Joint Biophysical Modeling of Paired Single-Cell RNA and Protein Measurements

Abstract

Surface protein measurements can supplement gene expression information from single-cell RNA sequencing to provide a more complete assessment of cell identity and function. Recently developed multiomic assays facilitate such measurements, and can, in principle, be utilized to understand the dynamics of transcription and translation. We develop a framework for biophysical modeling of transcription jointly with translation from single-cell data, along with a suitable technical noise model for sequencing data. We demonstrate its efficacy using simulations, and illustrate how it can be useful in practice with 10x multiomic data. Our proof-of-principle highlights the potential for jointly modeling transcription and translation as data quality and measurement accuracy improves.