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• Telomerase activation by genomic rearrangements in high-risk neuroblastoma

  Neuroblastoma is a malignant pediatric tumor of the sympathetic nervous system1. Roughly half of these tumors regress spontaneously or are cured by limited therapy. By contrast, high-risk neuroblastomas have an unfavorable clinical course despite intensive multimodal treatment, and their molecular basis has remained largely elusive2-4. We have performed whole-genome sequencing of 56 neuroblastomas (high-risk, n=39; low-risk, n=17) and discovered recurrent genomic rearrangements affecting a chromosomal region (5p15.22) proximal of the telomerase reverse transcriptase gene (TERT). These rearrangements occurred only in high-risk neuroblastomas (12/39, 31%) in mutually exclusive fashion with MYCN amplifications and ATRX mutations, which are known genetic events in this tumor type1,2,5. In an extended case series (n=217), TERT rearrangements defined a subgroup of high-risk tumors with particularly poor outcome. Despite the large diversity of these rearrangements, they all induced massive transcriptional upregulation of TERT. In the remaining high-risk tumors, TERT expression was also elevated in MYCN-amplified tumors, whereas alternative lengthening of telomeres was present in neuroblastomas without TERT or MYCN alterations, suggesting that telomere lengthening represents a central mechanism defining this subtype. The 5p15.22 rearrangements juxtapose the TERT coding sequence to strong enhancer elements, resulting in massive chromatin remodeling and DNA methylation of the affected region. Supporting a functional role of TERT, neuroblastoma cells bearing rearrangements or amplified MYCN exhibited both upregulated TERT expression and enzymatic telomerase activity. In summary, our findings show that remodeling of the genomic context abrogates transcriptional silencing of TERT in high-risk neuroblastoma and places telomerase activation in the center of transformation in a large fraction of these tumors.

  Study EGAS00001001308

• Comparison of capture-based method for transcriptome profiling of formalin-fixed paraffin embedded tumor samples

  Background: The need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. Methods: Transcriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. Results: The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p < 0.01). Both Agilent and IDT detected all the clinically relevant fusions that were initially identified in FF-TruSeq. Conclusion: All exome capture-based methods had comparable performance and concordance with FF-TruSeq. By enabling the interrogation of FFPE tumor samples, our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

  Study EGAS00001005255

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• Genetic heritage of the Baphuthi highlights an over-ethnicised notion of 'Bushman' in the Maloti-Drakensberg, southern Africa

  Using contemporary people as proxies for ancient communities is a contentious but necessary practice in anthropology. In southern Africa, the distinction between the Cape KhoeSan and eastern KhoeSan remains unclear as ethnicity labels have been changed through time and most communities were decimated if not extirpated. The eastern KhoeSan may have had genetic distinctions from neighbouring communities who speak Bantu languages and KhoeSan further away, alternatively the identity may not have been tied to any notion of biology, instead denoting communities with a nomadic 'lifeway' distinct from African agro-pastoralism. The Baphuthi of the 1800s in the Maloti-Drakensberg, southern Africa had a substantial KhoeSan constituency and a lifeway of nomadism, cattle raiding, and horticulture. Baphuthi heritage could provide insights into the history of the eastern KhoeSan. We examine genetic affinities of 23 Baphuthi to discern whether the narrative of KhoeSan descent reflects distinct genetic ancestry. Genome-wide SNP data (Illumina GSA) were merged with 52 global populations, for 160K SNPs. Genetic analyses show no support for a unique eastern KhoeSan ancestry distinct from other KhoeSan or southern Bantu-speakers. The Baphuthi have strong affinities with early-arriving southern Bantu-speaking (Nguni) communities, as the later-arriving non-Nguni show strong evidence of recent African admixture possibly related to Late-Iron Age migrations. The references to communities as 'San',and 'Bushman' in historic literature has often been misconstrued as notions of ethnic/biological distinctions. The terms may have reflected ambiguous references to non-sedentary polities instead, as seems to be the case for the eastern ‘Bushman’ heritage of the Baphuthi.

  Study EGAS00001007080

• Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes

  Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes

  Dataset EGAD00001000050

• Methylated DNA immunoprecipitation sequencing of untreated and castration resistant prostate cancer

  Methylated DNA immunoprecipitation sequencing of 28 untreated prostate cancers, 11 castration resistant prostate cancers, and 12 benign prostatic hyperplasias.

  Dataset EGAD00001000610

• Whole exome sequencing Data from a child with ALPI deficiency and parents

  This dataset contains raw sequences (BAM files) of P1 trio: mother, father and affected child (P1). Whole exome sequencing (WES).

  Dataset EGAD00001004048

• PromethION (and Illumina) WGS and MinION transcriptome for a patient with diffuse large B-cell lymphoma.

  Dataset EGAD00001006204

• banfora_20150706_X

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 355 individuals from the VAC050 trial performed in Banfora, Burkina Faso - X chromosome.

  Dataset EGAD00010002579

• banfora_20150706_autosomes

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 355 individuals from the VAC050 trial performed in Banfora, Burkina Faso - autosomes.

  Dataset EGAD00010002581

• Batch1_Genotypes_Raw

  Genotypes generated for Puno cohort Batch 1. Case (PRE) and control (PUN) families were recruited in hospital, and additional unrelated controls were recruited in university (UNA). Raw genotypes no QC.

  Dataset EGAD00010002126

• Whole Genome Sequencing of tumor and blood from 4 pediatric cases with second malignancies.

  Whole Genome Sequencing (120X) of the two tumors and blood from 4 pediatric cases with second malignancies (12 WGS)

  Dataset EGAD50000000237

• snRNA-sequencing data from 3 FSHD and 1 control multinucleated myotube cell cultures

  snRNA-sequencing data from 3 FSHD and 1 control multinucleated myotube cell cultures

  Dataset EGAD50000000207

• 10X Chromium 5' scRNA and scTCR sequencing of on-treatment HNSCC PBMC samples

  We performed 10X Chromium 5' scRNA and scTCR sequencing on 4 on-treatment HNSCC PBMC samples.

  Dataset EGAD50000000054

• 10X Chromium 3' scRNA sequencing of pre- and on-treatment HNSCC biopsy samples

  We performed 10X Chromium 3' scRNA sequencing of 23 pre- and on-treatment HNSCC biopsy samples.

  Dataset EGAD50000000055

• Evaluation of Ancestry Admixture among Chileans

  The purpose of this study is to investigate ancestry admixture among Chileans with and without gallbladder cancer.

  Study phs001385

• 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

• H3K27ac HiChIP Dataset for 19 T-ALL patients and one normal control sample

  19 H3K27ac HICHIP from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference.

  Dataset EGAD50000000023

• Human skin cancer (BCC, SCC, melanoma) and healthy control skin

  Smart-seq2 single cell RNA sequencing of human BCC, SCC, melanoma (ALM) and healthy control skin samples.

  Dataset EGAD50000000540

• 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

• scRNA-seq analysis of HGSC tumors, including immune TME, before and after NACT

  Gene expression profiles of single cells from 26 tumor and ascites samples samples from 17 patients

  Dataset EGAD50000000862

• Methylation profiling of CDS and ES tumor samples

  Methylation profiling of 9 CDS and ES tumor samples, using the approach described in "Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  Dataset EGAD00010002760

• 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

• WGS and RNA-Seq data from a GBM patient PT-GB9186

  WGS and RNA-Seq data from a GBM patient PT-GB9186

  Dataset EGAD00001004237

• 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

• ADAPTeR Study: TCRseq data from ccRCC patients

  ADAPTeR study multi-region TCRseq of pre and post nivolumab tumour and PBMC samples

  Dataset EGAD00001008165

• WGS and RNA-Seq data from a GBM patient PT-AH1410

  WGS and RNA-Seq data from a GBM patient PT-AH1410

  Dataset EGAD00001004223

• WGS and RNA-Seq data from a GBM patient PT-AK7565

  WGS and RNA-Seq data from a GBM patient PT-AK7565

  Dataset EGAD00001004224

• whole genome sequencing of breast cancer cell lines and patient derived xenograft models

  whole genome sequencing of six commonly used breast cancer cell lines and six patient derived xenograft models

  Dataset EGAD00001008802

• WGS and RNA-Seq data from a GBM patient PT-GR2309

  WGS and RNA-Seq data from a GBM patient PT-GR2309

  Dataset EGAD00001004241

• Long non-coding RNA capture

  Capture lncRNA and totalRNA sequencing of various sample types (including plasma, FFPE and high quality RNA).

  Dataset EGAD00001007819

• smallRNA sequencing data from PAXgene blood from control and MCI individuals

  smallRNA sequencing from healthy individuals and MCI patients, along with phenotypic information.

  Dataset EGAD00001008153

• 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

• WGS and RNA-Seq data from a GBM patient PT-GB9483

  WGS and RNA-Seq data from a GBM patient PT-GB9483

  Dataset EGAD00001004238

• Cell line sequencing data

  SmMIP libraries using bulk cell line DNA and DNA mixes were generated in replicates and were sequenced on the NovaSeq SP platform (Illumina)

  Dataset EGAD00001007790

• WGS and RNA-Seq data from a GBM patient PT-HN6692

  WGS and RNA-Seq data from a GBM patient PT-HN6692

  Dataset EGAD00001004242

• WGS and RNA-Seq data from a GBM patient PT-BK0248

  WGS and RNA-Seq data from a GBM patient PT-BK0248

  Dataset EGAD00001004228

• WGS and RNA-Seq data from a GBM patient PT-LS4891

  WGS and RNA-Seq data from a GBM patient PT-LS4891

  Dataset EGAD00001004252

• 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

• WGS and RNA-Seq data from a GBM patient PT-AB0029

  WGS and RNA-Seq data from a GBM patient PT-AB0029

  Dataset EGAD00001004221

• WGS and RNA-Seq data from a GBM patient PT-JP2405

  WGS and RNA-Seq data from a GBM patient PT-JP2405

  Dataset EGAD00001004247

• WGS and RNA-Seq data from a GBM patient PT-LR9369

  WGS and RNA-Seq data from a GBM patient PT-LR9369

  Dataset EGAD00001004251

• Treated and control Patient Derived Xenografts of colorectal cancer (CRC) samples

  Bank of treateed and control PDXs metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001010022

• Raw sequencing data for PicoCNV and MutLX2 development papers

  Bulk tumour, germline and DigiPico WGS BAM files from patients 11611, 11615, 11619

  Dataset EGAD00001010302

• WGS and RNA-Seq data from a GBM patient PT-JB1730

  WGS and RNA-Seq data from a GBM patient PT-JB1730

  Dataset EGAD00001004245

• Whole transcriptome sequencing of untreated and castration resistant prostate cancer

  Whole transcriptome sequencing of 28 untreated prostate cancers, 13 castration resistant prostate cancers, and 12 benign prostatic hyperplasias.

  Dataset EGAD00001000609

• Exome sequencing of short SGA children with IGF-I and insulin resistance

  Exome sequencing of short SGA children with IGF-I and insulin resistance. Collaboration with Professor David Dunger, University of Cambridge. Funded by NIHR.

  Dataset EGAD00001002208

• MYC and MINCR-regulated lncRNAs in hT-RPE-MycER cells

  RNA-sequencing data from teh hT-RPE-MycER cell line after MYC activation and after MINCR knock-down in conditions of MYC ON or OFF

  Dataset EGAD00001001598

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

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

  Dataset EGAD00001011267