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
Format:	Artikel
Sprache:	eng
Schlagworte:	Bioinformatics Biology Cell Lineage Diagnostic Imaging - statistics & numerical data High-Throughput Screening Assays - methods Localization Microscopes Microscopy, Fluorescence - methods Models, Statistical Original Papers Position (location) Proteins Proteomics - methods Saccharomyces cerevisiae - metabolism Saccharomyces cerevisiae Proteins - metabolism Statistics
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container_title	Bioinformatics
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creator	Handfield, Louis-François Strome, Bob Chong, Yolanda T Moses, Alan M
description	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.
doi_str_mv	10.1093/bioinformatics/btu759
format	Article
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subjects	Bioinformatics Biology Cell Lineage Diagnostic Imaging - statistics & numerical data High-Throughput Screening Assays - methods Localization Microscopes Microscopy, Fluorescence - methods Models, Statistical Original Papers Position (location) Proteins Proteomics - methods Saccharomyces cerevisiae - metabolism Saccharomyces cerevisiae Proteins - metabolism Statistics
title	Local statistics allow quantification of cell-to-cell variability from high-throughput microscope images
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