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.

Ma, C., Wang, X. (2012). Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis Plant Physiology 160(1), 192-203.

Chuang Ma
Professor, Doctoral Supervisor

My research interests include artificial intelligence, abiotic stress and plant breeding.