Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data

Autor: Chloe I Bloom, Jacques Banchereau, Mohamed Alfaki, J. Theodore Phillips, Asuncion Mejias, Octavio Ramilo, Karolina Palucka, Laurent Chiche, Farrah Kheradmand, Noémie Jourde-Chiche, Matthew C. Altman, Fleur Mougin, Davide Bedognetti, Marc Lipman, Christine M. Graham, Nicole Baldwin, Mathieu Garand, Patricia Thebault, Scott R. Presnell, Basirudeen Syed Ahamed Kabeer, Darawan Rinchai, Goran B. Klintmalm, Matthew Berry, Ganjana Lertmemongkolchai, Prasong Khaenam, Robert J. Wilkinson, Rodolphe Thiébaut, Damien Chaussabel, Virginia Pascual, Aaron Ayllon-Benitez, Anne O'Garra, Mohammed Toufiq, Elizabeth Whalen
Přispěvatelé: Wellcome Trust, National Institutes of Health, Benaroya Research Institute [Seattle] (BRI), University of Washington [Seattle], Sidra Medicine [Doha, Qatar], Baylor Institute for Immunology Research (BIIR), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), Hôpital Européen [Fondation Ambroise Paré - Marseille], Centre recherche en CardioVasculaire et Nutrition = Center for CardioVascular and Nutrition research (C2VN), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), The Francis Crick Institute [London], Imperial College London, Royal Cornwall Hospital, University of Cape Town, University College of London [London] (UCL), Khon Kaen University [Thailand] (KKU), Baylor College of Medicine (BCM), Baylor University, Ohio State University [Columbus] (OSU), Jackson Laboratory, Weill Cornell Medicine [New York], Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), Weill Cornell Medicine [Cornell University], Cornell University [New York], United States Department of Health & Human Services National Institutes of Health (NIH) - USAU01AI082110Wellcome Trust European Commission 03135Francis Crick Institute from the Wellcome Trust FC10218Cancer Research UK FC10218United States Department of Health & Human Services National Institutes of Health (NIH) - USANIH National Institute of Allergy & Infectious Diseases (NIAID)AI067854UK Research & Innovation (UKRI) FC10218United States Department of Health & Human Services National Institutes of Health (NIH) - USA U01AI115940, European Project: 104803,WT::(2014)
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Nature Communications
Nature Communications, Vol 12, Iss 1, Pp 1-19 (2021)
Nature Communications, Nature Publishing Group, 2021, 12 (1), ⟨10.1038/s41467-021-24584-w⟩
Nature Communications, 2021, 12 (1), ⟨10.1038/s41467-021-24584-w⟩
ISSN: 2041-1723
Popis: As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via: https://drinchai.shinyapps.io/BloodGen3Module/.
The blood transcriptome of human subjects can be profiled on an almost routine basis in translational research settings. Here the authors show that a fixed and well-characterized repertoire of transcriptional modules can be employed as a reusable framework for the analysis, visualization and interpretation of such data
Databáze: OpenAIRE
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