createStatisticalAdjacency {MetNet} | R Documentation

## Create statistical adjacency matrix

### Description

`createStatisticalAdjacency` creates a consensus adjacency matrix given the models to use.

### Usage

    createStatisticalAdjacency(x, model, threshold=1, ...)

### Arguments

`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 `method="central.graph"` threshold is set to 1 by default. For other values of method, the value should be carefully defined by the user. If threshold is set to NULL (default), it will be set to 1 internally.
`...` | parameters passed to the functions `lasso`, `randomForest`, `clr`, `aracne`, `correlation`, `bayes` and/or `consensusAdjacency`

### Details

`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).

### Value

matrix, containing binary values if a connection is present or not

### Author(s)

Thomas Naake, thomasnaake@googlemail.com

### Examples

    data("x_test", package="MetNet")
    x <- x_test[, 3:dim(x_test)[2]]
    x <- as.matrix(x)
    createStatisticalAdjacency(x, c("pearson", "spearman"))

[Package MetNet version 1.2.0 Index]