RSGCC

Sep 16, 2012
Code PubMed

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. https://dx.doi.org/10.1104/pp.112.201962

algorithms Arabidopsis genetics computational biology methods databases nucleic acid gene expression profiling methods gene expression regulation plant genes RNA plant analysis plant genetics ROC curve reproducibility of results sensitivity and specificity sequence analysis RNA methods statistics as topic methods transcription factors genetics transcriptome
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Chuang Ma
Principal Investigator, Professor, Doctoral Supervisor

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

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