Durbin Blythe, Rocke David M
Department of Statistics, UC Davis, Davis, CA 95616, USA.
Bioinformatics. 2003 Jul 22;19(11):1360-7. doi: 10.1093/bioinformatics/btg178.
Durbin et al. (2002), Huber et al. (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency.
R and Matlab code and test data are available from the authors on request.
德宾等人（2002年）、胡贝尔等人（2002年）和芒森（2001年）分别独立引入了一族变换（广义对数族），该变换能使微阵列数据的方差稳定到一阶。我们基于博克斯和考克斯（1964年）所述的方法，引入了一种与线性模型一起估计变换参数的方法。我们还讨论了在广义对数族中找到在其他标准（如最小残差偏度和最小均值 - 方差相关性）下最优变换的方法。
可根据作者要求提供R和Matlab代码及测试数据。
