Development of a Fixed Repertoire of Blood Transcriptome Modules Based on Co-expression Patterns Across Immunological States release_vfiwsy6j45akhhpe6wwbmvdnre

by Matthew Altman, Darawan Rinchai, Nicole Baldwin, Mohammed Toufiq, Elizabeth Whalen, Mathieu Garand, Basirudeen Kabeer, Mohamed Alfaki, Scott Presnell, Prasong Khaenam, Aarón Ayllón Benítez, Fleur Mougin (+21 others)

Released as a post by Research Square.

(2020)

Abstract

<jats:title>Abstract</jats:title> As the capacity for generating large scale 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. It is meant to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome profiling data. It is supported by customized resources, which include analysis workflows, fingerprint grid plots data visualizations, interactive web applications. These provide access to a vast number of module-specific functional profiling reports, reference transcriptional profiles, and give users the ability to visualize changes in transcript abundance across the modular repertoire at different granularity levels. A use case focusing on a set of six modules comprising interferon-inducible genes is also provided. Taken together, this well-characterized set of modules may be employed for the interpretation and benchmarking of blood transcriptome profiles obtained within and across patient cohorts.
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