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.
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Ma, C., Wang, X. (2012). Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis Plant Physiology 160(1), 192-203. https://dx.doi.org/10.1104/pp.112.201962