER study was developed to compare cardiometabolic risk factors in caregivers and controls. These risk factors include physiologic measures, psychologic measures, neighborhood characteristics, and genetic and genomic factors. DNA and plasma were collected and used for examination of cardiometabolic and stress biomarkers, genotyping and methylation analysis.

  Study phs001747

• Development of targeted DNA sequencing panel for brain tumors

  A prompt and reliable molecular diagnosis for brain tumors has become crucial in precision medicine. While Comprehensive Genomic Profiling (CGP) has become feasible, there remains room for enhancement in brain tumor diagnosis due to the partial lack of essential genes and limitations in broad copy number analysis. In addition, the long turnaround time of commercially available CGPs poses an additional obstacle to the timely implementation of results in clinics. To address these challenges, we developed a CGP encompassing 113 genes, genome-wide copy number changes, and MGMT promoter methylation.

  Study EGAS50000000699

• cfDNA Methylomes for HCC Detection and Postoperative Monitoring

  To overcome the limitations of current ctDNA-based HCC detection, specifically mutational profiling, we propose quantifying cfDNA methylation levels using cfMeDIP-seq and evaluating its capacity for HCC detection and post-surgery recurrence monitoring. This approach aims to reveal the clonal dynamics of HCC during surgery and upon relapse. Our preliminary data and analyzed results demonstrate that tumor-agnostic cfDNA methylomes can accurately detect HCC and predict recurrence after liver resection or transplantation. This method could have significant implications for the diagnosis, treatment, and monitoring of HCC.

  Study EGAS50000000450

• Gene signature for predicting homologous recombination deficiency in triple-negative breast cancer

  We developed a gene expression-based classifier for homologous recombination deficiency (HRD) in breast cancer patients using WES and RNA-seq data obtained from 94 TNBC samples from a Malaysian hospital-based cohort (MyBrCa). This classifier was able to predict for high levels of a mutational signature associated with HRD in an additional MyBrCa TNBC validation cohort (this EGA study) as well as in TNBCs from TCGA. We also validated the classifier on a NanoString platform with both fresh frozen and FFPE tissue.

  Study EGAS00001006518

• Myeloid-specific KDM6B inhibition sensitizes Glioblastoma to PD1 blockade

  This data set include FASTQ files for five experiments: Human scRNA-Seq data (6 samples), Human Visium spatial transcriptomic data (3 samples), Mouse scRNA-seq data (4 samples), Mouse scATAC-seq data (2 samples), Mouse ChIP-seq data (8 samples). For the mouse scATAC-seq data (2 samples), there are originally three FASTQ files, R1, R2 and R3 files. The R1 and R2 FASTQ files were merged into one larger file ("R1R2") per sample for submission as paired-end sequencing setting to follow the EGA guidelines. They can be split into individual R1 and R2 files in order to be processed by Cell Ranger software. The files with IC1 suffix are CHIP-seq Input control for anti-KDM6B antibody pull down experiments and the files with IC2 suffix are CHIP-seq Input control for anti-H3K27ME3 antibody pull down experiments in murine model.

  Dataset EGAD00001010073

• Whole-genome sequence data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Each tumor sample was cut into three pieces, yielding two end-pieces for cryovials and a middle portion placed in 10% buffered formalin. End pieces were homogenized manually and with a paddle blender (Stomacher). All paraffin-embedded blocks, including formalin-fixed tumor samples and molecular-fixed fallopian tubes, were sectioned and stained with hematoxylin and eosin prior to expert histopathological review to confirm the presence of high grade serous carcinoma. Homogenized end pieces were then flash frozen and later used for WGS. For all tumor and matched normal (peripheral blood) samples, DNA was extracted with the Qiagen AllPrep DNA/RNA kit (tumor samples from patients 25,26,28-32) or the Qiagen Blood and Tissue Extraction Kit (tumor samples from patients 1-4,7,9-17, and all blood samples). For all tumor and normal samples, DNA extraction was followed by library construction and sequencing using Illumina HiSeq2500 whole genome shotgun v4 chemistry with paired-end 125bp reads.

  Dataset EGAD00001003984

• Dataset for CD8-Positive lymphocyte samples

  This dataset contains scRNA sequencing data for CD8-Positive lymphocytes samples. Sequencing was performed on a Illumina NextSeq 550. The sequencing was always paired.

  Dataset EGAD50000000092

• WES data from patient samples at the stage of NDMM and EMM and normal samples

  This contains the raw Whole Exome sequencing data used for the publication

  Study EGAS50000000036

• RNA-seq dataset for gamma delta (γδ) T-ALL patients

  RNA-seq data for 85 patients with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL)

  Dataset EGAD50000000027

• Bulk RNAseq of patient samlpes at the stage of NDMM, RRMM without EMM and EMM

  This study contains the raw bulk RNAseq data used for the publication

  Study EGAS50000000035

• Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Dataset EGAD00010002682

• EARLY DIAgnosis of PAncreatic Cancer (EARLY DIAPAC) study

  Whole genome sequencing of pancreatic cyst fluid for early detection and diagnosis of pancreatic cancer.

  Study EGAS50000000611

• DAC for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Data access comittee for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Dac EGAC50000000650

• Genomic sequencing data for PNG15 and PNG16

  This data set contains genomic sequencing data and variant calls for PNG15 and PNG16.

  Dataset EGAD50000001598

• shallow Whole-Genome sequencing of 14 TNBC tumor in the MATADOR trial - for in silico spike-in experiment

  14 TNBC tumors with tumor percentage ~90% were selected for in silico spike-in experiment

  Dataset EGAD50000001863

• scRNAseq dataset of vitligo dermis and epidermis

  scRNAseq dataset of vitligo dermis and epidermis for 6 patients. For each patient nonlesional and perilesional skin were sampled and processed separately.

  Dataset EGAD50000001874

• NAR-GAB 2025 deposit data

  Human exome gVCFs: rare-disease cohort for the NAR-GAB 2025 study on splicing-SNV prioritization.

  Study EGAS50000001456

• HICHIP_TALL_t_14_16_translocation

  For patient P01, HiChIP experiment for was performed using the Arima-HiC+ kit (A510008, Arima genomics) according to the manufacturer’s protocols.

  Dataset EGAD50000002167

• Primary Neuroblastoma Circle-seq

  We generated Circle-seq data for primary neuroblastoma to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004797

• Res1_PC9_exp2_MC_01_04_22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006170

• V4_panel_bait_design_test

  Targeted gene screen of FFPEs, cell lines and primary tumours for testing the new V4 Cancer gene panel.

  Study EGAS00001001808

• Myeloma_Follow_up_Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Study EGAS00001000743

• Res1_H23_exp2_MC_13_07_22

  8 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006683

• Res1_PC9_exp1_MC_29_03_22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006169

• WXS files for Mullighan BiTE WXS

  WXS files for Mullighan BiTE WXS paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005730

• Whole-genome sequencing data for 449 Nigerian individuals

  Whole-genome sequencing data in the form of multi-sample, per-chromosome VCFs for n=449 individuals across 47 unique ethnolinguistic groups.

  Dataset EGAD00001010095

• RNASeq files for Mullighan Leventaki ALCL Project

  RNASeq files for Mullighan Leventaki ALCL Project paper titled "Integrative molecular analysis of pediatric Anaplastic large cell lymphoma reveals subtypes with distinct immune suppression signatures."

  Dataset EGAD00001005951

• WES for Patient 9 to 14 of NIBIT-M4 clinical trial

  WES for Patient 9 to 14 of NIBIT-M4 clinical trial

  Dataset EGAD00001009700

• RNAseq files for Mullighan BiTE RNASEQ1

  RNAseq files for Mullighan BiTE RNASEQ1 paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005731

• A95724A

  Whole genome sequencing for single cells for library A95724A 503 samples; filetype=bam

  Dataset EGAD00001008229

• WGS files for Millighan BiTE WGS

  WGS files for Mullighan BiTE WGS paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005729

• Brain mets discovery cohort whole-exome sequencing raw sequencing files

  These are the raw sequencing files for the 50 brain tumour, 3 extracranial tumour and 34 matched normals for the patients in the discovery cohort.

  Dataset EGAD00001005981

• Additional WGS files for Genomic Landscape ALL paper

  Additional WGS files for Genomic Landscape ALL paper titled "The genomic landscape of pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001010270

• Mucoepidermoid Carcinoma

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001003958

• Targeted sequencing using SPET for Mesothelioma.

  Targeted sequencing using SPET for Mesothelioma.

  Dataset EGAD00001001916

• WGS files for Klco-NUP98 data

  WGS files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015443

• WXS files for Klco-NUP98 data

  WXS files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015444

• RNASeq files for Klco-NUP98 data

  RNASeq files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015445

• scRNASeq files for Klco-NUP98 data

  scRNASeq files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015479

• Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Dataset EGAD00001011994

• Mucoepidermoid carcinoma- normals

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001004946

• MT amplicon sequencing reads of 217 Egyptian individuals

  This data set contains for 217 Egyptian individuals the amplicon sequencing reads mapping to chrM. These were subsequently used for haplogroup assignment.

  Dataset EGAD00001006040

• neoALTTO

  RNAseq fastq files for 254 samples for the neoALTTO study of lapatinib, trastuzumab or combination in HER2+ breast cancer patients. Those are pre-treatment baseline samples.

  Dataset EGAD00001011354

• Alcohol Dependence: Sequencing from Multiplex Families

  Two multiplex for alcohol dependence family studies were initiated based on the gender of a pair of probands. Ascertainment of a pair of AD probands was used to increase the density of alcohol dependence within the family. Identification of male (Cognitive and Personality Factors in Relatives of Alcoholics Family Study) and female (Biological Risk Factors in Female Alcoholics Family Study) alcohol dependent probands was accomplished by identifying an alcohol dependent proband while in treatment in a substance abuse treatment facility in Pittsburgh and surrounding communities who provided contact information for a sibling whom he/she thought might be interested in participating. The studies had identical ascertainment requirements. DNA was banked for all willing participants.

  Study phs001775

• Immune Profiles Study

  This study assesses glioma patient blood methylation longitudinally beginning pre-surgery through other clinically important timepoints. Progression and survival are studied in relation to methylation derived immunologic profiles and other characteristics. For this study, patients scheduled for surgery at University of California San Francisco (UCSF) for a possible newly diagnosed glioma (grades 2-4) or recurrent grade 2/3 glioma were consented and enrolled. Patients had blood collected pre-surgery and, if the pathology results confirm a glioma, every few weeks or months during their treatment (up to 30 total timepoints). Blood immunomethylomic profiles were measured at these timepoints to assess associations with glioma patient outcomes, clinical measures, other known prognostic markers, and imaging characteristics.

  Study phs002998

• Development and Validation of Patient-Derived Xenografts from Fibrolamellar Carcinoma Human Tissue

  We developed and validated Patient-Derived Xenografts (PDX) of Fibrolamellar Carcinoma human tissue from surgical resections. Human tissues from primary liver tumor, recurrent liver, and liver metastases were implanted into NOD-SCID-Gamma (NSG) mice (Jackson laboratories) and monitored for tumor growth. Some of the original tissues were frozen for further analysis including RNA sequencing. Tumors that grew were then harvested and passaged into additional mice. Some tumor tissues from the PDX samples were frozen for RNA-Seq analysis. The PDX was validated by histologic, transcriptomic and proteomic analysis. The RNA-Seq analysis was performed on original tissue samples including primary liver tumor, recurrent liver, liver metastases, normal liver, and the derived PDX.

  Study phs002435

• Division of Cancer Epidemiology and Genetics (DCEG) Imputation Reference Dataset

  We have built a new resource for imputation of SNPs for existing and future genome-wide association studies (GWAS), known as the Division of Cancer Epidemiology and Genetics (DCEG) Reference Set. The first build of the data set includes 728 cancer-free individuals of European descent from three large prospectively sampled studies, 98 African-American individuals from the Prostate, Lung, Colon, and Ovary Cancer Screening Trial (PLCO), 74 Chinese individuals from a Chinese clinical trial in Shanxi, China (SHNX), and 349 unrelated individuals from the HapMap Project (see Molecular Data Section for details on arrays used). The final harmonized dataset includes 2.8 million autosomal polymorphic SNPs on 1,249 subjects after rigorous quality control metrics were applied.

  Study phs000396

• Sequencing data of tumor tissue obtained from GANNET53 study patients

  The GANNET53 clinical trial evaulated novel treatment options for ovarian cancer patients with platinum-resistant relapse. Archival fresh-frozen paraffin embedded tissue was available from 131 of the 133 enrolled patients. NGS sequencing aimed at assessing the mutational spectrum of key ovarian cancer genes (with a focus on TP53), and their relevance for therapy resistance. From available FFPE samples, DNA was extracted and NGS sequenced using the SureSeq™ Ovarian Cancer Panel and the NGS Library Preparation kit covering all exons of 7 key ovarian cancer genes BRCA1, BRCA2,TP53, PTEN, ATM, ATR, NF1 for single nucleotide variants (SNV) and indels. Finally, sequence data from 118 individual FFPE tumor tissue samples were generated.

  Study EGAS50000000935

• MYOSEQ project

  The MYOSEQ project focuses on the application of next generation sequencing, in particular whole exome sequencing (WES), in a large cohort of patients with unexplained limb‐girdle weakness (LGW). Focusing on undiagnosed patients with a clearly defined clinical phenotype enables increased diagnostic rates for known genes (in particular Pompe disease, GNE related pathologies and other known LGMD subtypes) in this cohort, while the use of WES provides scope both for new gene discovery and for additional research into disease modifiers and genotype‐phenotype correlation with substantial cost effectiveness. The LGW patient cohort was collated by Newcastle University in collaboration with clinical centers across Europe. The sequencing was performed at the Broad Institute and jointly analyzed with Newcastle University.

  Study EGAS00001002069

• Identification of four new susceptibility loci for testicular germ cell tumour, including variants near GAB2, GSPT1 and ZFPM1

  Genome wide association studies (GWAS) have identified multiple risk loci for testicular germ cell tumour (TGCT), revealing a polygenic model of disease susceptibility strongly influenced by common variation. To identify further SNPs associated with TGCT we conducted a multistage GWAS with a combined dataset of >25,000 individuals (6,059 cases and 19,094 controls). We identified new risk loci for TGCT at 3q23 (rs11705932, TFDP2, P = 1.5 x 10-9), 11q14.1 (rs7107174, GAB2, P = 9.7 x 10-11), 16p13.13 (rs4561483, GSPT1, P = 1.6 x 10-8) and 16q24.2 (rs55637647, ZFPM1, P = 3.4 x 10-9). We additionally present detailed functional analysis of these loci, identifying a statistically significant relationship between rs4561483 risk genotype and increased GSPT1 expression in TGCT patient samples. These findings provide additional support for a polygenic model of TGCT risk and further insight into the biological basis of disease development.

  Study EGAS00001001302

• Ultra-Low-Pass Whole Genome Sequencing of Cell-Free DNA for Large B-Cell Lymphoma

  While deep targeted DNA sequencing of liquid biopsies has shown prognostic utility in large B-cell lymphoma (LBCL), the routine clinical adoption of these assays remains limited due to their high costs. Here, leveraging a well-annotated cohort of encompassing both frontline and relapsed/refractory (R/R) LBCL, we profiled patient plasma samples with two complementary modalities – ultra-low-pass whole genome sequencing (ulpWGS) and deep targeted DNA sequencing, the former being a cost-effective method to profile large scale chromosomal abnormalities and estimate tumor burden. Our findings revealed a strong association of high cell-free tumor burden by both genomic profiling modalities with established measures of tumor burden and patient survival. Notably, the associations with survival remained statistically significant after accounting for international prognostic index scoring. Furthermore, we showed that del(17p) in circulating tumor DNA as detected by ulpWGS was strongly associated with TP53 mutation status and predicted for significantly inferior patient outcome in frontline but not R/R LBCL patients. Our study demonstrates that ulpWGS can provide robust prognostic biomarkers for both frontline and R/R LBCL, highlighting its broad applicability for risk stratification.

  Study EGAS50000001027

• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  Background Despite advances in identification of genetic markers associated to severe COVID-19, the full genetic characterisation of the disease remains elusive. Imputation of low-coverage whole genome sequencing (lcWGS) has emerged as a competitive method to study such disease-related genetic markers as they enable genotyping of most common genetic variants used for genome wide association studies. This study aims at exploring the potential use of imputation in lcWGS for a highly selected severe COVID-19 patient cohort. Findings We generated an imputed dataset of 79 variant call format (VCF) patient files using the GLIMPSE1 tool, each containing, on average, 9.5 million single nucleotide variants. The validation assessment of imputation accuracy yielded a squared Pearson correlation of approximately 0.97 across sequencing platforms, showing that GLIMPSE1 can be used to confidently impute variants with minor allele frequency up to approximately 2% in Spanish ancestry individuals. We conducted a comprehensive analysis on the patient cohort, examining hospitalisation and intensive care utilisation, sex and age-based differences, and clinical phenotypes using a standardised set of medical terms specifically developed to characterise severe COVID-19 symptoms for this cohort. Conclusion This dataset highlights the utility and accuracy of lcWGS imputation in the study of COVID-19 severity, setting a precedent for other applications in resource-constrained environments. The methods and findings presented here may be leveraged in future genomic projects, providing vital insights for health challenges like COVID-19.

  Study EGAS00001007573

• Preclinical Pediatric Molecular Analysis for Therapy Choice (MATCH)

  Purpose: Pediatric solid tumors arise from diverse tissues during development and exhibit a wide range of molecular, cellular and genetic features. This diversity, combined with the low incidence of pediatric cancer makes it increasingly difficult to personalize therapy for individual patients based on the unique features of their tumors. Therefore, well-credentialed preclinical models that capture the diversity and heterogeneity of pediatric solid tumors are essential for identifying molecular targeted therapeutics for precision medicine. Experimental Design: Here, we report 281 orthotopic patient derived xenografts (O-PDXs) from 224 patients representing 24 different types of pediatric solid tumors. We have performed genomic characterization of the O-PDXs and compared them to their corresponding patient tumors. To demonstrate the feasibility and utility of using such a diverse collection of O-PDXs in preclinical studies, we performed a preclinical pediatric precision medicine trial based on the NCI-COG Pediatric MATCH trial enrollment criteria. We also tested molecular targeted therapy for a novel oncogenic fusion recently reported in pediatric melanoma and precision drug delivery using nano-liposomal irinotecan. Results: In the preclinical match study, we identified one specific single agent response to LY3023414 in an osteosarcoma model with a TSC2 variant of unknown significance. Combinations of nano-liposomal irinotecan were effective in treating both Ewing sarcoma and rhabdomyosarcoma xenografts. Conclusion: Our studies demonstrate the value of large, well-credentialed preclinical models for future precision medicine in pediatric oncology using single agents, drug combinations and novel drug formulations.

  Study EGAS00001008011

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Sequence reads for pediatric GBM samples for manuscript: Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Dataset EGAD00001000134

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD50000000201

• Cancer Registry of Norway - NIPH Data Access Committee for CRCbiome datasets

  The Cancer Registry of Norway - NIPH appointed Data Access Committee for the CRCbiome datasets - The microbiome as a colorectal cancer screening biomarker. https://www.mn.uio.no/sbi/english/groups/rounge-group/crcbiome/.

  Dac EGAC50000000121

• WGS dataset for gamma delta (γδ) T-ALL patients

  Whole genome sequencing data for 61 samples with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL) and 29 germline samples

  Dataset EGAD50000000028

• RNA-seq data for genomic determinants of response and resistance to inotuzumab in B-ALL

  RNA-seq data for 101 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000095

• WTCCC2 Schizophrenia study

  A WTCCC2 project genome-wide case-control association study for schizophrenia (SP) in individuals from Ireland.

  Study EGAS00000000118

• Massachusetts General Hospital Cancer Center DAC for high-throughput microfluidic enrichment from whole leukopak for CTC-based liquid biopsy

  Whole genome sequencing and whole exome sequencing data of circulating tumor cells isolated from patients with metastatic prostate cancer and liver cancer.

  Dac EGAC50000000423

• scRNA-seq for 4 reactive lymph node and 12 high grade B cell lymphoma samples

  Dataset includes count matrices, barcode tsvs, and features tsv for each sample, generated using Cell Ranger.

  Dataset EGAD50000001386

• Targeted Capture DNA Sequencing

  We performed targeted capture DNA sequencing for 29 genes in extranodal NK/T-cell lymphoma, nasal type (n=67).

  Study JGAS000548

• ONT and PacBio data of 22q11 patient-parent duos/trios

  ONT and PacBio FASTQ files generated for de novo assembly and resulting de novo assemblies

  Study EGAS50000001647

• Genome-wide genotyping and methylation data from Understanding Society

  Genome-wide genotyping and methylation data from Understanding Society. Please visit https://www.understandingsociety.ac.uk/ for further information.

  Study EGAS00001008417

• A96233A

  Whole genome sequencing for single cells for library A96233A 637 cells; filetype=bam

  Dataset EGAD00001007622

• MT sequencing reads from WGS of 10 Egyptian individuals

  This data set contains for 10 Egyptian individuals the WGS reads mapping to chrM. These were subsequently used for haplogroup assignment.

  Dataset EGAD00001006038

• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327

• A108735A

  Whole genome sequencing for single cells for library A108735A 714 cells; filetype=bam

  Dataset EGAD00001007593

• A98293B

  Whole genome sequencing for single cells for library A98293B 703 samples; filetype=bam

  Dataset EGAD00001008265

• lowinput RNASEQ files for Mullighan BiTE RNASEQ2

  lowinput RNASEQ files for Mullighan BiTE RNASEQ2 paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005732

• A98176B

  Whole genome sequencing for single cells for library A98176B 1389 samples; filetype=bam

  Dataset EGAD00001008261

• A96178A

  Whole genome sequencing for single cells for library A96178A 788 cells; filetype=bam

  Dataset EGAD00001007115

• WES for Patient 1 to 8 of NIBIT-M4 clinical trial

  WES for Patient 1 to 8 of NIBIT-M4 clinical trial

  Dataset EGAD00001009701

• Additional RNASeq files for Roussel MBPRP

  Additional RNASeq files for Roussel paper titled "Combination of CDK4/6 with BET-bromodomain and PI3K/mTOR inhibitors in medulloblastoma in vitro and in vivo"

  Dataset EGAD00001009394

• consHLA extra samples for comparison with clinical HLA types

  Samples not in other datasets for the paper titled; consHLA: a Next Generation Sequencing Consensus-based HLA Typing Workflow

  Dataset EGAD00001015625

• A96172A

  Whole genome sequencing for single cells for library A96172A 1476 samples; filetype=bam

  Dataset EGAD00001008240

• A98294A

  Whole genome sequencing for single cells for library A98294A 994 samples; filetype=bam

  Dataset EGAD00001008266

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006325

• A95730A

  Whole genome sequencing for single cells for library A95730A 739 cells; filetype=bam

  Dataset EGAD00001007614

• A95724B

  Whole genome sequencing for single cells for library A95724B 581 samples; filetype=bam

  Dataset EGAD00001008230

• A96216A

  Whole genome sequencing for single cells for library A96216A 1001 samples; filetype=bam

  Dataset EGAD00001008257

• A98289B

  Whole genome sequencing for single cells for library A98289B 1032 samples; filetype=bam

  Dataset EGAD00001008264

• Sequencing data for Murtaza et al. Nature Communications 2015 (doi:10.1038/ncomms9760)

  Exome and targeted amplicon sequencing data for tumor, germline and plasma samples from a patient with metastatic breast cancer.

  Dataset EGAD00001002108

• Bam files for the whole exome sequencing from the study on Spatial homogeneity in pediatric brain tumors.

  Bam files for the whole exome sequencing from the study on Spatial homogeneity in pediatric brain tumors.

  Dataset EGAD00001001055