21206 results for "fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins The service is affordable and quick..JIZq"

in 18.47 milliseconds.

• IHEC DEEP Release August 2016

  Additional sequencing data for the German IHEC contribution (DEEP, http://deep.dkfz.de/, http://www.deutsches-epigenom-programm.de/). This is the additional data released in August 2016. Contains datatypes: - Whole Genome Bisulfite sequencing - ChipSeq (H3K27ac, H3K27me3, H3K36me3, H3K4me1, H3K4me3, H3K9me3, Input) - tRNA – not unmapped - mRNA - snRNA - Dnase Hypersensitive sites - RRBS - NOMe

  Study EGAS00001001937

• Targeted_Sequencing_of_Human_Myeloid_Malignancies

  This study involves targeted sequencing of samples from myeloid malignancies at different timepoints to assess clonal evolution of malignancya.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001289

• SAIF Alignment File

  This is the bam file generated after alignment using BWA program for the SAIF genome

  Dataset EGAD00001000249

• An_exome_sequencing_study_of_the_HIV_elite_long_term_non_progressors_and_rapid_progressors__CASCADE_cohorts_

  Background: A rare subgroup of HIV infected individuals naturally controls infection withouttreatment. These ?elite controllers? constitute an important model for the natural control ofHIV infection. Indeed, the study of these individuals may provide insights into strategies forthe development of HIV vaccines. Although several HLA and chemokine alleles are knownto be over-represented in elite controllers, only a small portion of HIV phenotypic variation isexplained by known genetic variants. The elite controller phenotype is rare and distinct,representing the extreme of an infectious disease trait. As such, this phenotype may be partlyexplained by variation in host immune control, which may be characterized by differences inrare functional genetic variants. Genomic regions underlying elite control can be potentiallyidentified by comparing the presence or frequency of variants in this group to thatrepresenting the opposite extreme. In this context, ?rapid progressors? is a group defined byits rapid immunological and clinical disease progression.Aim: To extend an existing study, in order to identify DNA sequence variants involved in thecontrol of HIV infection with greater statistical resolution. Specifically, we aim to sequence upto 200 exomes from multiple cohort studies within the EuroCoord CASCADE collaboration (acollaboration of 25 HIV seroconversion cohort studies across Europe).

  Study EGAS00001000522

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• Cutaneous Melanoma GWAS Combining Multiple Populations and Risk Phenotypes

  Most genetic susceptibility to cutaneous melanoma (CM) remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 melanoma cases (67% newly-genotyped) and 375,188 controls identified 54 significant loci with 68 independent SNPs. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with nevus count and hair colour GWAS, and transcriptome association approaches, uncovered 31 potential secondary loci, for a total of 85 CM susceptibility loci. These findings provide substantial insights into CM genetic architecture, reinforcing the importance of nevogenesis, pigmentation, and telomere maintenance together with identifying potential new pathways for CM pathogenesis.

  Study phs001868

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Dataset EGAD00001005035

• NICOLA QUB Genetic

  Blood-derived DNA was obtained from samples within the NICOLA cohort. Genetic data was generated using the Illumina Infinium CoreExome-24 array (Illumina, USA) and is available for 2,978 participants (551,839 directly genotyped and 18,148,478 imputed single nucleotide polymorphisms following initial quality control). Genetic .bed .bim and .fam files are available.

  Dataset EGAD00010002762

• Analysis of recent shared ancestry in a familial cohort identifies coding and noncoding autism spectrum disorder variants

  Autism spectrum disorder (ASD) is a collection of neurodevelopmental disorders characterized by deficits in social communication and restricted, repetitive patterns of behavior or interests. ASD is highly heritable, but genetically and phenotypically heterogeneous, reducing the power to identify causative genes. We performed whole genome sequencing (WGS) in an ASD cohort of 68 individuals from 22 families enriched for recent shared ancestry. We identified an average of 3.07 million variants per genome, of which an average of 112,512 were rare. We mapped runs of homozygosity (ROHs) in affected individuals and found an average genomic homozygosity of 9.65%, consistent with expectations for multiple generations of consanguineous unions. We identified potentially pathogenic rare exonic or splice site variants in 12 known (including KMT2C, SCN1A, SPTBN1, SYNE1, ZNF292) and 12 candidate (including CHD5, GRB10, PPP1R13B) ASD genes. Furthermore, we annotated noncoding variants in ROHs with brain-specific regulatory elements and identified putative disease-causing variants within brain-specific promoters and enhancers for 5 known ASD and neurodevelopmental disease genes (ACTG1, AUTS2, CTNND2, CNTNAP4, SPTBN4). We also identified copy number variants in two known ASD and neurodevelopmental disease loci in two affected individuals. In total we identified potentially etiological variants in known ASD or neurodevelopmental disease genes for ~61% (14/23) of affected individuals. We combined WGS with homozygosity mapping and regulatory element annotations to identify candidate ASD variants. Our analyses add to the growing number of ASD genes and variants and emphasize the importance of leveraging recent shared ancestry to map disease variants in complex neurodevelopmental disorders.

  Study EGAS00001006058

• Myocardial Infarction Genetics Exome Sequencing Consortium: Pakistan Risk Of Myocardial Infarction Study

  The Pakistan Risk of Myocardial Infarction (PROMIS) study is a retrospective multicenter case-control cohort study of individuals with and without coronary heart disease from Pakistan. Multiple biological samples have been collected from the participants including DNA, plasma, serum, and whole blood. The goal of the study is to recruit 20,000 cases and 20,000 controls of Pakistani descent. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using either Agilent's SureSelect Human All Exon Kit v2 or Illumina's ICE capture reagent; and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000917