Statistical lower bounds on protein copy number from fluorescence expression images

摘要: Motivation: Fluorescence imaging has become a commonplace for quantitatively measuring mRNA or protein expression in cells and tissues. However, such data are usually relative—absolute concentrations molecular copy numbers typically not known. While this is satisfactory many applications, certain kinds of quantitative network modeling analysis noise, absolute measures necessary. Results: We propose two methods estimating from single uncalibrated images These rely on variability between cells, due either to steady-state fluctuations unequal distribution molecules during cell division, make their estimates. apply these 152 fluorescence Drosophila melanogaster embryos early development, generating number estimates 14 genes the segmentation network. also analyze effects noise our estimators compare with empirical findings. Finally, we confirm an observation Bar-Even et al., made much different setting Saccharomyces cerevisiae, that variance tends scale mean expression. Availability: The all drawn FlyEx (explained within), available at http://flyex.ams.sunysb.edu/FlyEx/. Data MATLAB codes algorithms described article http://www.perkinslab.ca/pubs/ZP2009.html. Contact: [email protected]