14538 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Single nucleus RNA sequencing of squamous cell carcinoma arising from mature teratoma of the ovary

  Squamous cell carcinoma arising from mature teratoma is one of the rare ovarian cancers. Therefore, the detailed molecular background of this disease has not been elucidated. The purpose of this study is to investigate the single-cell transcriptional landscape of this disease.

  Study JGAS000521

• Papua New Guinean Genome Diversity Project

  Papua New Guinean populations have one of the highest genetic diversity of the world. Our dataset provides genomic data covering most of the Papua New Guinean territory (n=58).

  Study EGAS00001005393

• DAC Portal documentation

  DAC Portal Welcome to the DAC Portal documentation! If you are involved in governance or legal aspects, technical or operational aspects, or serving as a data steward, this page will be helpful for you. By exploring these materials, you can define your own Data Access Committee (DAC) and policies, understand the minimal requirements for a DAC and a policy object, and comprehend how the EGA data access requests are managed. DAC Portal Index Setting up your account DACs and Policies Pending Request table Manage Data Requests History page Audit your DACs, policies, and datasets Deprecation User Preferences DAC API - A programmatic approach Setting up your account Register yourself as an EGA user. The Helpdesk team will validate your account (this could take up to 48 hours). After validation, you will receive an email with a link to verify your email - Make sure you click on the link to verify your account! If you don’t receive the email, please check your spam folder. Once your account is active you can login to the DAC Portal. We recommend you to check out the Take The Tour! DACs and Policies Create a DAC Click on Create a DAC Add the title and description to your DAC. Once ready, click on the ‘Create’ button. You will have to wait until the Helpdesk Team validates the creation of your DAC. Once approved by Helpdesk, your DAC will be assigned with a persistent identifier (EGAC). Edit a DAC Once your DAC is registered and approved, you can edit it and add contacts. Remember, you can add as many contacts as needed. And, you can also remove/add contacts anytime. To add a contact, you must write the username or email of a registered EGA user in the Members field. Once you have typed the whole username or email, a drop-down menu will appear where you can select the contact. Select a contact from the drop-down menu. Make sure you write the full username or email of the contact so it appears as an option. Make sure that you select one main contact. Set up the role you want to grant to the new contact of the DAC. We recommend you to check out the FAQ to learn more about the different roles! After adding all the necessary contacts and assigning roles, click on Update. This will send an email notification to the new DAC member, letting them know about the invitation to managing the DAC. Once they log into the DAC Portal, they will be able to either accept or turn down the invitation. Create a policy First, please note that all information registered in a policy metadata object will be publicly available on the EGA website. For each released dataset, all users will be able to read the policy under the “Data Access” tab. Select Create a Policy from the Policies tab. Select the DAC that you want your policy to depend on. Add the title and terms and conditions for accessing and using your data. If you already have an external website for data access requests, you can add the URL directly here (see example here). You can find a template of a Data Access Agreement (DAA) document in our Policy documentation page. The DAA template is provided for guidance only and should be adapted to suit your own purpose depending on the security policies, terms for publication or embargoes, and restrictions on data use or sharing. You can also add Data Use Ontologies (DUO) to your policy. These DUO codes are used to semantically tag the terms and conditions of using the data linked to the policy (example). For more information, you can refer to the Data Uso Ontology documentation. Once completed, make sure to click the Create button in order to register your policy. A persistent identifier (EGAP) will be assigned automatically. Edit a policy Please, note that you will not be able to edit the policy if it shows in orange. Meaning that you are a member of the DAC linked to that policy. Members don’t have edit rights. Only admins can edit objects. You can check your registered policies on My policies, available at the menu in the top-right corner. Select your policy. It will then display the information of that policy, allowing you to edit the information. Once you are done with the modifications, click Update. Pending Requests Table Table Settings Upon selecting a specific DAC, you will be presented with a customisable table showcasing all pending data access requests. This table allows you to tailor the displayed information according to your preferences by selecting desired columns. Available Columns (Displayed with the Eye Icon): Date: The date when the data access request was submitted. Full Name: Name and surname of the user submitting the request. Email: Email address associated with the user's request. Username: The username linked to the EGA account of the user submitting the request. Organisation: Affiliated organisation of the user submitting the request. Dataset: EGA accession ID for the requested EGA dataset. Dataset Title: Title of the requested dataset. DAC Comment: Space provided for internal comments related to the request. Expiration: Option to specify an expiration date for granted permissions. Check more information on the pending request table here! Table Filters By default, all data access requests are displayed. However, you have the option to apply filters to refine your view. Follow these steps to apply filters: Click on the More button. This action will reveal the different columns available for applying filters. As you select columns, the checked fields will be displayed at the top of the request table. Choose the specific values within the selected columns that you want to filter for. Click the Search button to apply the selected filters. Do you find yourself frequently applying the same filters? You can save multiple combinations of filters for easy access at any time! Here's how: Click the Save button. Provide a descriptive name for the filter combination. Click Save to confirm. To load saved filters, simply select the saved filter from the dropdown menu to apply it automatically. Check more information on filters here! Advanced Search For users requiring more granular control over their data access requests, the DAC Portal offers an Advanced Search feature using JIRA Query Language (JQL). With JQL, you can craft precise and complex queries to filter and retrieve specific data access requests based on various criteria such as date, user details, dataset attributes, and more. Using JQL's flexibility, you can create custom queries to meet your specific needs, allowing for advanced filtering options beyond the standard filters provided. You can find the Advanced Search feature following these steps: Click the … button Select Advanced To view the allowed fields for filtering and explore all available options, simply click on the info icon. Once you have written the filtering values, click the Search button to apply. Check more information on filters here! Manage Data Requests Upon logging into the DAC Portal, you'll notice a sand clock icon next to the DAC ID, indicating the number of pending requests. Click on the DAC to review these requests. Accept requests Click on the right side of the toggle button to grant access to the user. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with granting permissions. Deny requests Click on the left side of the toggle button to deny access to the user. Provide a reason for the denial. Note that the user will receive an email with this reason. Click on the Done button. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with denying permissions. Tips! Apply a filter to view all requests to be managed at once. Use the toggle in the row with column names to grant or deny permissions for multiple requests simultaneously. You can grant and deny permissions in the same action, simplifying the process. The confirmation box will provide a summary of all actions, including grants, denials, DAC comments, and expiration dates. History Page The History page serves as a dedicated space to view information regarding all requests managed by all DAC members. Here, you can review active permissions and revoke them as needed. Go to the History page by clicking on the "HISTORY" button from a DAC page in the DAC Portal. Here are the different row types you may find: Current permissions: row in green with a toggle button to revoke permissions on the right. Approved requests: row in green, with no toggle button. Request denied: row in red with “request denied” on the right. Permission revoked: row in red with “permission revoked” on the right. Distinctions to Note! Between Request Denied and Permission Revoked: Request Denied: Refers to requests that were rejected from the outset, indicating that access to the dataset was never granted. Permission Revoked: Indicates that permissions were previously granted but have since been revoked. Users with permissions revoked have previously accessed the dataset. Between Approved Request and Current Permissions: Approved Request: Represents an entry when a data access request has been approved in the past. Current Permissions: Denotes ongoing permissions where a user has present access to the dataset. An approved request may now appear as Permission Revoked in the present. By observing these different rows, users can gain insight into the complete history of a user's interactions and permissions regarding a dataset over time. To revoke access to a specific user for a dataset, follow these steps: Go to History page Look for the row with the specific permissions. You can use the filters! Click on the toggle button to revoke access. Add a denial reason. Bear in mind that the requester will receive the denial reason! Click on the Apply button. Check more information on the Hisotry page here! Audit your metadata objects In the DAC Portal, you can efficiently manage and audit various metadata objects pertinent to your role as a Data Controller. Upon accessing the DAC Portal, you will encounter three primary tabs on the homepage: DAC: Contains information about Data Access Committees (DACs). Policies: Provides insights into linked policies. Datasets: Displays datasets and relevant details. Within each tab, you'll find a comprehensive list of the objects you manage, these being grouped by type (DAC, Policies, Datasets), as well as by your role (member/admin). Whilst the lists give you a quick look, to check how things are connected, we've added a table at the bottom DACs and policies. DACs Let’s check which policies are linked to a specific DAC: Go to "My DACs." Select a DAC. Click on "EDIT" to see more details. You are now on this page: Scroll down to see the linked policies. Click on “List of linked policies of this DAC” and you will see a list of all policies linked to your selected DAC. Policies Do you want to view a list of datasets connected to a particular policy? Follow the same steps mentioned earlier, but head to the policy tab this time. In the policy tab, you'll find a list of all your policies. Here, you may notice two different icons next to the policy ID (EGAP): DAC Icon (): This represents the DAC. Hover your mouse over the icon to see the DAC ID. Dataset icon (): This indicates datasets falling under that policy. The number next to the icon tells you how many datasets are linked to the policy. For example, if you see "2" next to the icon, it means there are two datasets linked to that policy. If you want to check the linked datasets and their relevant information, simply click on a specific policy. You'll then find the "List of linked datasets of this policy" at the bottom of the page. Datasets Finally, in the dataset tab, by default you will see a list of all the datasets you can manage with all your DACs and policies. Yet, we've included two handy ways to organise them: DAC vs. policy: You can group by datasets, either by DAC or policy. Released vs. unreleased: You can sort out datasets based on their release status. Feel free to experiment with both options! For instance, if you want to see which DACs have unreleased datasets, simply select DAC and unreleased, and you'll get the details you need! Deprecation Do you have a bunch of metadata objects like DACs and policies that you don’t need anymore? This section shows you how to get rid of them! But what does "deprecation" mean for EGA? It's basically changing the status of a metadata object to "deprecated," which means we won't be using it in the future. In simple terms, it's like saying these objects are no longer useful. However, because we believe in making metadata FAIR, once an object has a persistent identifier, we can't just delete it. So, instead of deleting, we deprecate it. Here's a helpful tip! If you want to make a metadata object disappear from the DAC Portal, deprecate it. You won’t see it in the portal anymore! Let’s say you want to deprecate a DAC. Let’s do it! Go to "My DACs." Select a DAC. Click "EDIT" to see more details. You are now in this page: Click on the Deprecate button It will then appear a message. There are two options here: Your DAC is not linked to any policy, hence it’s ready to be deprecated. Click on “Yes. Confirm” to deprecate your DAC object! Your DAC is linked to at least one policy, and you need to either: Deprecate the linked policy first, or Link the policy to a different DAC Now, let’s say you don’t want to get rid of the policy altogether, but you want to change the DAC it’s linked to. Here's how: Go to the policy tab. Find the policy you want to change (for example, EGAP50000000019). Choose a new DAC to link it to. Click on Update. See the Edit Policy section for more details. After ensuring that the DAC we want to deprecate isn’t linked to any policy, return to the "My DACs" section and follow the steps outlined previously. This will lead you to a confirmation message. You can only deprecate DACs and Policies. To deprecate a dataset, please contact our Helpdesk team. Check more information on how deprecation works here! User Preferences We have implemented email notifications in the DAC Portal. Here’s the complete list: DACs: Pending requests Approved by Helpdesk Rejected by Helpdesk DAC Invitation Requesters: Data access request approved Data access request denied Permissions revoked Upcoming expiration date As a DAC member, you will be able to decide whether you want to receive the DAC notifications or not. For that, go to the top-right corner menu, select User Preference. You will be able to decide whether you want to receive notifications for: Approved by Helpdesk Rejected by Helpdesk DAC Invitation For pending requests, you will be able to select how often do you want to receive the notification: Daily Weekly Fortnightly As a DAC member, you are responsible for managing data access requests. Consequently, you will receive notifications for pending requests. If you prefer not to manage these requests, please arrange to be removed as a contact for your DAC. Here's a tip! Do you have a pending request that you don’t want to receive a notification? Add a DAC comment! The EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! DAC API - A programmatic approach In addition to the new DAC Portal, we are excited to announce the release of the DAC API. This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can click the button below. Check out the DAC API specification!

  Documentation access/data-access-committee/dac-portal

• Nyamasati study access committee

  Dac EGAC00001001028

• OMKar Study Data Access Committee

  Dac EGAC00001003581

• WES of der(1;7)(q10;p10) myeloid neoplasms

  The study examined WES of der(1;7)(q10;p10) myeloid neoplasm cases. BAM files of WES of 26 myeloid neoplasm patients with der(1;7)(q10;p10) were used to identify key driver genes in patients with der(1;7)(q10;p10). This study is one of the largest WES for der(1;7)(q10;p10)(+) myeloid neoplasm cases.

  Study EGAS50000000704

• CIDR: The Role of Rare Coding Variation in Prostate Cancer in Men of African Ancestry - RESPOND Project 2

  In RESPOND Project 2, we seek to identify rare genetic factors that are associated with prostate cancer (PCa) risk and aggressiveness in men of African ancestry (AA). We will conduct exome sequencing of 15,000 prostate cancer cases and 5,000 controls from the RESPOND cohort and the African Ancestry Prostate Cancer Consortium (AAPC) with cases selected based on risk categories: high-risk (stage T3/T4 or Gleason 8+ or PSA>20 ng/ml), intermediate-risk (stage T2b/T2c or Gleason 7 or PSA 10-20 ng/ml) and low-risk disease (stage T1/T2a and Gleason ≤ 6 and PSA<10 ng/ml). We expect the findings from this Project to significantly advance knowledge of susceptibility to aggressive PCa and racial/ethnic disparities in PCa risk, and to guide the development of future preventive, early detection and prognostic measures for AA men. The first phase of the study will include exome sequence data for approximately 7,500 cases and 5,000 controls from AAPC. The second phase of the study will include exome data for 5,000 cases from RESPOND and AAPC.ACKNOWLEDGMENTS and CONTRIBUTING SITES Multiethnic Cohort (MEC): The MEC and the genotyping in this study were supported by National Institutes of Health (NIH) grants CA63464, CA54281, CA1326792, CA148085, and HG004726. Cancer incidence data for the MEC and Los Angeles Study of Aggressive Prostate Cancer (LAAPC) studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with federal funds from the National Cancer Institute (NCI)/NIH/Department of Health and Human Services (DHHS) under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the Centers for Disease Control and Prevention (CDC). Ghana Prostate Study (GPS): The Ghana Prostate Study was funded by the Intramural Program of the NCI/NIH/DHHS under Contract No. HHSN261200800001E. Men of African Descent and Carcinoma of the Prostate (MADCaP): We thank all MADCaP study participants. This work is a product of the MADCaP network. This work was supported by NCI/NIH grant U01CA184374 to Timothy Rebbeck and National Institute of General Medical Sciences (NIGMS) MIRA grant R35GM133727 to Joseph Lachance. Additional funding includes a seed grant from the Integrated Cancer Research Center at Georgia Institute of Technology. UGANDA: The UGANDA study was supported by NIH grant R01CA165862. Southern Community Cohort (SCCS) is funded by NIH grant CA092447. SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt Ingram Cancer Center (CA68485). Data on SCCS cancer cases were provided by Alabama Statewide Cancer Registry, Kentucky Cancer Registry, Office of Cancer Surveillance at Tennessee Department of Health, Florida Cancer Data System, Central Cancer Registry at North Carolina Division of Public Health, Georgia Comprehensive Cancer Registry, Louisiana Tumor Registry, Mississippi Cancer Registry, South Carolina Central Cancer Registry, Virginia Cancer Registry at Virginia Department of Health, and Cancer Registry at Arkansas Department of Health. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries (NPCR)/Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the NPCR/CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. Karuprostate: The Karuprostate study was supported by the French National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la Prostate. Séverine Ferdinand, Marc Romana. The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. We would also like to acknowledge the UNC BioSpecimen Facility and the LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). Gene-Environment Interaction in Prostate Study (GECAP) was supported by NIH grant ES011126. King County Prostate Cancer Study (KCPCS) was supported by NIH grants CA056678, CA082664, and CA092579, with additional support from the Fred Hutchinson Cancer Research Center. We thank the participants in these studies, and Ms. Suzanne Kolb for help with study management. The Los Angeles Study of Aggressive Prostate Cancer (LAAPC) was funded by grant 99-00524V-10258 from the Cancer Research Fund, under Interagency Agreement #97-12013 (University of California contract #98-00924V) with the Department of Health Services Cancer Research Program. Cancer incidence data for the MEC and LAAPC studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with Federal funds from the NCI/NIH/DHHS under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the CDC. Prostate Cancer Studies at MD Anderson (MDA) was supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388.

  Study phs002637

• Whole-Genome Sequencing (WGS) of a Malignant Granular Cell Tumor (GCT) with Metabolic Response to Pazopanib

  We report one case study of a malignant granular cell tumor patient with metabolic response to pazopanib. In this study, we used whole-genome sequencing of the tumor with the matched blood to characterize the somatic mutation profile in this tumor. This is the first reported whole-genome sequencing study of the rare malignant granular cell tumor.

  Study phs000978

• Phase 2 Study of Nivolumab and Entinostat in Unresectable or Metastatic Cholangiocarcinoma and Pancreatic Adenocarcinoma

  The study was a single-center, open-label, phase II trial (registration no. NCT03250273) designed to evaluate the efficacy of entinostat in combination with nivolumab in patients with advanced pancreatic ductal adenocarcinoma (PDAC). The aim was to assess the objective response rate using RECIST v1.1 criteria as the primary endpoint. A total of 27 patients with advanced PDA were enrolled from November 2017 to November 2020. Their treatment involved a 14-day lead-in with entinostat monotherapy, followed by a combination with nivolumab. The study utilized several molecular technologies to assess immune profiles and tumor microenvironment (TME) changes: high-dimensional mass cytometry by time of flight (CyTOF), Luminex for chemokine analysis in plasma, multiplexed immunohistochemistry (mIHC), image cytometry-based quantification, bulk RNA sequencing analysis. The objective response rate (ORR) was 11% with three patients showing a partial response (PR). The median duration of response was 10.2 months. Grade ≥ 3 treatment-related adverse events (TRAEs) occurred in 63% of patients, with the most common being decreased lymphocyte count, anemia, hypoalbuminemia, and hyponatremia. Gene expression analysis showed an enrichment in inflammatory response signaling pathways with the combination treatment. RNA sequencing data with clinical and demographic patient information will be available through dbGaP. For expression summaries, please refer to GEO submission GSE248014.

  Study phs003615

• Lipodystrophy study Data Access Committee

  Dac EGAC00001000997

• PIVUS Study Data Access Commitee

  Dac EGAC00001001170

• Study EGAS00001005054 Data Access Committee

  Dac EGAC00001002066

• MBL2 study data access committee

  Dac EGAC00001002678

• ORIENT study Data Access Commitee

  Dac EGAC00001002940

• PEDS-PLAN - Pediatric Precision Laboratory Advanced Neuroblastoma Therapy

  A multi-center clinical trial for newly diagnosed high-risk neuroblastoma patients. Molecular tumor boards selected one of six targeted agents based on tumor-normal whole exome sequencing and tumor RNA sequencing data.

  Study phs002303

• Whole Genome Sequencing of hiPS cells

  Human induced pluripotent stem (hiPS) cells hold great promise for regenerative medicine. Safety issues of use of hiPS cells however remain to be addressed. One of such issues is mutations derived from somatic donor cells and introduced during genome manipulation. We sequence whole genomes of hiPS cells and analyzed mutations. Our study brings hiPS cell technology one step closer to application to regenerative medicine.

  Dataset EGAD00001000362

• Idiosyncratic and generic single nuclei and spatial transcriptional patterns in papillary and anaplastic thyroid cancers

  Thyroid cancer is the most common endocrine malignancy. This dataset encompasses two types of thyroid cancer : anaplastic which is the most de-differentiated and aggressive one, and papillary which is the most common one. We profiled 14 patients, including 10 papillary and 4 anaplastic thyroid carcinomas, using both single nuclei RNA sequencing and spatial transcriptomics to link single cell resolution RNA sequencing with tissue morphology and better understand inter and intratumoral thyroid cancer heterogeneity.

  Study EGAS00001007574

• Analysis of Epigenomes and Genome Topology in Colorectal Cancer

  When diagnosing cancer, pathologists use nuclear morphology as a hallmark of tumor cells, but the topological changes linked to alterations in the shape of the nucleus were poorly understood. To uncover the molecular changes that occur in the 3D structure of cancer genomes, we integrated topological maps for colon tumors and normal colon tissues with epigenetic, transcriptional, and imaging data. We characterized tumor-associated changes in chromatin loops, topologically associated domains (TADs), and large-scale compartments. We found that chromatin loop rewiring contributes to oncogenic gene expression programs. Whereas TAD structures are largely stable, the spatial partitioning of the open and closed genome compartments is compromised in tumors and is accompanied by hypomethylation and histone mark rearrangements. We also identified a compartment that is reorganized in tumors and is at the interface between the canonical A and B compartments. Similar changes were evident in non-malignant cells that had accumulated excessive cellular divisions. Our analyses suggest that these compartment changes repress stemness and invasion programs while inducing immunity genes, and they may therefore restrain malignant progression.

  Study phs002288

• Efficacy and safety of entrectinib in patients with ROS1-positive advanced/metastatic non-small cell lung cancer (NSCLC) from the Blood First Assay Screening Trial (BFAST)

  BFAST is a global, open-label, multicohort trial that evaluates the efficacy and safety of multiple therapies in patients with advanced/metastatic NSCLC and targetable alterations, identified by blood-based molecular testing. We present data from Cohort D (ROS1-positive). Patients ≥18 years old with stage IIIB/IV, ROS1-positive NSCLC detected by blood-based testing, received entrectinib 600 mg daily. At data cut-off (November 2021), 55 patients were enrolled and 54 had measurable disease. Cohort D met its primary endpoint; the confirmed objective response rate (ORR) by investigator was 81.5% which was consistent with the ORR from the integrated analysis of entrectinib (investigator-assessed ORR: 73.4%, data cut-off May 2019, ≥12 months follow-up). The safety profile of entrectinib was consistent with prior reports. These results demonstrate consistency with those from the integrated analysis of entrectinib in patients with ROS1-positive NSCLC identified by tissue-based testing and support the clinical value of blood-based testing to inform clinical decision-making.

  Study EGAS50000000105

• Circulating, Cell-Free DNA Methylation Patterns Indicate Cellular Sources of Allograft Injury after Liver Transplant

  Post-transplant complications reduce allograft and recipient survival. Current approaches for detecting allograft injury non-invasively are limited and do not differentiate between cellular mechanisms. Here, we monitor cellular damages after liver transplants from cell-free DNA (cfDNA) fragments released from dying cells into the circulation. We analyzed longitudinal blood samples collected from patients at different time points after transplant. Sequence-based methylation of cfDNA fragments were mapped to an atlas of cell-type-specific DNA methylation patterns derived from 476 methylomes of purified cells. For liver cell types, DNA methylation patterns and multi-omic data integration show distinct enrichment in open chromatin and regulatory regions functionally important for the respective cell types. We find that multi-tissue cellular damage post-transplant recovers in patients without allograft injury during the first post-operative week. However, sustained elevation of hepatocyte and biliary epithelial cfDNA within the first month indicates early-onset allograft injury. Further, cfDNA composition differentiates amongst causes of allograft injury indicating the potential for non-invasive monitoring and timely intervention.

  Study phs003610

• Relation between transcriptome, karyotype and age in cases of sex chromosome aneuploidies.

  Why women live longer than men is still an open question in human biology. Sex chromosomes have been proposed to play a role in the observed sex gap in longevity, and the Y male chromosome has been suspected of having a potential toxic genomic impact on male longevity. It has been hypothesized that transposable element (TE) repression declines with age, potentially leading to detrimental effects such as somatic mutations and disrupted gene expression, which may accelerate the aging process. Given that the Y chromosome is rich in repeats, age-related increases in TE expression could be more pronounced in males, likely contributing to their reduced longevity compared to females. In this work, we first studied whether TE expression is associated with the number of sex chromosomes in humans. We analyzed blood transcriptomic data obtained from individuals of different karyotype compositions: 46,XX females (normal female karyotype), 46,XY males (normal male karyotype), as well as males with abnormal karyotypes, such as 47,XXY, and 47,XYY.

  Study EGAS50000001009

• Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

  Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n=17) and DNA methylation (whole-genome bisulphite sequencing, n=10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

  Study EGAS00001002592

• Relation between transcriptome, karyotype and age in cases of sex chromosome aneuploidies.

  Why women live longer than men is still an open question in human biology. Sex chromosomes have been proposed to play a role in the observed sex gap in longevity, and the Y male chromosome has been suspected of having a potential toxic genomic impact on male longevity. It has been hypothesized that transposable element (TE) repression declines with age, potentially leading to detrimental effects such as somatic mutations and disrupted gene expression, which may accelerate the aging process. Given that the Y chromosome is rich in repeats, age-related increases in TE expression could be more pronounced in males, likely contributing to their reduced longevity compared to females. In this work, we first studied whether TE expression is associated with the number of sex chromosomes in humans. We analyzed blood transcriptomic data obtained from individuals of different karyotype compositions: 46,XX females (normal female karyotype), 46,XY males (normal male karyotype), as well as males with abnormal karyotypes, such as 47,XXY, and 47,XYY.

  Study EGAS00001007462

• Whole Exome and Whole Genome Profiling as well Genome-Wide Methylation Profiling from Early to Advanced Chronic Lymphocytic leukemia (CLL), Genome-Wide Methylation Profiling in Monoclonal B Cell Lymphocytosis (MBL)

  Serial whole exome sequencing of samples collected from 21 patients at multiple time points during progression from early to late chronic lymphocytic leukemia (CLL) and one matching non-tumor tissue sample from each patient. Additional whole genome sequencing of samples from 3 selected patients. Genome-wide B cell methylation compared between 5 healthy donors from the same age group as patients, 20 patients with monoclonal B cell lymphocytosis and in serial CLL samples with matching whole exome sequencing. Moreover, genome-wide single-cell RRBS-profiling of B cells from one healthy donor and from one patient with CLL was performed using a protocol newly developed by the A. Meissner group.

  Study phs001431

• A Case Controlled Etiologic Study of Sarcoidosis (ACCESS-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from (ACCESS) include Bronchial Lavage, DNA, Peripheral Blood Mononuclear Cells, and Plasma. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: To determine the etiology of sarcoidosis by establishing a case control, multi-center study. In addition to etiology, this study also sought to examine socioeconomic variables and the clinical course of patients with sarcoidosis, including quality of life.Background: Sarcoidosis is a chronic granulomatous disorder of unknown cause that is characterized by activation of T-lymphocytes and macrophages. For many years, sarcoidosis was presumed to be an atypical manifestation of tuberculosis because of the similarity between the inflammatory responses of the two diseases. However, as culture techniques became more widely employed to diagnose tuberculosis and it became less common, it became clear that sarcoidosis was not simply a variation of tuberculosis. Data on the etiology of sarcoidosis have come from diverse sources: in clinical investigations, alveolitis has been found to precede granulomatous inflammation; in case control studies, familial aggregation has been identified; and in case reports, recurrence of granulomatous inflammation has been observed after lung transplantation. The cause may not prove to be a single, known exposure. Interactions of exposures with genetic dispositions could have important implications for our understanding of immune responses as well as the pathogenesis of sarcoidosis.Participants: 736 participants with sarcoidosis enrolled within 6 months of diagnosis from 10 clinical centers in the U.S. Using the ACCESS sarcoidosis assessment system, organ involvement was determined for the whole group and for subgroups differentiated by sex, race, and age (Conclusions: The initial presentation of sarcoidosis is related to sex, race and age, and it tends to remain stable over two years in the majority of patients. The etiology is probably multifactoral with both genetic and environmental factors contributing.Specimen Details: The PBMC for this study are pelleted and suspended in guanidinium-based solution and are nonviable.

  Study phs004276

• Joslin Study on the Genetics of Type 2 Diabetes

  Between 1993 and 2003, families were recruited in the Joslin Study on the Genetics of Type 2 Diabetes for the presence of an autosomal dominant mode of inheritance of diabetes. Recruiting and screening of families occurred through probands who were receiving medical care at the Joslin Clinic (Boston, MA). Screening of families included 1) a proband and at least one sibling with type 2 diabetes, 2) diabetes occurring in at least three generations, 3) diabetes inherited on one side of the prospective family. Probands had to have a diabetes diagnosis between the age range from 10 to 60 years. Demographic data, clinical data, and family history were collected from participating family members, along with blood and urine samples. This study includes genetic and phenotypic data from one family examined in Simeone, Wilkerson, et. al. (NPJ Genomic Medicine 2022, PMID: 35869090). Genotype data for 14 family members and whole genome sequencing data for 6 individuals were generated with the goal of identifying a potential genetic cause of disease in this family. To de-identify this family and protect confidentiality, information on sex in phenotype data and variants identified in X, Y, and MT chromosomes have been removed in compliance with IRB guidelines.

  Study phs002959

• ALI-RSV study Data Access Commitee

  Dac EGAC00001003371

• Data access commitee to DAISY study

  Dac EGAC00001003031

• Leiden Longevity Study Data Access Committee

  Dac EGAC00001000210

• STREP GENE Study Data Access Committee

  Dac EGAC00001001107

• Probiotic Study Team Data Access Committee

  Dac EGAC00001001168

• Asthma Remission Study Data Access Committee

  Dac EGAC00001001258

• Asthma Remission Study Data Access Committee

  Dac EGAC00001001261

• SI-NET study data access committee

  Dac EGAC00001002004

• IVF Retrospective Study Data Access Committee

  Dac EGAC00001002319

• Data Access Committee for Massim study

  Dac EGAC00001002522

• Human Liver Study Data Access Commitee

  Dac EGAC00001003020

• Islet RFX6 Study Data Access Committee

  Dac EGAC00001002684

• Pediatric B-cell precursor acute lymphoblastic leukemia samples with very early relapse

  In this study we performed a genomic analysis of diagnosis-relapse pairs of 12 children who relapsed very early, followed by a deep-sequencing validation of all identified mutations. In addition, we included one case with a good initial treatment response and on-treatment relapse at the end of upfront therapy.

  Study EGAS00001005615

• MutationalPatterns2: The one stop shop for the analysis of mutational processes: DNA repair deletions

  Study EGAS00001004789

• Data Access Commitee to XP skin study

  Dac EGAC00001002945

• TB-DAR Study Data Access Commitee

  Dac EGAC00001002440

• TRACERx Pilot Study Data Access Committee

  Dac EGAC00001000198

• EXCEED Study Data Access Commitee

  Dac EGAC00001001139

• Osteosarcoma Study HD Data Access Commitee

  Dac EGAC00001001337

• The Jerusalem Perinatal Study (JPS) data access committee

  Dac EGAC00001001421

• South African Ethnographic study data access committee

  Dac EGAC00001001613

• Data access commitee to RUBY study

  Dac EGAC00001001775

• BAMI Platelet Sub-study Data Access Committee

  Dac EGAC00001001850

• Mechanisms of patient response to Dabrafenib in Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)*NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]*CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Dataset EGAD00001001375