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Fig. 1 | Journal of Translational Medicine

Fig. 1

From: A modular framework for the development of targeted Covid-19 blood transcript profiling panels

Fig. 1

Design of targeted blood transcript panels for Covid-19 disease immune profiling. The first selection steps are data-driven (ac). They consist in identifying co-expressed sets of transcripts to constitute “selection pools”. The last selection step is knowledge-driven (d). It consists in identifying transcripts among each of the selection pools which are functionally relevant for Covid-19 disease (e.g. potential therapeutic targets, molecules involved in viral entry and replication, immunological markers). a Pre-determined module repertoire. The process primarily relies on a generic collection of co-expressed gene sets (transcriptional modules) that were developed using an approach described in Altman et al. [7] and in the methods section. Two dimension reduction levels are built into this modular repertoire. The least reduced level has 382 variables (modules). The most reduced level has 38 variables (module aggregates, which comprise the 382 modules). b Selection of module aggregates. Analysis of Covid-19 patient profiles is the basis for a first down-selection step from 38 to 17 module aggregates. c Delineation of homogeneous Covid-19 module sets. The next step identifies within each of the 17 aggregates subsets of modules that show high degree of expression similarity across Covid-19 patients. d Candidate transcript selection. The last step involves expert curation and consists in identifying at least one transcript within each module set. Criteria for selection can be adapted based on needs (e.g. enrichment in candidates that are immune relevant and/or potential therapeutic targets and/or of relevance to SARS biology)

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