Local statistics allow quantification of cell-to-cell variability from high-throughput microscope images.
Ontology highlight
ABSTRACT: Motivation
Quantifying variability in protein expression is a major goal of systems biology and cell-to-cell variability in subcellular localization pattern has not been systematically quantified.Results
We define a local measure to quantify cell-to-cell variability in high-throughput microscope images and show that it allows comparable measures of variability for proteins with diverse subcellular localizations. We systematically estimate cell-to-cell variability in the yeast GFP collection and identify examples of proteins that show cell-to-cell variability in their subcellular localization.Conclusions
Automated image analysis methods can be used to quantify cell-to-cell variability in microscope images.
SUBMITTER: Handfield LF
PROVIDER: S-EPMC4380034 | biostudies-literature | 2015 Mar
REPOSITORIES: biostudies-literature
Publications
Local statistics allow quantification of cell-to-cell variability from high-throughput microscope images.
Handfield Louis-François LF Strome Bob B Chong Yolanda T YT Moses Alan M AM
Bioinformatics (Oxford, England) 20141114 6
<h4>Motivation</h4>Quantifying variability in protein expression is a major goal of systems biology and cell-to-cell variability in subcellular localization pattern has not been systematically quantified.<h4>Results</h4>We define a local measure to quantify cell-to-cell variability in high-throughput microscope images and show that it allows comparable measures of variability for proteins with diverse subcellular localizations. We systematically estimate cell-to-cell variability in the yeast GFP ...[more]
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