14508 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

in 18.78 milliseconds.

• National Human Genome Research Institute (NHGRI) GENEVA Genome-Wide Association Study of Venous Thrombosis (GWAS of VTE)

  Overview: Our overall long-term goal is to determine risk factors for the complex (multifactorial) disease, venous thromboembolism (VTE), that will allow physicians to stratify individual patient risk and target VTE prophylaxis to those who would benefit most. In this genome-wide association case-control study (1300 cases and 1300 controls) we hope to identify susceptibility variants for VTE. Mutations within genes encoding for important components of the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways are risk factors for VTE. We hypothesize that other genes within these four pathways or within other pathways also are VTE disease-susceptibility genes. Therefore, we performed a genome wide association (GWA) screen and analysis using the Illumina 660W platform to identify SNPs within 1,300 clinic-based, non-cancer VTE cases primarily from Minnesota and the upper Midwest USA, and 1300 clinic-based, unrelated controls frequency-matched on patient age, gender, myocardial infarction/stroke status and state of residence. This is a subset of a slightly larger candidate gene study using 1500 case-control pairs to identify haplotype-tagging SNPs (ht-SNPs) in a large set of candidate genes (n~750) within the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways. Study Populations. Cases. VTE cases were consecutive Mayo Clinic outpatients with objectively-diagnosed deep vein thrombosis (DVT) and/or pulmonary embolism (PE) residing in the upper Midwest and referred by Mayo Clinic physician to the Mayo Clinic Special Coagulation Laboratory for clinical diagnostic testing to evaluate for an acquired or inherited thrombophilia, or to the Mayo Clinic Thrombophilia Center. Any person contacted to be a control but discovered to have had a VTE was evaluated for inclusion as a case. Cases were primarily residents from Minnesota, Wisconsin, Iowa, Michigan, Illinois, North or South Dakota, Nebraska, Kansas, Missouri and Indiana. A DVT or PE was categorized as objectively diagnosed when (a) confirmed by venography or pulmonary angiography, or pathology examination of thrombus removed at surgery, or (b) if at least one non-invasive test (compression duplex ultrasonography, lung scan, computed tomography scan, magnetic resonance imaging) was positive. A VTE was defined as: Proximal leg deep vein thrombosis (DVT), which includes the common iliac, internal iliac, external iliac, common femoral, superficial [now termed "femoral"] femoral, deep femoral [sometimes referred to as "profunda" femoral] and/or popliteal veins. (Note: greater and lesser saphenous veins, or other superficial or perforator veins, were not included as proximal or distal leg DVT). Distal leg DVT (or "isolated calf DVT"), which includes the anterior tibial, posterior tibial and/or peroneal veins. (Note: gastrocnemius, soleal and/or sural [e.g., "deep muscular veins" of the calf] vein thrombosis was not included as distal leg DVT). Arm DVT, which includes the axillary, subclavian and/or innominate (brachiocephalic) veins. (Note: jugular [internal or external], cephalic and brachial vein thrombosis was not included in "arm DVT"). Hepatic, portal, splenic, superior or inferior mesenteric, and/or renal vein thrombosis. (Note: ovarian, testicular, peri-prostatic and/or pelvic vein thrombosis was not included). Cerebral vein thrombosis (includes cerebral or dural sinus or vein, saggital sinus or vein, and/or transverse sinus or vein thrombosis). Inferior vena cava (IVC) thrombosis Superior vena cava (SVC) thrombosis Pulmonary embolism Patients with VTE related to active cancer, antiphospholipid syndrome, inflammatory bowel disease, vasculitis, a rheumatoid or other autoimmune disorder, a vascular anomaly (e.g., Klippel-Trénaunay syndrome, etc.), heparin-induced thrombocytopenia, or a mechanical cause for DVT (e.g., arm DVT or SVC thrombosis related to a central venous catheter or transvenous pacemaker, portal and/or splenic vein thrombosis related to liver cirrhosis, IVC thrombosis related to retroperitoneal fibrosis, etc.), with hemodialysis arteriovenous fistula thrombosis, or with prior liver or bone marrow transplantation were excluded. Controls. A Mayo Clinic outpatient control group was prospectively recruited for this study. Controls were frequency-matched on the age group (18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80+ years), sex, myocardial infarction/stroke status, and state of residence distribution of the cases. We selected clinic-based controls using a controls' database of persons undergoing general medical examinations in the Mayo Clinic Departments of General Internal Medicine or Primary Care Internal Medicine. Additionally persons undergoing evaluation at the Mayo Clinic Sports Medicine Center, and the Department of Family Medicine were screened for inclusion as controls. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to venous thrombosis through large-scale genome-wide association studies of 1,300 clinic-based, VTE cases and 1300 clinic-based, unrelated controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000289

• EuCANCan: EUropean-CANadian Cancer network

  The EUropean-CANadian Cancer network (EuCANCan) is a project aiming to develop a federated network of aligned and interoperable infrastructures for the homogeneous analysis, management and sharing of genomic oncology data for Personalized Medicine. This initiative, funded by the European Commission and the Canadian Institutes of Health and coordinated by the Barcelona Supercomputing Center (BSC), is expected to process and provide the scientific community with around 30-35 thousand patient samples from different types of cancer, coming from different nodes involved in this project, during the four years of the project. Data generated as part of primary studies, often in small hospitals or research centers, is hardly reused by other projects or groups. EuCANCan is proposed to foster the homogenisation and discoverability of cancer samples from very different sources for the whole community. These efforts will help paving the way to future standardised and global genomics projects, specially for those participant countries that eventually integrate the methodology and infrastructure generated during the project. “The more data we have access to the more and better discoveries. We attempt to overcome the legal and technical limitations in order to generate, gather and exploit bigger datasets as well as answer more ambitious questions”. These were some of the words Dr. David Torrents, main coordinator of the project, shared with a regional radio during the kick-off meeting of the project, on February 11th, 2019. The EUCANCan network will be composed of reference nodes in Amsterdam, Barcelona, Berlin, Heidelberg, Paris and Toronto which have established strong research and clinical programs in the field of genomic oncology. The Centre for Genomic Regulation (CRG), specifically the European Genome-phenome Archive (EGA), is among the leading institutions. Its exhaustive experience in biomedical data archival and secure distribution is considered key for crucial developments within the project. It is also notable the recent inclusion of EUCANCan in the list of GA4GH driver projects. Further information and details can be found in the following links: InsideHPC BSC official description Techweek (Spanish)

  Blog eucancan

• MGHBoston_Molpheno_Closed

  This dataset contains Whole Genome Sequencing and, if available, RNA-sequencing and/or ATAC-sequencing data of 17 lymphoblastoid cell lines derived from patients with complex genomic rearrangements. Patients have phenotypes in category of intellectual disability and/or multiple congenital anomalies. Data access is closed.

  Dataset EGAD00001004866

• Health and Retirement Study (HRS)

  Introduction to V2: This data release comprises data from the V1 release combined with approximately 3,000 additional samples, collected during the HRS 2010 field period. The 2010 data include samples from a random half of the new cohort enrolled in 2010 along with a significant expansion of the minority sample. Description: The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of approximately 20,000 people in America over the age of 50 every two years. Supported by the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, the HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study collects information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. Through its unique and in-depth interviews, the HRS provides an invaluable and growing body of multidisciplinary data that researchers can use to address important questions about the challenges and opportunities of aging. Because of its innovation and importance, the HRS has become the model and hub for a growing network of harmonized longitudinal aging studies around the world. Origins of the HRS. As the population ages it is increasingly important to obtain reliable data about aging and topics that are relevant to a range of policy issues in aging. To address this need, the National Institutes on Aging (NIA) established a cooperative agreement with the University of Michigan Institute for Social Research to collect such data. The HRS launched data collection in 1992 and has re-interviewed the original sample of respondents every two years since then. By adding new cohorts and refreshing the sample, the HRS has grown to become the largest, most representative longitudinal panel study of Americans 50 years and older. HRS Study Design. The target population for the original HRS cohort includes all adults in the contiguous United States born during the years 1931-1941 who reside in households, with a 2:1 oversample of African-American and Hispanic populations. The original sample is refreshed with new birth cohorts (51-56 years of age) every six years. The sample has been expanded over the years to include a broader range of birth cohorts as well. The target population for the AHEAD survey consists of United States household residents who were born in 1923 or earlier. Children of the Depression (CODA) recruits households born 1924-1930, War Babies 1942-47, Early Boomers 1948-53, and Mid-Boomers 1954-59. Data collection includes a mixed mode design combining in-person, telephone, mail, and Internet. For consenting respondents, HRS data are linked at the individual level to administrative records from Social Security and Medicare claims. Genetic Research in the HRS. The HRS has genotyped 2.5 million single nucleotide polymorphisms (SNPs) on respondents using Illumina's Human Omni2.5-Quad (Omni2.5) BeadChip. The genotyping was performed by the NIH Center for Inherited Disease Research (CIDR). Saliva was collected on half of the HRS sample each wave starting in 2006. In 2006, saliva was collected using a mouthwash collection method. From 2008 onward, the data collection method switched to the Oragene kit. Saliva completion rates were 83% in 2006, 84% in 2008, and 80% in 2010 among new cohort enrollees. HRS Phenotypic data. Phenotypic data are available on a variety of dimensions. Health measures include physical/psychological self-report, various health conditions, disabilities, cognitive performance, health behaviors (smoking, drinking, exercise), physical performance and anthropomorphic measures, and biomarkers (HbA1c, Total Cholesterol, HDL, CRP, Cystatin-C). Data are also available on health services including utilization, insurance and out-of-pocket spending with linkage to Medicare records. Economic measures include employment status/history, earnings, disability, retirement, type of work, income by source, wealth by asset type, capital gains/debt, consumption, linkage to pensions, Social Security earnings/benefit histories. There is also extensive information on family structure, proximity, transfers to/from of money, time, social and psychological characteristics, as well as a wide range of demographics. Performance on a cognitive test combining immediate and delayed word recall was selected as an example trait for the dbGaP data release. In the immediate word recall task the interviewer reads a list of 10 nouns to the respondent and asks the respondent to recall as many words as possible from the list in any order. After approximately five minutes of asking other survey questions, the respondent is asked to recall the nouns previously presented as part of the immediate recall task. The total recall score is the sum of the correct answers to these two tasks, with a range of 0 to 20. Researchers who wish to link to other HRS measures not in dbGaP will be able to apply for access from HRS. A separate Data Use Agreement (DUA) will be required for linkage to the HRS data. See the HRS website (http://hrsonline.isr.umich.edu/gwas) for details.

  Study phs000428

• Clonal dynamics after allogeneic haematopoietic cell transplantation using genome-wide somatic mutations - TGS

  Allogeneic haematopoietic cell transplantation (HCT) replaces the stem cells responsible for blood production with those harvested from a donor, and is received by 40,000 patients worldwide each year. To quantify dynamics of long-term stem cell engraftment, we sequenced whole genomes of 2,824 single-cell-derived haematopoietic colonies from blood samples of 10 donor-recipient pairs taken 9-31 years after HLA-matched sibling HCT. With younger donors, 10,000-50,000 stem cells had engrafted and were still contributing to haematopoiesis at time of sampling, but estimates were 10-fold lower with older donors. Engrafted stem cells made multilineage contributions to myeloid, B-lymphoid and T-lymphoid populations, although individual clones often showed biases towards one or other mature cell type. Recipients had lower clonal diversity than matched donors, equivalent to ~10-15 years of additional ageing, arising from up to 25-fold greater expansion of stem cell clones. An HCT-related population bottleneck alone could not explain these differences: instead, phylogenetic trees evinced two distinct modes of HCT-specific selection. In 'pruning selection', cell divisions underpinning recipient-enriched clonal expansions had occurred in the donor, preceding transplant - their selective advantage derived from preferential mobilisation, harvest, survival ex vivo or initial homing. In 'growth selection', cell divisions underpinning clonal expansion occurred through proliferative advantage in the recipient's marrow after homing - clones with multiple driver mutations especially demonstrated this pattern. Uprooting stem cells from their native environment and transplanting them to foreign soil exaggerates selective pressures, distorting and accelerating the loss of clonal diversity compared to the unperturbed haematopoiesis of donors.

  Dataset EGAD00001010874

• Maintenance of Brain Tumor Profile on Organotypic Brain Slice Culture (OBSC)

  We used uncultured tumor resection tissue from an NF2 mutation-driven grade II meningioma (MG-II) to investigate whether tumors engrafted onto organotypic brain slice cultures (OBSCs) maintained the genetic profile of the parent tumor. We prepared three groups of samples for whole exome sequencing (WES) from the same pool of dissociated MG-II tissue. Group HT is the original uncultured human tumor tissue (n = 3). Group CL is the parent tumor tissue expanded in standard in vitro cell culture until the minimum number of cells required for WES had grown. Because of initial cell loss and subsequent clonal expansion, this required six passages over the span of approximately one month (n = 3). Group BSHT is the uncultured tumor resection tissue engrafted onto OBSCs and subsequently dissected from the OBSCs at the conclusion of our standardized assay length (4 days; n = 4). WES analysis showed that tumor tissue engrafted onto OBSCs maintained a significant genetic resemblance to the parent tumor, while tumor tissue expanded in vitro displayed a distinctly different profile. Furthermore, the mutational profiles of all four BSHT biological replicates were markedly similar, indicating that each OBSC-engrafted tumor indeed contained a representative sample of the original patient tumor. A closer look at the hallmark NF2 mutations existing within all samples revealed that while all samples from the original tumor (HT1-3) and the OBSC-engrafted tumor (BSHT1-4) maintain the frame shift deletion at V24, this mutation was lost in all samples expanded in vitro (CL1-3) and replaced by mutations in other areas. Together, this data suggests that the rapid assay design and tumor-accommodating niche of our OBSC platform enables effective maintenance of the original patient tumor profile. The BBsplit algorithm from the BBtools suite was run on all samples to eliminate rat DNA contamination in the BSHT samples as well as to account for any biases that may result as a part of that process. Only the reads that were binned to the human reference were used for subsequent analysis. Reads were then mapped to the GRCh38 version of the human genome with BWA v0.7.17 and realigned together with ABRA2 v.23. Quality control was implemented using the GATK/Picard v4.1.7.0 toolkit. Somatic variants were called for each sample using the MuTect2 algorithm v4.1.7.0. Variants were merged into a single cohort variant call file and then converted to MAF via vcf2maf v1.6.21 tool. Variants were annotated using VEP v87. To identify mutations with potentially high biological impact, multiple filtering steps were applied to somatic mutation calling. First, we selected only the somatic variants that passed all filters from the MuTect2 FilterMutectCalls algorithm and second, only high/moderate impact (change coding) variants as defined by the VEP annotation were further analyzed. Over 1900 single nucleotide variants (SNVs) were detected across all samples. Figures that summarized the results were generated using maftools.

  Study phs003268

• Prognostic and therapeutic significance of leukemia subtypes and minimal residual disease measurements in pediatric acute lymphoblastic leukemia treated with contemporary risk-directed trial: a cohort study

  Background Genomic analyses to identify leukemia subtypes and refinement of minimal residual disease (MRD) determination are two recent advances that would have substantial impact on the management of children with acute lymphoblastic leukemia (ALL). However, the combined application of these two approaches to determine the prognostic and therapeutic significance of MRD measurement and full spectrum of leukemia subtypes in the context of contemporary risk-directed therapy has not been studied comprehensively.MethodsBetween October 29, 2007 and March 26, 2017, 598 consecutive children with newly diagnosed ALL were enrolled in a clinical trial at St. Jude Children’s Research Hospital. Patients were provisional classified according to the presenting clinical and laboratory features including immunophenotype and cytogenetics. Patients with ETV6-RUNX1 and high hyperdiploid B-progenitor ALL were provisionally included in the low-risk groups; those with TCF3-PBX1, hypodiploidy and T-cell ALL in the standard (intermediate)-risk group; and patients with BCR-ABL1, KMT2A and early T-cell precursor ALL in the high-risk group. Final risk assignment was based primarily on MRD levels measured by flow cytometry on Day 15 (≥1%) and Day 42 (<0.01% or ≥1%) of remission induction. Using genomic classification based on cytogenetics and genomic analysis (single nucleotide polymorphism array analysis and transcriptome, exome, and genome sequencing), patients were classified into 17 subtypes. The primary aim was to determine the event-free survival, overall survival and cumulative risk of relapse according to specific leukemia subtypes and MRD levels on Days 8, 15 and 42 of remission induction. This clinical trial was registered at ClinicalTrials.gov, number NCT00549848.FindingsPatients with ETV6-RUNX1, high hyperdiploidy and DUX4-rearranged B-ALL all received low- or standard-risk therapy, and had the highest 5-year event-free survival rates: 98.4% (95% CI, 95.9-100), 95.3% (91.2-99.4), and 95.0% (84.2-100), respectively. All 142 patients with Day 8 MRD<0.01%, except two with KMT2A-rearranged ALL and one with TCF3-PBX1, were in continuous complete remission. The TCF3-PBX1, PAX5alt, T-cell, early T-cell precursor, iAMP21 and hypodiploid ALL had intermediate outcome with 5-year event-free survival rates ranging from 80.0% (39.4-100) to 88.2% (71.7-100). Patients with KMT2A-rearranged, BCR-ABL1, BCR-ABL1-like and ETV6-RUNX1-like ALL had the worst outcomes, with 5-year event-free survival rates between 64.1% (43.9-84.3) and 76.2% (51.9-100), despite most patients receiving standard- or high-risk therapy. Treatment intensification based on MRD and genotype improved outcome. Relapse did not occur in any of the patients with ETV6-RUNX1, DUX4-rearranged, TCF3-PBX1, iAMP21, ZNF384-rearranged, hypodiploid, or BCR-ABL1-like B-ALL who had day 15 MRD≥1% and received standard-risk therapy. However, day 42 MRD<0.01% did not preclude relapse in patients with intermediate-risk or unfavorable subtypes including TCF3-PBX1, PAX5alt, T-cell, iAMP21, BCR-ABL1, BCR-ABL1-like, ETV6-RUNX1-like, KMT2A-rearranged, and MEF2D-rearranged ALL, despite intensified treatment in the standard- or high-risk arms. InterpretationContemporary risk-directed treatment based on genotypes and MRD can cure virtually all patients with ETV6-RUNX1, hyperdiploid>50 and DUX4-rearranged ALL. While intensified treatment improve outcome for patients with high MRD during induction, substantial proportions of patients with intermediate-risk or unfavorable subtypes would still relapse even achieving negative MRD status at the end of induction and require novel therapeutics to improve outcome.

  Study EGAS00001004739

• Alzheimer's Disease Sequencing Project (ADSP)

  NOTICE OF CHANGE IN LOCATION FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) GENETIC AND PHENOTYPIC DATA: ADSP whole exome and whole genome sequence data that are shared through dbGaP were mapped to the Genome Reference Consortium human genome GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site. Please see the ADSP Design page for the complete study description. All data that are mapped to GRCh38 (hg38) are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service (DSS). For instructions on how access the ADSP Build 38 data that are shared through NIAGADS DSS, visit the Application Instructions page. STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals. Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases. The Discovery Phase analysis (2014-2018) is funded under PAR-12-183. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD. The Replication Phase (2016-2021) analysis will be funded under RFA-AG-16-001 and RFA-AG-16-002 and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs. GRCh37 Data Releases The first ADSP data release occurred on November 25, 2013. It included the whole-genome sequencing data in BAM file format on 410 individuals. The second ADSP data release occurred on March 31, 2014, and included the whole-genome sequencing data in BAM file format for an additional 168 individuals. The third ADSP data release occurred on November 03, 2014 and included whole-exome sequencing data in BAM file format for 10,939 individuals. The fourth ADSP data release occurred on February 13, 2015 and included revised ethnic data for subjects with whole-exome sequencing data. The fifth ADSP data release occurred on July 13, 2015 and included whole-genome genotypes and updated phenotypes as well as changes to pedigree structures and sample IDs. The sixth ADSP data release occurred on December 8, 2015, and included whole-exome genotypes and updated phenotypes as well as changes to subject IDs. This seventh ADSP data release on April 12, 2016 includes: (1) WES and WGS SNV VCF files (2) WES and WGS Indel PLINK files ADSP Data Available through dbGaP: ADSP - Whole Genome Sequencing ADSP - Whole Exome Sequencing Comments DNA-Seq (BAM) n=578 n=10913 Sequence data available (plus n=38 replications w/out genotype data) Concordant SNV Genotypes (PLINK format) N/A n=10913 QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set) Consensus Genotypes (PLINK and VCF format) n=578 n=10913 QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK Concordant Indel Genotypes (PLINK format) n=578 n=10913 QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines Phenotype Data n=4735 n=10913 Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members. Please use the release notes provided by dbGaP to obtain detailed information about study release updates. The ADSP data portal provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit https://www.niagads.org/adsp/.

  Study phs000572

• Detroit Research on Cancer Survivors (ROCS) and Disparities and Cancer Epidemiology - Colorectal Cancer (DANCE)

  The goals for this study were as follows:1. Enroll a total of 5,060 African Americans newly diagnosed with cancer into the Detroit Research on Cancer Survivors (Detroit ROCS) Cohort. These population-based cases will be ascertained through the Detroit Metropolitan Detroit Cancer Surveillance System (MDCSS), a founding member of the NCI SEER Program. Participation at baseline will include a written, web-based, or telephone interview, saliva and/or blood collection, and tumor block retrieval, with detailed cancer-related information coming from the MDCSS registry and medical records.2. Enroll a subgroup of colorectal cancer patients identified through the Louisiana Tumor Registry (LTR). An additional 500 colorectal cancer patients, approximately half non-Hispanic white and half African American, will be identified through the LTR and enrolled into the ROCS protocol. The survey is the same survey administered to the ROCS cohort. The Louisiana (“DANCE-CRC”) cohort will not be followed beyond baseline, and blood will not be collected (tumor tissue, however, will be collected, deidentified, and sent for processing through Dr. Rozek's laboratory at Georgetown University).The proposed cohorts will provide for a broad research agenda evaluating cancer outcomes in African Americans across a variety of factors from individual, provider, health care system and community perspectives. These factors include tumor characteristics driving individualized treatment planning, quality of life after a diagnosis and recurrence. Utilizing the MDCSS registry, we will enroll a large population-based sample of African-American cases with lung, breast, colorectal, and prostate cancers and their caregivers resulting in a cohort that will provide substantial benefit to the cancer research community. KCI has a strong history of research in the African-American community and the faculty represents a breadth of experience that includes clinical oncology, genetic epidemiology, environmental exposures, quality of life, treatment decision making, racism/discrimination, and health behaviors. Drs. Schwartz and Beebe-Dimmer have been and will continue to be generous collaborators with other institutions to ensure that this resource will be extensively utilized. The proposed overall cohort will be the only one of its kind, to our knowledge, filling a substantial gap in our understanding of the determinants driving cancer outcomes in African Americans. In addition to registry data detailing cancer specifics, yearly surveys have collected information about individualized treatment experiences, heath histories, family histories, quality of life after a diagnosis, recurrence and caregiving. Population: Adult cancer survivors (see inclusion criteria in next section) Molecular Technologies: Genotyping: Infinium Expanded Multi-Ethnic Genotyping Array (MEGAEX) DNA Sequencing: Illumina NovaSeq X Plus using XLEAP-SBS (sequencing by synthesis) Whole genome sequencingPrincipal Findings: The preliminary data collected reinforces differences by race in factors affecting cancer outcomes. Variants in DNA damage repair genes and HOXB13 may be important cancer risk factors for Black men diagnosed with prostate cancer, and are more frequently observed in men with a family history of cancer. ROCS participants reported high rates of a family history of cancer. The high rate of eligibility for Cancer genetic counseling among ROCS participants supports the need for interventions to increase referrals and uptake of genetic counseling among African Americans 60% of ROCS participants reported participating in regular physical activity (PA), with 24% reporting ≥150 min/wk. There were no differences by sex, but prostate cancer survivors were the most likely to report participating in regular PA, whereas lung cancer survivors were the least likely. Survivors who reported participating in regular PA reported higher health-related quality of life and lower depression. More African American than White survivors reported financial hardship and limiting care. More White than African American survivors reported utilizing assets, while more African American survivors reported cancer-related debt. Data available in dbGaP: Individual phenotype data Individual genotype data Individual sequencing dataSample types: Germline DNA

  Study phs003116

• EGA file encryption types

  EGA file encryption The European Genome-Phenome Archive (EGA) stands as a significant initiative in the field of genomics, facilitating the secure storage and sharing of vast amounts of genomic data. Jointly hosted by the Centre for Genomic Regulation (CRG) and the European Bioinformatics Institute (EMBL-EBI), the EGA offers a robust infrastructure for managing encrypted data, ensuring the privacy and integrity of sensitive genomic information. Both CRG and EMBL-EBI play pivotal roles in the EGA, each institution bringing unique expertise in managing different types of encryptions. EMBL-EBI EGACryptor encryption system, while CRG utilises Crypt4GH, resulting in two distinct encryption file types: cip and c4gh, respectively. How can I check the file encryption? To access your dataset of interest on the European Genome-Phenome Archive (EGA) and determine the corresponding encryption file extension, please follow these step-by-step instructions: Utilise the search or navigation features provided on the EGA website to locate the dataset you are interested in. Once you find the dataset webpage, click on the "Files" tab, typically located on the dataset's webpage. Upon reaching the "Files" tab, you will be presented with a table containing comprehensive information about the files associated with the dataset. This table will include various columns, such as "File Name," "Size," and "Location." The "Location" column is particularly relevant for determining the encryption file extension. Figure 1: File table showing all the information available for the files in a dataset. This table is specific for each dataset. To identify the encryption file extension corresponding to a specific file, locate the "Location" column in the table. If the file is archived in Spain, the file will have the .c4gh extension, indicating that it is encrypted using Crypt4gh. Conversely, if the file is archived in the UK, the encrypted file extension will be .cip, indicating the usage of EGACryptor for encryption. It is worth noting that a file can be available in both locations, meaning it will be accessible with both file extensions (.c4gh and .cip). This allows users to choose the encryption method that aligns with their preferred platform or analysis tools.

  Documentation check-encryption-type