Original title: DESP: Demixing Cell State Profiles from Dynamic Bulk Molecular Measurements
Authors: Ahmed Youssef,Indranil Paul,Mark Crovella,Andrew Emili
In this article, the authors introduce a new algorithm called DESP that allows for the exploration of the dynamic expression of proteins and other molecules involved in developmental and pathological processes. They explain that current technical limitations prevent accurate examination of these systems on a cellular level. DESP addresses this issue by using independent estimates of cell state proportions to analyze bulk molecular measurements, specifically quantitative proteomics. The algorithm was tested on an epithelial-to-mesenchymal transition model and successfully reconstructed cell state signatures from both proteomic and transcriptomic measurements. This provided valuable insights into the regulatory mechanisms involved in this transition. Overall, DESP offers a computational framework that bridges the gap between bulk and single-cell molecular analyses, allowing for the study of proteomes and other molecular profiles at the cell state-level using established workflows. The authors have declared no competing interests.
Original article: https://www.biorxiv.org/content/10.1101/2023.01.19.524460v3