Local statistics allow quantification of cell-to-cell variability from high-throughput microscope images

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. We define a local measure to quantify cell-to-cell variability in high-throughput microscope images and show that...

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Veröffentlicht in:Bioinformatics 2015-03, Vol.31 (6), p.940-947
Hauptverfasser: Handfield, Louis-François, Strome, Bob, Chong, Yolanda T, Moses, Alan M
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Sprache:eng
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Zusammenfassung: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. 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. Automated image analysis methods can be used to quantify cell-to-cell variability in microscope images.
ISSN:1367-4803
1367-4811
1460-2059
DOI:10.1093/bioinformatics/btu759