14666 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Transcriptome sequencing of fibroblast-dependent alveolar organoids derived from patient-specific iPS cells with SFTPC^Y104H variant and their gene-corrected (monoallelic wild type SFTPC) ones.

  A disease-specific iPS cell line derived from a pulmonary fibrosis patient with SFTPC^Y104H and its gene-corrected (monoallelic wild type SFTPC) one were established. Then lung progenitor cells were differentiated from each cell line and co-cultured with human fetal lung fibroblasts to generate alveolar organoids, respectively. Alveolar epithelial cells and fibroblasts were isolated by fluorescence-activated cell sorting and each RNA was extracted. We performed transcriptome analysis of those samples by RNA-sequencing.

  Study JGAS000617

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML___part2

  Genomic libraries will be generated from total genomic DNA derived from 4000 samples with Acute Myeloid Leukaemia. Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 64 Samples will be individually barcoded and subjected to up to one lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.

  Study EGAS00001000570

• Genomic profiling of paediatric glioma cell lines

  Although paediatric gliomas resemble their adult counterparts in many ways, there appear to be distinct clinical and biological differences. One important factor hampering the development of new targeted therapies is the relative lack of cell lines derived from childhood glioma patients, as it is unclear whether the well-established adult lines commonly used are representative of the underlying molecular genetics of childhood tumours. We have carried out a detailed molecular profiling of paediatric glioma cell lines KNS42, SF188, UW479, RES259 and RES186.

  Study EGAS00001003006

• Whole genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes

  Glioblastoma (GBM) has one of the worst five-year survival rates of all cancers. While genomic studies of the disease have been performed, alterations in the non-coding regulatory regions of GBM have largely remained unexplored. We apply whole-genome sequencing (WGS) to identify non-coding mutations, with regulatory potential in GBM, under the hypothesis that regions of evolutionary constraint are likely to be functional, and somatic mutations are likely more damaging than in unconstrained regions.

  Study EGAS00001004379

• Solve-RD Solving the Unsolved Rare Dieseases

  Solve-RD – solving the unsolved rare diseases is a research project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257 from 1 January 2018 to 31 March 2024. Six European Reference Networks (ERNs; ERN-RND, -ITHACA, -EuroNMD, -GENTURIS, -RITA and -EpiCare) contributed data and samples to one or more of the four cohorts for data re-analysis and novel omics. For more information see https://solve-rd.eu/results/solve-rd-data/.

  Study EGAS00001003851

• COVID_19_Challenge_Project_Single_Cell_Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection

  Study EGAS00001005696

• The distinct DNA methylome of acute lymphoblastic leukemia

  Here, using whole genome bisulfite sequencing (WGBS) data of over one hundred patients from multiple subtypes of acute lymphoblastic leukemia (ALL), controls samples and ALL cell lines, we show that in contrast to the prevailing paradigm, ALL samples exhibit CpG island hypermethylation but little to no global loss of methylation. The subtype-specific CpG island hypermethylation levels in T cell ALL span a broad range of methylation levels rather than previous binary classifications and are influenced by multiple factors, including TET2 expression.

  Study EGAS00001005203

• Acquiring and sequencing of all 24 single human chromosomes

  Haplotype phased whole genome sequencing of individuals is a technical challenge when family members are unavailable for determining chromosome of origin and variant linkage. Completely phasing genome sequences with single chromosomes has been shown to be feasible however amplifying all the single chromosomes for subsequent whole genome sequencing has been proposed but not performed to date. We acquired single chromosome of one of each of the autosomes and sex chromosomes to assess the feasibility of this sequencing library template preparation process.

  Study EGAS00001003300

• Security Overview

  Security Overview The European Genome-phenome Archive (EGA) houses consented human data under controlled access. Access decisions are handled by the relevant Data Access Committee (DAC), which autonomously manages requests through the DAC Portal. This document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. As security is a prime concern of the EGA, the EGA is a member of the Global Alliance for Genomics and Health (GA4GH) Data Security work stream. The EGA contributes and helps develop the recommendations outlined the GA4GH Security Technology Infrastructure document, which defines guidelines, best practices, and standards for building and operating an infrastructure that promotes responsible data sharing in accordance with the GA4GH Privacy and Security Policy. Explore the EGA dataflow to gain deeper insights! Accessing data in the EGA involves several steps. First, users need to create an EGA account. Once logged in, they can request access to data controlled by a DAC through the EGA website (see documentation). The DAC oversees these requests through the DAC Portal, and if approved, grants the necessary permissions to the user's EGA account, allowing them to access and download all relevant data and metadata for the requested dataset(s). The key points of EGA security strategy are: 1 Regular Risk Assessment The EGA regularly identifies and assesses risk related to the following: Breach of confidentiality,Breach of privacy or autonomy,Malicious or accidental corruption or destruction of data archived at EGA,Disruption of services provided by the EGA. 2 Risk mitigation The EGA implements and maintains safeguards to minimise the risks identified above in accordance with the 6 control objectives listed in Appendix 1 and outlined in the GA4GH Security and Infrastructure document.If a breach is discovered, the EGA applies a defined protocol to minimise damage. 3 Identity and authorisation management The EGA authenticates the identity of individuals or software accessing controlled access data held at the EGA.The EGA ensures an appropriate level of assurance (LoA) is applied to the identity consistent with the risk associated with that individual, such as multi-factor authentication for DACs.The EGA provides the minimum access rights and privileges consistent with the user’s identity, allowing access consistent with the GA4GH Privacy and Security Policy, as determined by the appropriate DAC. 4 Audit Logs The EGA maintains a set of logs recording: Changes to user access rights,Data access requests,Resource usage. 5 Cryptography, communication security, and data integrity The EGA ensures data transmission integrity using a hash function.All data transmitted to or from the EGA is end-to-end encrypted.All data at EGA is stored using strong encryption.Encryption keys are not stored in the same system as the encrypted data.All data archived at EGA must be accompanied by a signed submission statement ensuring appropriate consent or ethical approval has been obtained, and is in accordance with all applicable laws and regulations. The EGA has a defined protocol defining the response in the event of a security breach, and is continuing to work with the GA4GH Data Security Work Stream to help define best practice and associated standards for breach responses. Appendix 1 GA4GH Control Objectives Control Objective 1: Implement technology safeguards to minimise the risk of unauthorised access, use, or disclosure of confidential and private data.Control Objective 2: Implement technology safeguards to minimise the risk of discovery, access, and use of individuals’ clinical and genomic data, and individual identities, other than as authorised by applicable jurisdictional law, institutional policy, and individual consents.Control Objective 3: Implement technology safeguards to minimise the risk of accidental or malicious corruption or destruction of data.Control Objective 4: Implement technology safeguards to minimise the risk of disruption, degradation, and interruption of services enabling access to data.Control Objective 5: Implement technology safeguards to minimise the risk of potential security attacks and misuse of authorised accesses and privileges.Control Objective 6: Implement technology safeguards to promptly detect the failure to attain the above control objectives and to respond with proper countermeasures.Appendix 2Refer to the document below to learn more about EGA long-term data preservation policy and procedures at EMBL-EBI.Long-term data preservation

  Documentation about/security

• Exploring the Genomic Dark Matter of Neurodevelopmental Disorders

  Neurodevelopmental Disorders (NDDs) are a group of disorders that typically manifest early in development and may give rise to impaired cognition, communication, adaptive behavior, and psychomotor skills. This study aims to take a more comprehensive view into the genomic landscape of structural variants implicated in NDDs with intellectual disability (ID). We have evaluated the genome of families with a genetically unsolved severe NDD via optical genome mapping. This study identified likely pathogenic or pathogenic structural variants in known NDD genes, including BCL11A, OPHN1, PHF8, SON, and NFIA. Data is available in VCF format, following the standard filtering settings in Bionano Access and available as "variants_combine_filters_inMoleRefine1.vcf" files.

  Study phs002937