Compute per-gene correlation statistics by combining results from gene pair correlations.
A DataFrame of pairwise correlation statistics, returned by
For each gene, all of its pairs are identified and the corresponding p-values are combined using Simes' method. This tests whether the gene is involved in significant correlations to any other gene. Per-gene statistics are useful for identifying correlated genes without regard to what they are correlated with (e.g., during feature selection).
A DataFrame with one row per unique gene in
stats and containing the fields:
A field of the same type as
stats$gene1 specifying the gene identity.
Numeric, the correlation with the largest magnitude across all gene pairs involving the corresponding gene.
Numeric, the Simes p-value for this gene.
Numeric, the adjusted
p.value across all rows.
Logical, indicates whether the combined p-value is at its lower bound.
Simes RJ (1986). An improved Bonferroni procedure for multiple tests of significance. Biometrika 73:751-754.
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