Estimation of fluorescence-tagged RNA numbers from spot intensities

• DOI: 10.1093/bioinformatics/btt766
• Publication Date: 2014-01-04T02:03:14Z
• Authors: Antti Häkkinen; Meenakshisundaram...; Stefania Garasto; Andre S. Ribeiro
• Keywords: RNA, Bacterial; 0303 health sciences; 03 medical and health sciences; Microscopy, Fluorescence; Escherichia coli; Fluorescence; 3. Good health

Abstract Motivation: Present research on gene expression using live cell imaging and fluorescent proteins or tagged RNA requires accurate automated methods of quantification these molecules from the images. Here, we propose a novel method for classifying pixel intensities spots to numbers. Results: The relies new model intensity distributions RNAs, which estimated parameter values in maximum likelihood sense measurement data, constructed posteriori classifier estimate numbers spots. We applied number RNAs individual Escherichia coli cells containing coding an with MS2-GFP binding sites. tested two constructs, either 96 48 sites, obtained similar numbers, showing that is adaptive. further show results agree uses time series data quantitative polymerase chain reaction measurements. Lastly, simulated realistic ranges. This should, general, be applicable single-cell measurements low-copy fluorescence-tagged molecules. Availability implementation: MATLAB extensions written C estimation finding decision boundaries are available under Mozilla public license at http://www.cs.tut.fi/%7ehakkin22/estrna/. Contact: [e-mail]