get_recur_pval: Get the Recurrence P Values

In korkutlab/reflect: REcurrent Features LEveraged for Combination Therapy

Description

This employs a permutation approach to the recurrence P values. See References for details.

Usage

get_recur_pval(mat_value_clustered, df_feature = NULL)

Arguments

mat_value_clustered	A matrix of expression/alteration clustered by the sparse hierarchical clustering.
df_feature	A data frame that annotates function scores of features. It must contains columns: Feature, FunctionScore. Function score is either 1 (activating) or -1 (inhibiting). If df_feature = NULL, both 1 (activating) and -1 (inhibiting) are considered for each feature.

Value

A matrix that contains recurrence P values for each element of the input (mat_value_clustered).

References

Li X., et al. (2020) Precision combination therapies from recurrent oncogenic co-alterations doi: 10.1101/2020.06.03.132514.

Examples

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)

korkutlab/reflect documentation built on July 5, 2021, 7:38 a.m.