createStatisticalAdjacency {MetNet} | R Documentation |
createStatisticalAdjacency
creates a consensus
adjacency matrix given the models to use.
createStatisticalAdjacency(x, model, threshold=1, ...)
x |
matrix that contains intensity values of features/metabolites (rows) per sample (columns). |
model, |
character, vector containing the model that will be used ("lasso", "randomForest", "clr", "aracne", "pearson", "pearson_partial", "pearson_semipartial","spearman", "spearman_partial", "spearman_semipartial", "bayes") |
threshold |
numeric, when combining the adjacency matrices the
threshold parameter defines if an edge is reported or not. For
|
... |
parameters passed to the functions |
createStatisticalAdjacency
is a wrapper function for the
functions createStatisticalAdjacencyList
and
consensusAdjacency
. See ?createStatisticalAdjacencyList
and
?consensusAdjacency
for further details. The function
createStatisticalAdjacencyList
includes functionality to caluclate adjacency matrices based on
LASSO (L1 norm)-regression, random forests, context likelihood of
relatedness (CLR), the algorithm for the reconstruction of accurate
cellular networks (ARACNE), Pearson correlation (also partial and
semipartial), Spearman correlation (also partial and semipartial)
and Constraint-based structure learning (Bayes).
matrix, containing binary values if a connection is present or not
Thomas Naake, thomasnaake@googlemail.com
data("x_test", package="MetNet") x <- x_test[, 3:dim(x_test)[2]] x <- as.matrix(x) createStatisticalAdjacency(x, c("pearson", "spearman"))