Gene Networks Based on the Graphical Gaussian Model
高斯图模型构建基因网络
作者:Shisong Ma,
日期:02/20/2012,
浏览量:14511,
Q&A: 1
This protocol describes how to build a gene network based on the graphical Gaussian model (GGM) from large scale microarray data. GGM uses partial correlation coefficient (pcor) to infer co-expression relationship between genes. Compared to the traditional Pearson’ correlation coefficient, partial correlation is a better measurement of direct dependency between genes. However, to calculate pcor requires a large number of observations (microarray slides) greatly exceeding the number of variables (genes). This protocol uses a regularized method to circumvent this obstacle, and is capable of building a network for ~20,000 genes from ~2,000 microarray slides. For more details, see Ma et al. (2007). For help regarding the script, please contact the author.