LASSO_BN: LASSO regression

In BNrich: Pathway Enrichment Analysis Based on Bayesian Network

Description

LASSO regression – second step of simplification of BNs structures

Usage

LASSO_BN(BN, data_h, data_d)

Arguments

BN	A list of Bayesian networks achieved by BN_struct function
data_h	A list contains data frames related to control objects
data_d	A list contains data frames related to disease objects

Value

A list contains two lists.BN_h and BN_d are simplified BNs

Examples

#All the 187 preprocessed signaling pathways can be entered in analysis by fetch_data_file().
#But here you enter a subset of those pathways to see how this package works.
files <- system.file("extdata", "test_files_to_start.RData", package = "BNrich", mustWork = TRUE)
load(files)
Data <- system.file("extdata", "Test_DATA.RData", package = "BNrich", mustWork = TRUE)
load(Data)
uni_Result <- unify_path(dataH, dataD, MapkG = sub_mapkG, Pathway.id = path.id)
M1 <- uni_Result$mapkG1
BN <- BN_struct(M1)
data_h1 <- uni_Result$data_h
data_d1 <- uni_Result$data_d
LASSO_Result <- LASSO_BN(BN = BN , data_h = data_h1 , data_d = data_d1)

BNrich documentation built on April 14, 2020, 7:08 p.m.