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• HIV-phyloTSI: Subtype-independent estimation of time since HIV-1 infection for cross-sectional measures of population incidence using deep sequence data

  Estimating the time since HIV infection (TSI) at population level is essential for tracking changes in the global HIV epidemic. Most methods for determining TSI give a binary classification of infections as recent or non-recent within a window of several months, and cannot assess the cumulative impact of an intervention. We developed a Random Forest Regression model, HIV-phyloTSI, which combines measures of within-host diversity and divergence to generate continuous TSI estimates directly from viral deep-sequencing data, with no need for additional variables. HIV-phyloTSI provides a continuous measure of TSI up to 9 years, with a mean absolute error of less than 12 months overall and less than 5 months for infections with a TSI of up to a year. It performs equally well for all major HIV subtypes based on data from African and European cohorts. We demonstrate how HIV-phyloTSI can be used for incidence estimates on a population level.

  Study EGAS50000000895

• ONGOING CHROMOSOMAL INSTABILITY ACROSS ANEUPLOID SUBTYPES OF CHILDHOOD B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA ASSOCIATES WITH DISEASE PROGRESSION

  This is the DAC for the scDNA data on the c-B-ALL datasets

  Dac EGAC50000000005

• Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

  Targeted cfDNA and WBC sequencing data from patients profiled in the study "Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer". Note that 'Exome sequencing' is listed under Dataset Type since there is no option for targeted panel sequencing.

  Dataset EGAD50000000303

• Ribosome Profiling of Macrophages during Salmonella Infection

  The aim of this study is to assess translational changes in macrophages over a time course of Salmonella infection.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001001393

• Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute

  Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000179 COPDGene_v6 Cohort. phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno

  Study phs000179

• Construction of endoscopic biopsy banking for understanding the intestinal environment in colorectal diseases and exploratory studies using these banking systems.

  Colorectal cancer is the most common type of cancer in Japan. Although some colorectal cancers have a genetic background, most colorectal cancers are sporadic. Known risk factors for colorectal cancer include smoking, obesity, lack of exercise, and red and processed meat. Furthermore, although it has been suggested that changes in the intestinal environment due to changes in diet and lifestyle may be involved in the increased incidence of colorectal cancer in Japan, the molecular mechanism has not yet been fully elucidated. The main objective of this study is to elucidate the changes in the intestinal environment that cause colorectal tumors, and also to contribute to the establishment of colorectal mucosal tissue banking in Japan.

  Study JGAS000655

• Pharmacogenomic Interactions in Glioblastoma Cell Line Models

  Glioblastoma (GBM) is a lethal disease without effective treatments. To advance toward effective therapeutic approaches that are biomarker-driven, there is a need for new targeted agents and to develop accurate preclinical models that encompass its cellular and molecular diversity. Historical cell line models poorly represent molecular diversity of GBMs, so we developed a living tissue bank encompassing 103 patient-derived GBM cell lines (PDGCLs) as a platform for preclinical pharmacogenomic investigation at scale. Thirty-four PDGCLs were submitted to a comprehensive molecular characterization of copy number alterations and mutations using whole exome sequencing (WES) and gene expression (microarrays), and tested against a panel of 390 small molecules at sixteen different duplicated concentrations. After integrating and systematically correlating molecular alterations with drug sensitivities, we yielded 8,083,140 pharmacogenomic interactions, and discovered novel drug and biomarker combinations which help to prioritize highly effective novel candidate treatments in GBM. Our findings demonstrate the utility of deep characterization of large numbers of models from a single disease to detect complex predictors of compound sensitivity, and indicate novel therapeutic approaches for a large fraction of patients with GBM.

  Study phs001793

• A Genome-Wide Association Study on Cataract and HDL in the Personalized Medicine Research Project Cohort

  The primary goals of this project are to develop and validate electronic phenotyping algorithms, to accurately identify cases and controls while maintaining a positive predictive value (PPV) of >95%, and to conduct a genome wide association study that advances understanding of two specific yet interrelated disease states, while simultaneously engaging the community in these research efforts. Lipid abnormalities and cataracts are both diseases of public health significance, they share common risk factors, and they are both complex diseases which likely have many genes contributing to disease development. Whole genome association studies with these two outcomes and environmental risk factors could yield novel data about the etiology of the two separate outcomes as well as their interaction. PhenX is a project designed to prioritize Phenotypes and eXposure measures for Genome-wide Association Studies (GWAS). The PhenX Toolkit is a valuable resource for researchers who are planning or expanding a study and would like to incorporate well established measures that have been recommended by experts in the field. We are currently interested in gene-environment interactions for "age related cataract".

  Study phs000170

• The Somatic Mutational Landscape of Thyroid Cancer in Patients with Germline PTEN Mutations

  PTEN hamartoma tumor syndrome (PHTS) is associated with a high rate of thyroid cancer and benign thyroid disease, yet nothing is known of the genomic landscape of PHTS-associated thyroid tumors. In this study, exome sequencing was performed on 58 thyroid tumors (28 cancers, 30 benign nodules) from 19 patients with PHTS, sequenced in tumor-normal pairs. Somatic variant calling was utilized to determine the somatic mutational landscape of thyroid tumors in this population. This was then compared to the known mutational landscape of sporadic thyroid cancer in the general population using sequencing data from The Cancer Genome Atlas. The primary finding of the study was that PHTS-associated thyroid tumors had a unique genomic landscape, including a high frequency of second-hit somatic PTEN alterations compared to the sporadic thyroid tumors. Additionally, PHTS-associated thyroid cancers were found to have somatic alterations in BRAF, RAS family members, and genes associated with DNA double stranded break repair. Data available through dbGAP will include tumor BAM files for each tumor, normal BAM files for each patient, and MAF files for PHTS-associated thyroid cancer and PHTS associated benign thyroid nodules.

  Study phs003640

• Identification of 19 novel loci reveals gene regulatory mechanisms determining susceptibility to testicular germ cell tumour

  Testicular germ cell tumour (TGCT) is the most common cancer in young men1,2, and is characterised by strong inherited genetic risk factors3. Here we have undertaken large-scale genome wide association study (GWAS) for TGCT, encompassing ~7,500 cases and ~23,000 controls, through the Oncoarray consortium. We identified 19 novel loci, approximately doubling the number of known TGCT risk loci to 44 (P<5x10-8)4-14 and conduct deep, high-throughput functional annotation of all risk loci. We establish a network of physical interactions for all risk SNPs to candidate casual genes in 3D space, using high-throughput chromosome conformation capture techniques (HiC) in TGCT cells. Firstly, functional evidence reveals widespread disruption of developmental transcriptional regulators, consistent with failed primordial germ cell differentiation as an initiating step in TGCT oncogenesis15. We secondly observe multiple risk loci associated with defective microtubule assembly, compatible with the high level of aneuploidy observed in TGCTs, suggesting gross chromosomal instability. Finally KIT-MAPK signalling features as a recurrently dysregulated pathway. In summary our findings substantially increase the number of known TGCT risk alleles, and provides a functional basis for disease susceptibility.

  Study EGAS00001001836