KBoost_human_symbol: Function for KBoost on data from a human sample annotated...

In Luisiglm/KBoost: Inference of gene regulatory networks from gene expression data

Description

Function for KBoost on data from a human sample annotated with Symbol names.

Usage

KBoost_human_symbol(X, gen_names, g, v, ite, pos_weight, neg_weight)

Arguments

X	an NxG matrix with the expression values of G genes and N samples.
gen_names	SYMBOL gene names corresponding to the columns of X.
g	a positive no., width parameter for the RBF kernel. (default g = 40)
v	a double between 0 and 1, the shrinkage parameter. (default v =0.1)
ite	an integer with the number of iterations (default ite = 3)
pos_weight	no. between 0 and 1. Prior that a TF regulate a gene.
neg_weight	no. between 0 and 1, for TF gene pairs not seen before.

Value

list with results of KBoost on a dataset with Symbol gene names.

Examples

X = rnorm(50,0,1)
X = matrix(X,10,5)
gen_names = c("TP53","YY1","CTCF","MDM2","ESR1")
grn = KBoost_human_symbol(X,gen_names,pos_weight = 0.6, neg_weight =0.4)

Luisiglm/KBoost documentation built on May 13, 2021, 7:27 p.m.