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The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation.
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http://dx.doi.org/10.1038/s41467-020-16785-6 | DOI Listing |
JMIR Cancer
September 2025
iCARE Secure Data Environment & Digital Collaboration Space, NIHR Imperial Biomedical Research Centre, London, United Kingdom.
Background: Electronic health records (EHRs) are a cornerstone of modern health care delivery, but their current configuration often fragments information across systems, impeding timely and effective clinical decision-making. In gynecological oncology, where care involves complex, multidisciplinary coordination, these limitations can significantly impact the quality and efficiency of patient management. Few studies have examined how EHR systems support clinical decision-making from the perspective of end users.
View Article and Find Full Text PDFTraffic Inj Prev
September 2025
Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, Wisconsin.
Objective: Assessment of submarining occurrence in PMHS (Post-Mortem Human Subject) testing can be challenging, particularly for obese PMHS. This study investigates varied kinetic and kinematic response parameters as potential indicators of submarining. Data from 36 whole-body PMHS frontal sled tests conducted under varying boundary conditions were analyzed, incorporating three spring-controlled seat configurations, two extreme anthropometric profiles, two crash pulses, and two seatback angles.
View Article and Find Full Text PDFJ Bras Pneumol
September 2025
. Departamento de Pneumologia do Hospital Infante D. Pedro, Unidade Local de Saúde da Região de Aveiro, Aveiro, Portugal.
Objectives: This study explores the relationship between inhaler visual identification, naming, and adherence outcomes, and evaluates the potential of combining these factors into a screening tool for identifying poor adherence.
Methods: This observational, prospective study included adult patients with COPD, asthma, or asthma+COPD who had been on chronic inhalation therapy for at least the past year. Data were collected through patient interviews and medical records.
Arq Gastroenterol
September 2025
The Japanese Society of Internal Medicine, Editorial Department, Tokyo, Japan.
Background: This study aims to analyze research trends and emerging insights into gut microbiota studies from 2015 to 2024 through bibliometric analysis techniques. By examining bibliographic data from the Web of Science (WoS) Core Collection, it seeks to identify key research topics, evolving themes, and significant shifts in gut microbiota research. The study employs co-occurrence analysis, principal component analysis (PCA), and burst detection analysis to uncover latent patterns and the development trajectory of this rapidly expanding field.
View Article and Find Full Text PDFPLoS One
September 2025
The Institute of Port Information Digitalization, China Liaoning Port Group Co. Ltd., Dalian, Liaoning, China.
Background: Underwater environments face challenges with image degradation due to light absorption and scattering, resulting in blurring, reduced contrast, and color distortion. This significantly impacts underwater exploration and environmental monitoring, necessitating advanced algorithms for effective enhancement.
Objectives: The study aims to develop an innovative underwater image enhancement algorithm that integrates physical models with deep learning to improve visual quality and surpass existing methods in performance metrics.