Publications by authors named "S Mangiola"

Article Synopsis
  • The rise of omic data brings new challenges in how we handle, analyze, and integrate this information, which is crucial for biological research.
  • Bioconductor serves as a comprehensive platform for community-driven analysis of biological data, while tidy R programming introduces an innovative approach for organizing and manipulating data.
  • The tidyomics software ecosystem connects Bioconductor with tidy R practices, aiming to simplify omic analysis and facilitate collaboration across different scientific disciplines, as evidenced by its successful application in analyzing a large dataset from the Human Cell Atlas.
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Article Synopsis
  • - The increasing amount of omic data creates challenges in how to manage, analyze, and integrate this information.
  • - Bioconductor offers a community-driven platform for biological data analysis, while tidy R programming introduces a new standard for organizing and manipulating data.
  • - This software ecosystem connects Bioconductor with tidy R, aiming to simplify omic analysis and foster collaborations, demonstrated through the analysis of 7.5 million cells from the Human Cell Atlas.
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Understanding tissue biology's heterogeneity is crucial for advancing precision medicine. Despite the centrality of the immune system in tissue homeostasis, a detailed and comprehensive map of immune cell distribution and interactions across human tissues and demographics remains elusive. To fill this gap, we harmonised data from 12,981 single-cell RNA sequencing samples and curated 29 million cells from 45 anatomical sites to create a comprehensive compositional and transcriptional healthy map of the healthy immune system.

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Motivation: The precise characterization of cell-type transcriptomes is pivotal to understanding cellular lineages, deconvolution of bulk transcriptomes, and clinical applications. Single-cell RNA sequencing resources like the Human Cell Atlas have revolutionised cell-type profiling. However, challenges persist due to data heterogeneity and discrepancies across different studies.

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Background: Malignant pleural effusions (MPEs) are a common complication of advanced cancers, particularly those adjacent to the pleura, such as lung and breast cancer. The pathophysiology of MPE formation remains poorly understood, and although MPEs are routinely used for the diagnosis of breast cancer patients, their composition and biology are poorly understood. It is difficult to distinguish invading malignant cells from resident mesothelial cells and to identify the directionality of interactions between these populations in the pleura.

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