Growth Score: a single metric to define growth in 96-well phenotype assays

High-throughput phenotype assays are a cornerstone of systems biology as they allow direct measurements of mutations, genes, strains, or even different genera. High-throughput methods also require data analytic methods that reduce complex time-series data to a single numeric evaluation. Here, we pre...

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Bibliographic Details
Main Authors: Daniel A. Cuevas, Robert A. Edwards
Format: Article
Language:English
Published: PeerJ Inc. 2018-04-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/4681.pdf
Description
Summary:High-throughput phenotype assays are a cornerstone of systems biology as they allow direct measurements of mutations, genes, strains, or even different genera. High-throughput methods also require data analytic methods that reduce complex time-series data to a single numeric evaluation. Here, we present the Growth Score, an improvement on the previous Growth Level formula. There is strong correlation between Growth Score and Growth Level, but the new Growth Score contains only essential growth curve properties while the formula of the previous Growth Level was convoluted and not easily interpretable. Several programs can be used to estimate the parameters required to calculate the Growth Score metric, including our PMAnalyzer pipeline.
ISSN:2167-8359