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

Matthew C. Altman (), Darawan Rinchai (), Nicole Baldwin, Mohammed Toufiq, Elizabeth Whalen, Mathieu Garand, Basirudeen Syed Ahamed Kabeer, Mohamed Alfaki, Scott R. Presnell, Prasong Khaenam, Aaron Ayllón-Benítez, Fleur Mougin, Patricia Thébault, Laurent Chiche, Noemie Jourde-Chiche, J. Theodore Phillips, Goran Klintmalm, Anne O’Garra, Matthew Berry, Chloe Bloom, Robert J. Wilkinson, Christine M. Graham, Marc Lipman, Ganjana Lertmemongkolchai, Davide Bedognetti, Rodolphe Thiebaut, Farrah Kheradmand, Asuncion Mejias, Octavio Ramilo, Karolina Palucka, Virginia Pascual, Jacques Banchereau and Damien Chaussabel ()
Additional contact information
Matthew C. Altman: Systems Immunology, Benaroya Research Institute
Darawan Rinchai: Research Branch, Sidra Medicine
Nicole Baldwin: Baylor Institute for Immunology Research, Baylor Research Institute
Mohammed Toufiq: Research Branch, Sidra Medicine
Elizabeth Whalen: Systems Immunology, Benaroya Research Institute
Mathieu Garand: Research Branch, Sidra Medicine
Basirudeen Syed Ahamed Kabeer: Research Branch, Sidra Medicine
Mohamed Alfaki: Research Branch, Sidra Medicine
Scott R. Presnell: Systems Immunology, Benaroya Research Institute
Prasong Khaenam: Systems Immunology, Benaroya Research Institute
Aaron Ayllón-Benítez: Inserm U1219 Bordeaux Population Health Research Center, Bordeaux University
Fleur Mougin: Inserm U1219 Bordeaux Population Health Research Center, Bordeaux University
Patricia Thébault: LaBRI, CNRS UMR5800, Bordeaux University
Laurent Chiche: Hopital Européen
Noemie Jourde-Chiche: Aix-Marseille University, C2VN, INSERM 1263
J. Theodore Phillips: Baylor Institute for Immunology Research, Baylor Research Institute
Goran Klintmalm: Baylor Institute for Immunology Research, Baylor Research Institute
Anne O’Garra: Laboratory of Immunoregulation and Infection, The Francis Crick Institute
Matthew Berry: Royal Cornwall Hospitals NHS Trust
Chloe Bloom: National Heart and Lung Institute, Imperial College London
Robert J. Wilkinson: The Francis Crick Institute
Christine M. Graham: Laboratory of Immunoregulation and Infection, The Francis Crick Institute
Marc Lipman: UCL Respiratory, Division of Medicine, University College London
Ganjana Lertmemongkolchai: Centre for Research and Development of Medical Diagnostic Laboratories, Faculty of Associated Medical Sciences, Khon Kaen University
Davide Bedognetti: Research Branch, Sidra Medicine
Rodolphe Thiebaut: Inserm U1219 Bordeaux Population Health Research Center, Bordeaux University
Farrah Kheradmand: Baylor College of Medicine & Center for Translational Research on Inflammatory Diseases, Michael E. DeBakey VAMC
Asuncion Mejias: Abigail Wexner Research Institute at Nationwide Children’s Hospital and the Ohio State University School of Medicine
Octavio Ramilo: Abigail Wexner Research Institute at Nationwide Children’s Hospital and the Ohio State University School of Medicine
Karolina Palucka: Baylor Institute for Immunology Research, Baylor Research Institute
Virginia Pascual: Baylor Institute for Immunology Research, Baylor Research Institute
Jacques Banchereau: Baylor Institute for Immunology Research, Baylor Research Institute
Damien Chaussabel: Systems Immunology, Benaroya Research Institute

Nature Communications, 2021, vol. 12, issue 1, 1-19

Abstract: Abstract 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/ .

Date: 2021
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DOI: 10.1038/s41467-021-24584-w

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