| topkGenes {IntegratedJM} | R Documentation |
topkGenes
Description
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. |
Details
Returned data frame contains 6 columns, named as "Genes","FP-Effect", "p-adj(Effect)", "Unadj.Asso.","Adj.Asso.", "p-adj(Adj.Asso.)".
Value
A data frame containing top k genes according to the specified criteria from the specified set of genes.
Examples
## Not run:
topkGenes(jointModelResult=jmRes,subset_type="Effect",ranking="Pearson",k=10,sigLevel = 0.05)
## End(Not run)