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• MultiOMICS study of a pair of infant monozygotic twins with concordant B-cell ALL (WGBS)

  B-cell acute lymphoblastic leukemia (B-cell ALL) is the most common cancer in childhood. Studying identical twins with B-cell ALL provides a unique and tractable model for deciphering the developmental timing of pre- and post-natal mutations contributing to clonal evolution. To date, this has mainly focused on major cytogenetic subgroups of childhood B-cell ALL, including MLL fusions, ETV6-RUNX1, hyperdiploidy, and BCR-ABL1. However, formal demonstration of the prenatal origin and “backtracking” the natural history of the leukemia remains understudied in “B-other”/Normal Karyotype (NK) B-cell ALL. To characterize the epigenetic landscape of this particular leukemia subtype, we performed DNA bisulfite-sequencing on a pair of 8-month-old monozygotic twins diagnosed with concordant “B-other”/NK B-cell ALL.

  Dataset EGAD00001005018

• Exome sequencing of thyroid disease in Val Borbera

  The Val Borbera is a region characterized by low iodine and high prevalence of thyroid disorders, the commonest endocrine disorders in the general population. About 30% of the participants of the Val Borbera Project were affected by such disorders and were characterized by several parameters, TSH level, anti TPO antibodies, echography, family origin. Individuals with extreme phenotypes were identified and could be clustered based on family origin and genotype. We propose to exome sequence 6 of them, affected with true goiter, at high dept (40-60x) to obtain information on exonic rare variants. Due to the family structure and to the availability of whole genome sequence information on 110 individuals from the isolated population we expect to be able to identify putative causative variants for thyroid disorders that may be studied in the remaining affected individuals.

  Dataset EGAD00001000729

• Molecular underpinnings of dedifferentiation and aggressiveness in chromophobe renal cell carcinoma

  This study expands our understanding of aggressive chromophobe renal cell carcinoma (ChRCC), provides insight into molecular mechanisms of tumor progression, and informs pathologic classification and diagnostics. Tumor and adjacent normal samples were collected from 11 patients treated in affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital. Seven of the eleven patients consented to depositing their genomic data to public repository.

  Study EGAS50000000287

• Clonal Evolution and Blastic Plasmacytoid Dendritic Cell Neoplasm - Two Cases

  Here we present two case studies of sequential whole exome sequencing (WES) in patients, who both developed BPDCN throughout their medical history but primarily presented with lymphoid cancers (clonally related ALK-negative anaplastic large-cell lymphoma (ALCL) and T-lymphoblastic lymphoma (T-LBL)) and whose bone marrow at remission exhibited a CMML phenotype, from which in both cases BPDCN clones arose that subsequently became treatment refractory.

  Study EGAS50000000214

• Transcriptomic insights into IPMN-associated PDAC progression

  This study investigates the transcriptomic heterogeneity and evolutionary progression of intraductal papillary mucinous neoplasms (IPMNs) and their associated pancreatic ductal adenocarcinomas (PDAC). Multi-region tumour sampling was performed to characterise spatial variation in gene expression and to identify transcriptional changes associated with malignant transformation. The project aims to improve understanding of tumour evolution in pancreatic cancer and to identify molecular pathways involved in IPMN-to-PDAC progression.

  Study EGAS50000001540

• Transcriptomic profiling of myeloid cells from secondary lymphoid organs (lymph nodes and tonsils) from lymphoma patients and controls.

  Despite their recognized impact on the pathogenesis and prognosis of B-cell lymphoma, tumor-associated macrophages (TAM) have not been extensively explored in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). We investigated mononuclear phagocyte (MNP) heterogeneity using single cell RNA sequencing (scRNAseq) in B-cell lymphoma lymph nodes compared to reactive secondary lymphoid organs (lymph nodes and tonsils).

  Study EGAS50000001135

• Genomic characterization of germ-cell tumors in childhood

  Germ cell tumors (GCTs) are rare neoplasms affecting approximately 3.5% of pediatric patients, with diverse histological subtypes. Despite their low mutational burden, prevalent alterations in KIT, KRAS, and NRAS genes are observed, but molecular understanding of pediatric GCTs lags behind adult counterparts. We aimed to elucidate the genomic landscape of 16 pediatric GCT patients via whole exome sequencing (WES), which revealed somatic alterations resembling those in adult GCTs.

  Study EGAS50000000619

• RNAseq_of_ribosomal_footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Study EGAS00001001591

• SDH_deficient_renal_tumours___RNA_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004103

• Roma Sequencing Study

  Present day Roma genome were shaped by the extensive inbreeding and admixture during their Diaspora. Here, we shed light on the Roma demographic history by analyzing the whole genome sequence of 46 Roma individuals pertaining to four migrant groups in six European countries. The strong reduction in effective population size (~44%), that occurred around 2kya, was not masked by the subsequent high admixture in Middle Eastern and European countries.

  Study EGAS00001004287

• Molecular characterization of hepatocellular carcinoma in patients with non-alcoholic steatohepatitis

  Patients with hepatocellular carcinoma (HCC) associated to non-alcoholic steatohepatitis (NASH) are increasing globally, but their molecular traits are not well characterized. Our molecular characterization revealed higher rates of ACVR2A mutations (10%) – a potential tumour suppressor, presence of a novel mutational signature (MutSig-NASH-HCC), a more relevant role of Wnt/TGF-β proliferation subclass in tumours (42%) and immunosuppressive traits in the adjacent non-tumoral tissue.

  Study EGAS00001005222

• Population_based_analysis_of_POT1_variants_in_a_cutaneous_melanoma_case_control_cohort

  Pathogenic germline variants in the protection of telomeres 1 gene (POT1) have been associated with predisposition to a range of tumor types, including melanoma, glioma, leukemia and cardioangiosarcoma. We sequenced all coding exons of the POT1 gene in 2,929 European-descent melanoma cases and 3,298 controls, identifying 43 protein-changing genetic variants. We performed functional studies on each of these variants and explored their possible contribution to disease risk.

  Study EGAS00001006870

• A Population Genomics Study Using a Disease-Targeted Cell model: Integration of

  The common genetic variants associated with complex traits typically lie in non-coding DNA and may alter gene regulation in a cell type-specific manner. Consequently, the choice of tissue or cell model in the dissection of disease associations is important. We carried out an expression quantitative trait loci (eQTL) study of primary human osteoblasts (HOb) derived from 95 unrelated donors of Swedish origin, each represented by two independently derived primary lines to provide biological replication. We combined our data with publicly available information from a genome-wide association study (GWAS) of bone mineral density (BMD). The top 2000 BMD-associated SNPs were tested for cis-association of gene expression in HObs and in lymphoblastoid cell lines (LCLs) using publicly available data and showed that HObs have a significantly greater enrichment (threefold) of converging cis-eQTLs as compared to LCLs. The top 10 BMD loci with SNPs showing strong cis-effects on gene expression in HObs were selected for further validation using a staged design in two cohorts of Caucasian male subjects. All 10 variants were tested in the Swedish MrOS Cohort (n = 3014), providing evidence for two novel BMD loci (SRR and MSH3). These variants were then tested in the Rotterdam Study (n = 2090), yielding converging evidence for BMD association at the 17p13.3 SRR locus. The cis-regulatory effect was further fine-mapped to the proximal promoter of the SRR gene (rs3744270). Our results suggest that primary cells relevant to disease phenotypes complement traditional approaches for prioritization and validation of GWAS hits for follow-up studies. Reprinted from Grundberg E, Kwan T, Ge B et al., Genome Res Nov 2009, with permission from Genome Research, Cold Spring Harbor Press, PMID:19654370.

  Study phs000225

• Sudden Death in the Young Case Registry

  Knowledge gaps persist about the incidence of and risk factors for sudden death in the young (SDY). The SDY Case Registry is a collaborative effort between the National Institutes of Health, the Centers for Disease Control and Prevention, and the Michigan Public Health Institute. Its goals are to: (1) describe the incidence of SDY in the United States by using population-based surveillance: (2) compile data from SDY cases to create a resource of information and DNA samples for research; (3) encourage standardized approaches to investigation, autopsy, and categorization of SDY cases; (4) develop partnerships between local, state, and federal stakeholders toward a common goal of understanding and preventing SDY; and (5) support families who have lost loved ones to SDY by providing resources on bereavement and medical evaluation of surviving family members. Built on existing Child Death Review programs and as an expansion of the Sudden Unexpected Infant Death Case Registry, the SDY Case Registry achieves its goals by identifying SDY cases, providing guidance to medical examiners/coroners in conducting comprehensive autopsies, evaluating cases through child death review and an advanced review by clinical specialists, and classifying cases according to a standardized algorithm. The SDY Case Registry also includes a process to obtain informed consent from next-of-kin to save DNA for research, banking, and, in some cases, diagnostic genetic testing. The SDY Case Registry will provide valuable incidence data and will enhance understanding of the characteristics of SDY cases to inform the development of targeted prevention efforts. For cases where informed consent has been obtained for research genomic sequencing has been performed. On these cases genomic data, phenotype information and on a limited number of cases redacted autopsy reports will be available through dbGaP.

  Study phs003221

• Genomics of Substance Use Disorders in Latin American Populations

  This is a subsample of the National Survey of Drug, Alcohol, and Tobacco Use, administered in 2016 between August and October to participants aged 12-65 in urban and rural Mexican households, named Mexican Genomic Database for Addiction Research (MxGDAR). The objective of the survey was to evaluate the patterns of use of different psychoactive substances and mental health problems in Mexico. The sample universe was made up of primary sampling units (PSUs) that were the sum of basic statistical geographic areas, stratified by state and urban-rural communities. An adult aged 18-65 was chosen randomly from each household, and an adolescent aged 12-17 was also chosen randomly from the household which has at least one member under 18. The second administration of the survey included a subsample of 13,130 respondents who agreed to give a saliva sample for DNA analysis, to be used in analyzing the relationship of mental health, addiction, and genetics. This sample was weighted according to selection probability to be representative on the national level. Mental health symptomatology for these individuals was evaluated using the Diagnostic Interview for Psychosis and Affective Disorders (DI-PAD) using the operational criteria for psychotic disorders (OPCRIT v.4.0), administered by interviewers trained in its use. It includes the evaluation of symptomatology of psychosis, depression, anxiety, obsession/compulsion, mania/hypomania, and post-traumatic stress. The study seeks to replicate genetic associations with substance use (LINC01622), psychiatric disorders (PTPRM), or comorbidity between both (MGMT) reported in following paper: https://pubmed.ncbi.nlm.nih.gov/33762635/. Funding for genotyping was provided by the National Institute on Drug Abuse (NIDA), one of the National Institutes of Health (NIH).

  Study phs003558

• Germline Genomic Analyses of Breast Cancer in Latinas

  In this case-control study of breast cancer among Hispanic/Latina (H/L) women, the goals were to identify breast cancer susceptibility genes and genetic variants for risk of developing breast cancer in H/L women. There were two phases with whole exome sequencing (WES) done in a discovery phase and targeted sequencing of candidate genes in the replication phase. The candidate genes selected for replication came from the first phase and from genes known to affect breast cancer risk in prior studies. Cases and controls were drawn from several studies. Breast cancer cases for discovery phase included women from the City of Hope (COH) Clinical Cancer Genomics Community Research Network (CCGCRN), UCSF Cancer Genetics Clinic and USC Cancer Genetics clinic. Controls for discovery phase included women who did not have breast and were recruited through City of Hope community fairs. A separate group of controls included women from the California Teachers Study. Additional controls for discovery were obtained from WES already generated by the Multi-ethnic cohort (MEC) study. The discovery/WES results of known breast cancer genes were published (PMID 31206626). In the replication phase, we included cases and controls from the Cancer de Mama (CAMA) study which is a case-control study of breast cancer in Mexico, MEC for those not included in the discovery dataset, the San Francisco Bay Area Cancer study (phs000912), the Northern California Breast Cancer Registry, and the California Pacific Medical Center Research Institute Women's Cohort (phs000395). Cases from the PATHWAYS study who were recruited from Northern California Kaiser Permanente were also included. Results from the combined discovery and replication analyses are reported in PMID 36747679.

  Study phs003144

• Copy numbers in resectable gastric cancer treated with surgery alone

  Purpose: Gastric cancer is a heterogeneous disease requiring stratification to recognize its underlying biology and variable clinical outcome. The Cancer Genome Atlas (TCGA) recognizes four molecular subgroups: Epstein-Barr virus positive (EBV+) and microsatellite instable (MSI) with superior survival compared to genomically stable (GS) and chromosomal instable (CIN). Since classification criteria to distinguish GS from CIN were not defined, alternative markers such as Lauren’s histopathology or CDH1/p53 immunohistochemistry are commonly applied. Here we compared survival of gastric cancer subgroups determined by four methods. Experimental Design: EBV- and microsatellite stable tumors from a total of 309 patients treated with surgery alone were assigned to subgroups by: (i) specific copy number aberrations as determined by TCGA (GS or CIN), (ii) genome instability index (GII; high or low), (iii) Lauren’s classification (diffuse or intestinal), and (iv) CDH1/p53 immunohistochemistry (IHC; aberrant CDH1, normal-, or aberrant p53 expression). Subgroups were associated with cancer-related survival (CRS). Results: Five-year CRS was 42.0% for diffuse and 49.5% for intestinal type tumors, and 57.8% for GS and 41.6% for CIN tumors. Classification by GII or CDH1/p53 IHC did not correlate with CRS. The combination of TCGA and Lauren classifications resulted in four distinct subgroups. Five-year CRS for GS-intestinal (n=24), GS-diffuse (n=57), CIN-intestinal (n=142) and CIN-diffuse (n=86) was 61.4%, 56.5%, 47.6%, and 31.5%, respectively. Conclusions: TCGA’s GS and CIN have additional prognostic value to Lauren’s diffuse and intestinal subgroups in gastric cancer. GS-intestinal, GS-diffuse, CIN-intestinal and CIN-diffuse constitute biologically distinct entities and are suggested as stratification variables for future studies.

  Study EGAS00001007394

• 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

• Primary plasma cell leukemia (pPCL) samples were sequenced using the Nimblegen MedExome hybridization capture to detect translocations, copy number changes, and mutations in 20 pPCL samples and patient matched controls.

  Primary plasma cell leukemia (pPCL) is a rare malignancy related to multiple myeloma. Here we have assembled 20 patient samples and performed whole exome sequencing to determine the differences between multiple myeloma and pPCL. CD138+ cells were purified from bone marrow aspirates from patients with pPCL. Control cells were obtained from CD34+ stem cell harvests or CD3+ T cells. DNA was extracted and processed using the HyperPlus library prep kit (KAPA Biosystems) and sequenced using 75 bp paired end reads on an Illumina NextSeq500.

  Study EGAS00001003104

• Subtyping Sub-Saharan Esophageal Squamous Cell Carcinoma by Comprehensive Molecular Analysis

  Esophageal squamous cell carcinoma (ESCC) occurs as much as 20x more frequently in sub-Saharan Africa than Western countries. Through the UNC-Malawi project collaboration we obtained whole-exome matched tumor/normal and RNA sequencing of 59 ESCC from Malawi between 2011-2012. DNA analysis revealed similar mutations as other cohorts, while RNA analysis revealed three distinct subtypes. Mutational signature analysis revealed a pattern of mutation not previously reported in other cohorts or more broadly. Taken together this suggests the high prevalence of ESCC in the region is secondary to an as yet identified mutagen.

  Study phs001448

• Whole Exome Sequencing of Uveal Melanoma

  Uveal melanoma is a rare form of melanoma that occurs in the eye and has no effective treatment once metastatic. To further characterize the genomic events driving uveal melanoma, whole exome sequencing was performed on 61 primary tumors derived from enucleations, 3 liver metasases, and paired normal DNA. Recurrent somatic genetic alterations including point mutations, small insertions and deletions, as well as copy number variations were identified. In addition, RNA sequencing of uveal melanoma cell lines expressing shRNAs was performed from total RNA as well as polysome-associated mRNA in order to identify transcripts regulated by EIF1AX at the level of translation.

  Study phs001370

• TCR Repertoire Sequencing to Evaluate the Diversity of Follicular Helper T Cells in HIV Infected Lymph Nodes

  The TCR repertoire of CD4+ T cells in human lymph nodes is a case-based analysis of the TCR repertoire of CD4+ T cells in human lymph nodes. The study aims to determine how HIV infection alters the repertoire complexity of follicular helper T cells (TFH) in relationship to other T cell subsets in the lymphoid compartment. This study performs TCR repertoire sequencing using Molecular Identifier Clustering-based Immune Repertoire Sequencing (MIDCIRS). We found TFH cells become clonally expanded and convergently selected in LNs from patients with chronic HIV infection.

  Study phs001548

• RNA-Seq of Whole Blood from Pediatric Sickle Cell Anemia (SCA) Patients

  The aim of this study is to define the immune cell transcriptome by next generation RNA sequencing in blood from individuals with SCA, in comparison to healthy African American controls. This study has a cross-sectional case-control design. We will compare the transcriptome profiles of blood mononuclear cells from healthy age-matched African American children without cardiovascular disease or risk factors (“Controls”) to those of children with SCA, age 5 -21 years, who are not receiving chronic red blood cell transfusions or hydroxyurea therapy to identify genes that are differentially expressed in SCA. 

  Study phs002687

• Type I Interferon and Cycling Lymphocytes in Macrophage Activation Syndrome

  We performed immune profiling of peripheral blood mononuclear cells from patients with Still's disease and macrophage activation syndrome (MAS) using bulk RNA sequencing and single-cell RNA sequencing. Three groups were included in the study: healthy controls, patients with Still's disease without macrophage activation syndrome, and patients with Still's disease and macrophage activation syndrome. We found that macrophage activation syndrome is associated with transcriptomic signatures of interferon upregulation and cell cycling. We identified cycling lymphocytes within T cell and NK cell populations that are correlated with MAS disease activity. All sequencing data are available through dbGaP.

  Study phs003310

• Single-cell Analysis of Neoplastic Plasma Cells Identifies Novel Myeloma Pathobiology Mediators and Potential Targets

  Newly diagnosed symptomatic and relapsed/refractory myeloma is a clonal plasma cell (PC) dyscrasia that arises from precursors which have been studied utilizing bulk or single-cell (sc) techniques. By combining scRNA-sequencing with scB-cell receptor (BCR)-sequencing, we found more dysregulated genes in monoclonal PCs compared with analyses of the entire CD138+ population, which includes non-neoplastic/polyclonal PCs. Paired tumor and non-tumor WGS was performed to evaluate the presence of IgH-associated translocations and hyperdiploidy events, initially detected by FISH, in a subset of samples included in this study.

  Study EGAS50000000801