data matrix, which biclust function was applied to
bicResult
object of class biclust, containing result of a biclustering algorithm
number
number of bicluster from the output for the diagnostics
nResamplings
number of bootstrap replicates
replace
logical flag for bootstrap (TRUE), or sampling without replacement (FALSE)
Details
The function computes observed F statistics for row and column effect based on two-way ANOVA model. Bootstrap procedure is used to evaluate the significance of discovered bicluster.
Based on nResamplings replicates, the disribution of F statistics for row and column effects are obtained. The p-value is computed as
P(A) = F^*(A)_b > F(A)^{obs} /(nResamplings+1)
Low p-values denote non-random selection of columns for a given bicluster. Large p-values show that in other columns for a given set of genes in the bicluster structure is similar.
Hence, bicluster columns were just randomly picked by an algorithm for a set of co-regulated genes.
Value
bootstrapFstats
matrix with two columns, containing values of bootstrap F-statistics. The first column corresponds to row, the second column corresponds to column.