tuning_prop_vars: Get the optimal isolation parameters for the multi-gene...

In LucaGiudice/Esearch3D: Leveraging gene expression and chromatin architecture to predict intergenic enhancers

Description

This function determines the optimal values for the isolation parameter in the two step propagation, one value for the propagation with the gene-fragment network and one with the fragment-fragment network

Usage

tuning_prop_vars(gf_net, ff_net, input_m, info = NULL, n_cores = 2)

Arguments

gf_net	Edge list of the chromatin interaction network such that first column are genes and second column are "FragX" fragments
ff_net	Edge list of the chromatin interaction network such that first and second column are "FragX" fragments
input_m	numeric matrix of cell profile, one column of a cell, rows are genes or fragments, values are expression or IAS
info	2-column dataframe, first column is character vector of node names, second colum is numeric vector of number of enhancer annotations associated to a node
n_cores	number of cores to run the function with parallel computing

Value

List of two elements: combinations and best_comb combinations contains all the pair of values tested best_comb contains only the optimal two values of the isolation paramter for the first and second overall propagation

LucaGiudice/Esearch3D documentation built on Dec. 17, 2021, 1:12 a.m.