1 CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China and University of Chinese Academy of Sciences, Beijing, China2 Computational and Modeling Sciences, Platform Technologies and Science China, Shanghai, GSK3 CNR IAC “Mauro Picone”, Via dei Taurini 19, Roma, Italy4 Personal Genomics S.r.l, Strada Le Grazie 15, Verona, Italy
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Motivation:Cells derived by cellular engineering, i.e. differentiation of induced pluripotent stem cells and direct lineage reprogramming, carry a tremendous potential for medical applications and in particular for regenerative therapies. These approaches consist in the definition of lineage-specific experimental protocols that, by manipulation of a limited number of biological cues—niche mimicking factors, (in)activation of transcription factors, to name a few—enforce the final expression of cell-specific (marker) molecules. To date, given the intricate complexity of biological pathways, these approaches still present imperfect reprogramming fidelity, with uncertain consequences on the functional properties of the resulting cells.Results:We propose a novel tool eegc to evaluate cellular engineering processes, in a systemic rather than marker-based fashion, by integrating transcriptome profiling and functional analysis. Our method clusters genes into categories representing different states of (trans)differentiation and further performs functional and gene regulatory network analyses for each of the categories of the engineered cells, thus offering practical indications on the potential lack of the reprogramming protocol.Availability and Implementation:eegc R package is released under the GNU General Public License within the Bioconductor project, freely available at https://bioconductor.org/packages/eegc/.Contact:email@example.com or firstname.lastname@example.orgSupplementary information:Supplementary data are available at Bioinformatics online.