Monod: mechanistic analysis of single-cell RNA sequencing count data

Abstract

We present the Python package Monod for the analysis of single-cell RNA sequencing count data through chemical master equation models. Monod can effectively identify biological and technical components of noise, enabling insights into potential pitfalls of standard normalization techniques. By parameterizing multidimensional distributions with biophysical variables, it provides a route to identifying and studying differential expression patterns that do not cause changes in average gene expression. The Monod framework is open-source and modular, and may be extended to more sophisticated models of variation and further experimental observables.

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