We introduced the Gini correlation coefficient, a member of the family of Gini methodologies that have been widely used in economics, to infer non-linear transcriptional regulatory relationships in transcriptomics data (Figure 2). The Gini-based R package rsgcc would be an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analysis.
Figure. Gini correlation is a powerful algorithm to infer non-linear transcriptional regulatory relationships
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- Please cite the following article:
Ma C, Wang X. Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis [J]. Plant physiology. 2012 :pp-112.