Herein we introduce flowFit, a Bioconductor package designed to perform quantitative analysis of cell proliferation in tracking dye-based experiments. The software, distributed as an R Bioconductor library, is based on a mathematical model that takes into account the height of each peak, the size and position of the parental population (labeled but not proliferating) and the estimated distance between the brightness of a cell and the brightness of its daughter (in which the dye is assumed to undergo a 2-fold dilution). Although the algorithm does not make any inference on cell types, rates of cell divisions or rates of cell death, it deconvolutes the actual collected data into a set of peaks, whereby each peak corresponds to a subpopulation of cells that have divided N times. We validated flowFit by retrospective analysis of published proliferation-tracking experiments and demonstrated that the algorithm predicts the same percentage of cells/generation either in samples with discernible peaks (in which the peaks are visible in the collected raw data) or in samples with non-discernible peaks (in which the peaks are fused together). To the best of our knowledge, flowFit represents the first open-source algorithm in its category and might be applied to numerous areas of cell biology in which quantitative deconvolution of tracking dye-based experiments is desired, including stem cell research.

flowFit : a bioconductor package to estimate proliferation in cell-tracking dye studies / D. Rambaldi, S. Pece, P.P. Di Fiore. - In: BIOINFORMATICS. - ISSN 1367-4803. - 30:14(2014 Jul), pp. 2060-2065. [10.1093/bioinformatics/btu127]

flowFit : a bioconductor package to estimate proliferation in cell-tracking dye studies

S. Pece;P.P. Di Fiore
2014-07

Abstract

Herein we introduce flowFit, a Bioconductor package designed to perform quantitative analysis of cell proliferation in tracking dye-based experiments. The software, distributed as an R Bioconductor library, is based on a mathematical model that takes into account the height of each peak, the size and position of the parental population (labeled but not proliferating) and the estimated distance between the brightness of a cell and the brightness of its daughter (in which the dye is assumed to undergo a 2-fold dilution). Although the algorithm does not make any inference on cell types, rates of cell divisions or rates of cell death, it deconvolutes the actual collected data into a set of peaks, whereby each peak corresponds to a subpopulation of cells that have divided N times. We validated flowFit by retrospective analysis of published proliferation-tracking experiments and demonstrated that the algorithm predicts the same percentage of cells/generation either in samples with discernible peaks (in which the peaks are visible in the collected raw data) or in samples with non-discernible peaks (in which the peaks are fused together). To the best of our knowledge, flowFit represents the first open-source algorithm in its category and might be applied to numerous areas of cell biology in which quantitative deconvolution of tracking dye-based experiments is desired, including stem cell research.
Settore MED/04 - Patologia Generale
2-apr-2014
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/233611
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