get_recur_actionable_features: Get the Recurrent and Actionable Features for Each Sample
In korkutlab/reflect: REcurrent Features LEveraged for Combination Therapy

Description Usage Arguments Value Examples

Given a matrix of expression/alteration, a matrix of recurrence P values, a P value threshold, and optionally a set of actionable features, filter the recurrent and actionable features for each sample from the cohort.

get_recur_actionable_features(
  mat_value,
  mat_recur_pval,
  pval_threshold = 0.05,
  df_feature = NULL
)

`mat_value`	A matrix of expression/alteration with samples as rows and features as columns.
`mat_recur_pval`	A matrix that contains recurrence P values. It may not have the same row/column orders as mat_value, but the set of samples/features must be same between the two matrices.
`pval_threshold`	The threshold of P value below which are considered statistically significant. Default 0.05.
`df_feature`	A data frame that annotates actionability of features. It must contains columns: Feature, IsActionable. The type of IsActionable is logical. If df_feature = NULL, all features are considered to be actionable.

`df_recur_actionable`	A data frame of samples having recurrent and actionable features. It contains columns: SampleID, Feature, Feature_Value, Feature_Recur_Pval.
`mat_value_recur_actionable`	A matrix that only has recurrent and actionable element as in the input (mat_value).

library(reflect)
mat_value <- egfr_data$mat_value
wbound <- 2.0
mat_value_clustered <- sparse_hclust(mat_value, wbound)$mat_value_clustered

df_feature <- egfr_data$df_feature
mat_recur_pval <- get_recur_pval(mat_value_clustered, df_feature)

recur_actionable <- get_recur_actionable_features(mat_value, mat_recur_pval)