Processing Single-Cell Single-Molecule Genomic Information: New Methods for New Data

Many of the ongoing developments in genomic data processing have been fueled by the remarkable advancements in high-throughput experimental techniques. These, however, have broadly utilized bulk measurements in multi-cellular substrate, yielding largely population-averaged information about biological systems. Yet, from disease to development, it is deviations from the average behaviors that play key physiological roles in many biologically- and biomedically-relevant processes. Understanding mechanisms behind these ";deviant"; dynamics then requires new single-cell single-molecule data, which correspondingly demands new data processing methods able to account for the discrete and stochastic properties that biological processes can display at these scales [1]. Here, we present a brief introduction to and highlight some of the general considerations as well as our work in the field of single-cell single-molecule genomic data processing.