The topkGenes function is to identify the top genes based on different criteria.
Usage
topkGenes(jointModelResult, subset_type, ranking, k = 10, sigLevel = 0.01)
Arguments
jointModelResult
Data frame, containing the results from the fitJM function.
subset_type
Character string to specify the set of genes. It can have four values: "Effect" for only differentially expressed genes, "Correlation" for only correlated genes, "Effect and Correlation" for genes which are both differentially expressed & correlated and "Other" for the genes which are neither differentially expressed nor correlated.
ranking
Character string, specifying one of the columns of the jointModelResult data frame, based on the genes will be ranked within the selected subset.
k
Integer, specifying the number of genes, to be returned from the list of top genes. Default is 10.
sigLevel
Numeric between 0 and 1, specifying the level of significance, used to select the subset of genes.
Value
A data frame containing top k genes according to the specified criteria from the specified set of genes.
Details
Returned data frame contains 6 columns, named as "Genes","FP-Effect", "p-adj(Effect)", "Unadj.Asso.","Adj.Asso.", "p-adj(Adj.Asso.)".