Description Usage Arguments Details Value Examples
Combines output from calculateConditionalCors for multiple batches/normalizations.
1 | combineInteractions(list_of_interaction_tables)
|
list_of_interaction_tables |
list of output from calculateConditionalCors |
Counts the number of times TF-TF interactions were inferred across multiple batches or normalizations. And counts the number of times each TF-TF-Target trio was inferred across multiple batches.
list containing two tables : pair2consists with columns "TF1", "TF2", "recurr" pair2targets with columns "TF1", "TF2", "Target", "recurr"
"recurr" is the number of batches the relationship was obsered in.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | set.seed(13)
batchA_output <- data.frame(
TF1=sample(c("A", "B", "C", "D"), 50, replace=TRUE),
TF2=sample(c("A", "B", "C", "D"), 50, replace=TRUE),
Target=sample(c("E", "F", "G", "E", "F"), 50, replace=TRUE)
)
batchA_output <- list(Int=unique(batchA_output))
batchB_output <- data.frame(
TF1=sample(c("A", "B", "C", "D"), 50, replace=TRUE),
TF2=sample(c("A", "B", "C", "D"), 50, replace=TRUE),
Target=sample(c("E", "F", "G", "E", "F"), 50, replace=TRUE)
)
batchB_output <- list(Int=unique(batchB_output))
consensus <- combineInteractions(list(batchA_output, batchB_output));
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