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Fig. 2 | BMC Systems Biology

Fig. 2

From: DGCA: A comprehensive R package for Differential Gene Correlation Analysis

Fig. 2

Workflow for the Differential Gene Correlation Analysis (DGCA) R package. Users input a gene expression matrix, a design matrix to specify the conditions, and a comparison vector to specify which conditions will be compared. DGCA then calculates the gene pair correlations within each condition, processes these correlation values, and compares them to build up a difference in correlation matrix. If permutation testing is chosen, DGCA will perform the same procedure on permuted gene expression matrices. These permutation samples are used to estimate an empirical false discovery rate. After investigators choose the significance threshold for differential correlation between conditions (if any) to choose downstream gene pairs, they can use DGCA’s capacities for visualization, gene ontology (GO) enrichment, and/or network construction

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