CFAssay: statistical analysis of the colony formation assay.

Background: Colony formation assay is the gold standard to determine cell reproductive death after treatment with ionizing radiation, applied for different cell lines or in combination with other treatment modalities. Associated linear-quadratic cell survival curves can be calculated with different...

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Publicado en:Radiation Oncology Vol. 10; no. 1; pp. 1 - 7
Autores principales: Braselmann, Herbert, Michna, Agata, Heß, Julia, Unger, Kristian
Formato: Journal Article
Publicado: BioMed Central 11/4/2015
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 11/4/2015
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      pub: BioMed Central
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        atl: CFAssay: statistical analysis of the colony formation assay.
      aug:
        au:
          Braselmann, Herbert
          Michna, Agata
          Heß, Julia
          Unger, Kristian
        affil: Research Unit Radiation Cytogenetics, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Neuherberg, Germany
      sug:
        subj:
          Cell Physiology Radiation Effects
          Cytological Techniques
          Software
          Cell Line, Tumor
          Radiation, Ionizing
          Probability
          Ferrans and Powers Quality of Life Index
      ab: Background: Colony formation assay is the gold standard to determine cell reproductive death after treatment with ionizing radiation, applied for different cell lines or in combination with other treatment modalities. Associated linear-quadratic cell survival curves can be calculated with different methods. For easy code exchange and methodological standardisation among collaborating laboratories a software package CFAssay for R (R Core Team, R: A Language and Environment for Statistical Computing, 2014) was established to perform thorough statistical analysis of linear-quadratic cell survival curves after treatment with ionizing radiation and of two-way designs of experiments with chemical treatments only.Methods: CFAssay offers maximum likelihood and related methods by default and the least squares or weighted least squares method can be optionally chosen. A test for comparision of cell survival curves and an ANOVA test for experimental two-way designs are provided.Results: For the two presented examples estimated parameters do not differ much between maximum-likelihood and least squares. However the dispersion parameter of the quasi-likelihood method is much more sensitive for statistical variation in the data than the multiple R (2) coefficient of determination from the least squares method.Conclusion: The dispersion parameter for goodness of fit and different plot functions in CFAssay help to evaluate experimental data quality. As open source software interlaboratory code sharing between users is facilitated.Availability: The package is available at http://www.bioconductor.org/packages/release/bioc/html/CFAssay.html .
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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