CFAssay: statistical analysis of the colony formation assay.
CFAssay: statistical analysis of the colony formation assay.
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DOI：
10.1186/s13014-015-0529-y
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发表时间：
2015-11-04
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影响因子：
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通讯作者：
Unger K
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作者：
Braselmann H;Michna A;Heß J;Unger K
菌落形成试验是确定电离辐射治疗后细胞生殖死亡的金标准，适用于不同细胞系或与其他治疗方式相结合。相关的线性二次细胞存活曲线可以用不同的方法计算。为了便于合作实验室之间的代码交换和方法标准化，建立了一个软件包CFAssay For R (R Core Team, R: a Language and Environment For Statistical Computing, 2014)，用于对电离辐射处理后的线性二次元细胞存活曲线和仅化学处理的双向实验设计进行彻底的统计分析。CFAssay默认提供最大似然和相关方法，最小二乘法或加权最小二乘法可选择性选择。提供了细胞存活曲线比较检验和实验双向设计的方差分析检验。对于所提出的两个例子，估计参数在最大似然和最小二乘之间差别不大。然而，准似然方法的离散参数对数据统计变化的敏感性远高于最小二乘法的多重R2决定系数。CFAssay中拟合优度的离散参数和不同的图函数有助于评价实验数据的质量。作为开源软件，用户之间的实验室间代码共享变得更加容易。该软件包可在http://www.bioconductor.org/packages/release/bioc/html/CFAssay.html上获得。
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. 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. 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 R2 coefficient of determination from the least squares method. 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. The package is available at http://www.bioconductor.org/packages/release/bioc/html/CFAssay.html.