sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution

Chuankai Cheng; J Cameron Thrash

doi:10.1128/MRA.00296-21

sparse-growth-curve: a Computational Pipeline for Parsing Cellular Growth Curves with Low Temporal Resolution

Microbiol Resour Announc. 2021 May 13;10(19):e00296-21. doi: 10.1128/MRA.00296-21.

Authors

Chuankai Cheng¹, J Cameron Thrash²

Affiliations

¹ Department of Biological Sciences, University of Southern California, Los Angeles, California, USA.
² Department of Biological Sciences, University of Southern California, Los Angeles, California, USA thrash@usc.edu.

Abstract

Here, we introduce a Python-based repository, sparse-growth-curve, a software package designed for parsing cellular growth curves with low temporal resolution. The repository uses cell density and time data as the input, automatically separates different growth phases, calculates the exponential growth rates, and produces multiple graphs to aid in interpretation.