Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome dataMore about Open Access at the Crick
Authors listMatthew 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 Wilkinson Christine Graham Marc Lipman Ganjana Lertmemongkolchai Davide Bedognetti Rodolphe Thiebaut Farrah Kheradmand Asuncion Mejias Octavio Ramilo Karolina Palucka Virginia Pascual Jacques Banchereau Damien Chaussabel
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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/ .
Journal Nature Communications
Issue number 1