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Statistical tests to evaluate the significance of co-occurrence relationships.
Chi-squared test: Determine if the observed co-occurrence is significantly different from what would be expected by chance.
Fisher's exact test
Pointwise Mutual Information (PMI): Measures the extent to which the co-occurrence of entities is more likely than random chance.
Log-likelihood ratio: Identifies associations between entities while considering the expected frequency.
Apply the chosen statistical tests to the co-occurrence matrix to calculate p-values or other relevant statistics for each pair of entities.
Correct for multiple hypothesis testing using methods like Bonferroni correction or False Discovery Rate (FDR) correction to control for the family-wise error rate.
Implement filter options to select only
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