computeDWNW: Down weights computation

In redsnic/CIMICE: CIMICE-R: (Markov) Chain Method to Inferr Cancer Evolution

Down weights computation

Description

Computes the Down weights formula using a Dinamic Programming approach (starting call), see vignettes for further explaination.

Usage

computeDWNW(g, freqs, no.of.children, A, normUpWeights)

Arguments

g	graph (a Directed Acyclic Graph)
freqs	observed genotype frequencies
no.of.children	number of children for each node
A	adjacency matrix of G
normUpWeights	normalized up weights as computed by normalizeUPW

Value

a vector containing the Up weights for each edge

Examples

require(dplyr)
require(igraph)
preproc <- example_dataset() %>% dataset_preprocessing
samples <- preproc[["samples"]]
freqs   <- preproc[["freqs"]]
labels  <- preproc[["labels"]]
genes   <- preproc[["genes"]]
g <- graph_non_transitive_subset_topology(samples, labels)
# prepare adj matrix
A <- as.matrix(as_adj(g))
# pre-compute exiting edges from each node
no.of.children <- get_no_of_children(A,g)
upWeights <- computeUPW(g, freqs, no.of.children, A)
normUpWeights <- normalizeUPW(g, freqs, no.of.children, A, upWeights)
computeDWNW(g, freqs, no.of.children, A, normUpWeights)

redsnic/CIMICE documentation built on March 30, 2022, 2:46 a.m.