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flowFit: a Bioconductor package to estimate proliferation in cell-tracking dye studies.
MedLine Citation:
PMID:  24681909     Owner:  NLM     Status:  Publisher    
SUMMARY: 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 twofold dilution). While the algorithm does not make any inference on cell types, rates of cell divisions, or rates of cell death, it deconvolutes the actually 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 (Quah and Parish, 2012) 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.
AVAILABILITY: software page). (package vignette) (online tutorial).
Davide Rambaldi; Salvatore Pece; Pier Paolo Di Fiore
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-3-27
Journal Detail:
Title:  Bioinformatics (Oxford, England)     Volume:  -     ISSN:  1367-4811     ISO Abbreviation:  Bioinformatics     Publication Date:  2014 Mar 
Date Detail:
Created Date:  2014-3-31     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9808944     Medline TA:  Bioinformatics     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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