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• Reference single cell SNP array dataset from Coriell for training and validation of method for accurate single cell genotyping

  This dataset contains DNA from B-lymphocytes from 2 Coriell families and 4 individuals hybridized to HumanKaryomap BeadChip Array. Single cells from subjects GM12878 and GM7228 were amplified using multiple displacement amplification (SureMDA) according to Infium Karyomapping Assay Guide. Bulk DNA was processed and hybridized to an array for subject GM12878, GM07224 and GM07225.

  Dataset EGAD00001006376

• WES and WGS data for HGSC patient derived cell lines and fresh frozen tumor samples from same patients

  Sequencing data for three HGSC patients with patient derived cell lines. WES data for two patient derived cell line samples and matched blood control samples. Fresh frozen tumor samples of two patients with WES or WGS sequencing data.

  Dataset EGAD00001009330

• ESGI - Molecular diagnosis for mitochondrial disorders (2017-08-29)

  The MITOEXME project aims to improve protocols for molecular diagnosis of patients with OXPHOS disorders with a focus on a next generation sequencing methods and to increase the knowledge of pahtophysiological mechanisms by identification of new targets and cellular studies. In this project we will sequence the exomes fo 120 patients. This dataset contains all the data available for this study on 2017-08-29.

  Dataset EGAD00001003596

• Paired-end Whole Exome-seq analysis of multi-centric lower grade glioma

  This dataset includes Nimblegen SeqCap EZ Exome v3 data for each lesion of three patients with multicentric glioma. For two patients, each lesion was sequenced along with whole blood. For a third patient, 3 pieces from the right lesion and 4 pieces from the left were sequenced along with whole blood. In each case BAM files that have been aligned with BWA mem alignment are available.

  Dataset EGAD00001003795

• RNA-Seq of novel miR (nmiR-1 and nmiR-2) overexpression and knockdown in BL

  After overexpression and knockdown of both described novel miRs nmiR-1 and nmiR-2 in BL cell lines (SU-DHL4 for nmiR-1 and Raji for nmiR-2), we performed regular RNA-Seq (including Mock controls for all cell lines) to identify their direct and indirect downstream mRNA targets.

  Dataset EGAD00001001612

• Two lung cancer cell lines with EGFR mutations, PC-9 and KHM-3S, were either treated with Tarceva for 24 hours or left untreated. The gene expression profiles were examined by RNAseq, and the genome wide binding profiles of total STAT3 and pSTAT3 were characterized by ChIPseq.

  Lung cancers harboring activating EGFR mutants show dramatic responses to EGFR TKIs, such as Tarceva. However, nearly all patients show relapse within 1 year after initial treatment. To investigate the early signaling switches that are involved in the formation of drug resistance, and the role of STAT3 in the early signaling switches involved in the formation of drug resistance, we have treated two lung cancer cell lines with EGFR mutations, PC-9 and KMH-3S, with Tarceva for 24hours. The RNA samples with and without treatment were collected in triplicate for RNAseq experiment.The total STAT3 and pSTAT3 chromatinIP were done on samples with and without treatment for ChIPseq.

  Study EGAS00001000793

• A benchmarking resource for NGS testing of cancer predisposition genes

  A benchmarking resource of 639 individuals, to assess the analytical sensitivity of cancer predisposition gene (CPG) testing.The dataset includes sequencing data generated using the TruSight Cancer Panel (TSCP) a targeted NGS assay for analysis of CPGs and orthogonally generated data supporting at least one pathogenic variant in a CPG for a total of 645 pathogenic CPG variants.The set of pathogenic CPG variants includes strong representation of some of the most challenging types of pathogenic variants, with 339 indels, including 16 complex indels and 24 insertions or deletions with length greater than 5bp, and 74 exon CNVs, including 23 single exon CNVs. There are 502 pathogenic variants in BRCA1 or BRCA2, making this an important first-line validation dataset for laboratories performing NGS testing of BRCA1 and BRCA2.

  Study EGAS00001002993

• Sequencing data for Australian Ovarian Cancer study submitted 20121116

  Sequencing data for Australian Ovarian Cancer study submitted 20121116

  Dataset EGAD00001000293

• Sequencing data for Australian Pancreatic Cancer study submitted 20130102

  Sequencing data for Australian Pancreatic Cancer study submitted 20130102

  Dataset EGAD00001000323

• HiSeq sequencing data for PDAC cell lines generated by QCMG

  Sequencing data for PDAC cell lines generated by QCMG

  Dataset EGAD00001000371

• Array data for oesophageal and related samples – sj_paper_methyl_tumour_release

  Array data for oesophageal and related samples – sj_paper_methyl_tumour_release

  Dataset EGAD00010001822

• Colorectal cancer functional annotation - ChIP

  ChIP-seq data for multiple colorectal cancer cell lines (H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, CTCF)

  Study EGAS50000000207

• Roifman DAC

  This Data Access Committee will oversee all requests for data submitted by Dr. Chaim Roifman at the Hospital for Sick Children in Toronto, Canada. Requests should be directed by email to chaim.roifman@sickkids.ca.

  Dac EGAC50000000396

• EM-seq converted WGS for CSF-derived cfDNA from pediatric brain tumor patients

  EM-seq converted WGS for CSF-derived cfDNA from pediatric brain tumor patients

  Dataset EGAD50000001975

• GBM cancer stem cell lines -RNA-seq and WGS data

  Glioblastoma stem cell lines have been profiled for RNA-seq and WGS

  Study EGAS00001003700

• WTCCC2 project Glaucoma (GL) samples

  A WTCCC2 genome-wide association study for glaucoma (GL) in Australian individuals of European descent.

  Study EGAS00001000624

• DEEP IHEC release 2017

  Raw data files for DEEP's IHEC/EpiRR submission of 2017. metadata available at: http://deep.dkfz.de/#/experiments

  Study EGAS00001002655

• CRISPR_screen_M14__NCI_H3122

  Genome wide CRISPR screen was performed to find resistance to targeted drugs for melanoma and lung

  Study EGAS00001001060

• RNASeq files for Mullighan_GL_reALL RNASEQ1

  RNASeq files for Mullighan_GL_reALL RNASEQ1 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001005511

• T-WGBS for Naive B Cell

  Tagged-WGBS for 3 Naive B Cell samples of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005966

• RNASeq files for Mullighan ECOG2993 data

  RNASeq files for paper titled "Molecular classification improves risk assessment in adult B-lineage ALL: Patients on the international UKALLXII-ECOG2993 trial."

  Dataset EGAD00001006380

• A95654B

  Whole genome sequencing for single cells for library A95654B 1740 cells; filetype=bam

  Dataset EGAD00001006940

• RNAseq files for Mullighan_GL_reALL RNASEQ2

  RNAseq files for Mullighan_GL_reALL RNASEQ2 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001005510

• Somatic SNVs and Indels for INSPIRE Tumor WES

  Somatic SNVs and Indels for INSPIRE Tumor WES called using Mutect, Mutect2, Varscan2, Vardict, and Strelka2

  Dataset EGAD00001006569

• ONT Minion reads for a patient with ataxia-pancytopenia syndrome.

  ONT Minion reads to provide 30x coverage for a patient with ataxia-pancytopenia syndrome.

  Dataset EGAD00001005022

• WGS files for Roussel-ATRT-TM

  WGS files for Roussel-ATRT-TM paper titled "Atypical teratoid/ rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities"

  Dataset EGAD00001009163

• Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (Illumina)

  Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (Illumina)

  Dataset EGAD00001009630

• RNASeq files for CIC paper data

  RNASeq files for CIC paper titled "Malignant progression of an ancestral bone marrow clone harboring a CIC-NUTM2A fusion in isolated myeloid sarcoma"

  Dataset EGAD00001009788

• UKBEC 1st release of Exome data for 65 individuals

  UKBEC 1st release of Exome data for 65 neuropathologically confirmed control individuals of European descent.

  Dataset EGAD00001003100

• RNASeq files for Newman MAP3K8 melanoma

  RNASeq files for MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004567

• WES files for CHEN WTPDX WES

  WES files for CHEN WTPDX paper titled "Forty-Five patient-derived xenografts capture the clinical and biological heterogeneity of Wilms tumor"

  Dataset EGAD00001004506

• McGill EMC Release 4 in tissue "venous blood" for cell type "Monocyte"

  McGill EMC Release 4 in tissue "venous blood" for cell type "Monocyte"

  Dataset EGAD00001001282

• McGill EMC Release 4 in tissue "venous blood" for cell type "eosinophil"

  McGill EMC Release 4 in tissue "venous blood" for cell type "eosinophil"

  Dataset EGAD00001001281

• Maternal Plasma RNA Sequencing for Genomewide Transcriptomic Profiling and Identification of Pregnancy-Associated Transcripts

  Maternal Plasma RNA Sequencing for Genomewide Transcriptomic Profiling and Identification of Pregnancy-Associated Transcripts

  Dataset EGAD00001001609

• WXS files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  WXS files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  Dataset EGAD00001015801

• Thymic epithelial transplantation for complete DiGeorge syndrome Spatial (2025-07-28)

  Spatial transcriptomics study of thymic transplant biopsies . This dataset contains all the data available for this study on 2025-07-28.

  Dataset EGAD00001015659

• WGS files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  WGS files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  Dataset EGAD00001015800

• RNASeq files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  RNASeq files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  Dataset EGAD00001015802

• Remaining WGS files for Klco RPAML data

  Remaining WGS files for study titled "Genomics of pediatric myeloid neoplasms"

  Dataset EGAD00001008446

• Single cell whole genome sequencing of 5 ovarian cancer specimens

  Single cell whole genome sequencing BAM files for five ovarian cancer specimens.

  Study EGAS50000001458

• Molecular Analysis of Short- Versus Long-Term Survivors of High-Grade Serous Ovarian Carcinoma

  The underlying determinants for long-term survival (LTS, ≥10 years) versus short-term survival (STS, <3 years) of patients diagnosed with high-grade serous ovarian carcinoma (HGSC) are largely unknown. The present study sought to identify molecular predictors of LTS for women with HGSC. A cohort of 24 frozen HGSC samples (12 LTS and 12 STS) were collected and analyzed at DNA and RNA levels. Copy number variation and mutation did not indicate large differences between LTS and STS. From RNA-Seq analysis, 11 genes were found to be differentially expressed between the STS and LTS groups (fold change >2; false discovery rate <0.01). In the validation cohort, transmembrane protein 62 (TMEM62) was found to be related to LTS. Our in vitro and in vivo studies demonstrate that restoring TMEM62 may be a novel approach for treatment of HGSC. These findings may have implications for biomarker and intervention strategies to help improve patient outcomes.

  Study phs003020

• NIDCD Otitis Media Genetic Susceptibility and Middle Ear Microbial Shifts

  The study funded by R01 DC015004 aims to: (1) Identify rare OM susceptibility variants within families and in probands; and (2) Identify differences in the middle ear microbiome due to OM susceptibility variants. This study will also elucidate mechanisms responsible for the formation and growth of cholesteatoma, and bony erosion and complications due to cholesteatoma e.g. intracranial, hearing/vestibular loss, facial nerve palsy. A better understanding of cholesteatoma pathogenesis will potentially reveal novel drug targets, which can lead to new non-surgical therapies for cholesteatomatous OM. Our specific aims for this administrative supplement are: Aim 1 -- Perform RNA-sequencing using cholesteatoma samples collected from Filipino and Colorado patients who will be screened for FUT2, SPINK5 and A2ML1 variants; and Aim 2 -- Using network analysis, identify bone-expressed proteins potentially interacting with FUT2, SPINK5 or A2ML1, then test protein expression in archival human temporal bone in direct contact with cholesteatoma.

  Study phs001941

• Characterizing Individual Cells Obtained from Bone Marrow Biopsies of MPN Patients

  We profiled the transcriptomes of individual cells obtained from bone marrow aspirates of 7 treatment-naïve newly diagnosed JAK2-mutant myeloproliferative neoplasm (MPN) patients (3 polycythemia vera and 4 essential thrombocythemia patients), and 2 healthy controls. The submitted data corresponds to sequencing reads mapped to the human reference genome GhRC38 build using CellRanger for a total of 9 samples (one per patient). In addition, to reconstruct the lineage histories of single cells in MPN patients, we performed whole-genome sequencing of single-cell-derived colonies of hematopoietic stem and progenitor cells from 2 essential thrombocythemia (ET) patients: 22 JAK2-mutant colonies and 20 WT colonies for patient ET 1; and 13 JAK2-mutant colonies and 21 WT colonies for patient ET 2. The submitted data consists of sequencing reads aligned to the human reference genome GhRC38 build using bwa-mem. Each file corresponds to the whole-genome sequencing data for one colony.

  Study phs002308

• ALLELE Consortium Glioblastoma Project

  Glioblastoma patient samples were sequenced for this project. The purposes of this project are: (1) to establish an umbrella protocol as a mechanism for identifying patients (in the USA and international sites) who agree to the collection, storage, and broad usage of their specimens and ongoing collection, and review of their medical information for the purposes of minimal-risk research and use of such data in clinical trials on which the patient may enroll; (2) to develop operations that facilitate investigator access to the data and/or tissue to conduct research, while minimizing risks to participants and promoting responsible conduct; and (3) to provide the infrastructure for the sharing of de-identified, coded samples, clinical data, and genomic data between participating investigators and institutions. Eligible patients include patients with known or suspected nervous system tumors or other neurologic diseases. Whole exome sequencing from the stated project will be released under this submission.

  Study phs003000

• Spatial Transcriptomics Reveals Discrete Tumor Microenvironments and Autocrine Loops Within Ovarian Cancer Subclones

  Ovarian masses from patients with high grade serous ovarian carcinoma undergoing debulking surgery were subjected to spatial transcriptomics profiling using the 10x Genomics Visium (fresh frozen) platform. Copy number inference using inferCNV predicted the presence of subclones with mutually exclusive copy number alterations (CNAs) in 5 of the 8 patient samples studied. In one patient, 3 subclones were predicted. For this patient sample, a serial section of the same tumor was used to microdissect regions corresponding to each of these subclones, and a 'normal' region predicted to contain only fibroblasts and no tumor cells. These microdissected regions were processed for low pass whole genome sequencing (WGS) and CNAs recorded using ichorCNA. An oral biopsy lacking tumor cells from an unrelated donor was used as a negative control for CNA inference. The CNAs predicted by inferCNV for the three subclones were validated by the low pass WGS and no CNAs were observed in the normal region containing fibroblasts.

  Study phs003561

• NHLBI TOPMed: Genomic Summary Results for the Trans-Omics for Precision Medicine Program

  The NHLBI Trans-Omics for Precision Medicine (TOPMed) program aims to identify the genetic basis of variation in biomedical phenotypes, with emphasis on those related to heart, lung, blood and sleep disorders, as part of a broader Precision Medicine Initiative. The TOPMed program has provided whole genome sequencing (WGS) to over 80 different studies that had previously recruited participants and collected extensive phenotype data. Many TOPMed investigators affiliated with these studies have organized their activities into phenotype-focused Working Groups and have developed genotype-phenotype association projects. These analyses have resulted in valuable cross-study Genomic Summary Results (GSR) that include whole genome association test results of both common and rare variants. Most of the analyses include data from multiple studies, some of which are based on sensitive populations, precluding public sharing of GSR. This dbGaP accession provides a mechanism for sharing sensitive GSR, using the controlled-access mechanisms of dbGaP to provide protections for sensitive populations.

  Study phs001974

• GRIDSS, PURPLE, LINX: Unscrambling the tumor genome via integrated analysis of structural variation and copy number

  We have developed a novel, integrated and comprehensive purity, ploidy, structural variant and copy number somatic analysis toolkit for whole genome sequencing data of paired tumor/normal samples. We show that the combination of using GRIDSS for somatic structural variant calling and PURPLE for somatic copy number alteration calling allows highly sensitive, precise and consistent copy number and structural variant determination, as well as providing novel insights for short structural variants and regions of complex local topology. LINX, an interpretation tool, leverages the integrated structural variant and copy number calling to cluster individual structural variants into higher order events and chains them together to predict local derivative chromosome structure. LINX classifies and extensively annotates genomic rearrangements including simple and reciprocal breaks, LINE, viral and pseudogene insertions, and complex events such as chromothripsis. LINX also comprehensively calls genic fusions including chained fusions. Finally, our toolkit provides novel visualisation methods providing insight into complex genomic rearrangements.

  Study EGAS00001004034

• Serial TERT rearrangement breakpoint quantification in circulating tumor DNA enables minimal residual disease monitoring in patients with neuroblastoma

  Approximately 30% of high-risk neuroblastomas harbor genomic TERT rearrangements at diagnosis, resulting in high TERT transcript levels and active telomerase. Combined with mutations in the RAS/MAPK/ALK signaling transduction network, these patients have a dismal prognosis. Our objective was to establish a liquid biopsy-based monitoring strategy for this particularly vulnerable patient subgroup, for whom no in-time molecular diagnostic tools exist to date. Detection and quantification of TERT rearrangement breakpoints in cell-free tumor DNA circulating in peripheral blood and bone marrow plasma from patients with TERT-driven neuroblastoma improved minimal residual disease monitoring and early relapse detection in individual patients. TERT rearrangement breakpoints, as a single marker or combined with mutations in the RAS/MAPK/ALK signaling transduction network, can be reliably analyzed from 1ng DNA using droplet digital PCR assays fit for clinical routine use. TERT rearrangement breakpoints are reflected in cell-free tumor DNA and can serve as robust biomarkers for disease activity.

  Study EGAS00001007365

• Sequencing data from MethylScan assay on plasma

  Machine learning models in biomedical research are often hindered by demographic imbalances in clinical datasets, leading to biased predictions that disadvantage minority populations. Existing bias correction methods face limitations in handling the heterogeneity of biomedical data and the complexity of demographic influences. Here, we present DeBias, a computational framework for mitigating demographic biases in high-dimensional biomedical datasets. DeBias eliminates bias-associated subspaces within the entire feature space using control samples and enables global bias correction across all features, effectively preserving disease-specific signals while minimizing demographic distortions. To demonstrate its effectiveness, we applied DeBias to cfDNA methylation data for cancer detection. It achieved a >6-fold reduction in the number of features containing biases and outperformed existing methods in improving the cancer detection performance for minority populations. Our method represented a promising step toward developing machine learning models that are more accurate, reliable, and equitable for minority populations.

  Study EGAS00001008127

• Unifying recovery dynamics in heterogeneous diseases exemplified by COVID-19

  Studying the recovery dynamics in different diseases poses many difficulties, as patients often display high heterogeneity in their recovery courses. Moreover, most attempts to study disease dynamics focus on disease progression rather than disease recovery mechanisms. To model recovery dynamics, using severe COVID-19 as the example, we align heterogeneous recovery trajectories via a novel computational scheme applied to longitudinally sampled blood transcriptomes. We thus generate pseudotime trajectories, which we then link to cellular and molecular mechanisms based on cell deconvolution analysis and molecular pathway prediction, thus presenting a unique framework for studying recovery processes over time. Specifically, mature neutrophils displayed a gradual decrease during recovery, allowing superior useability for outcome prediction compared to currently used clinical markers. Further, we discovered a recovery-related regulatory change in gene programs resulting in immune rebalancing between interferon and NFkB activity and the restoration of cell homeostasis. We thus propose regulatory mechanisms governing COVID-19 recovery and suggest mature neutrophils and additional gene markers, as novel clinical biomarkers for disease outcome. Overall, we present a novel clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

  Study EGAS00001005735