# displayClusters: Plot given similarity matrix by clusters In SNFtool: Similarity Network Fusion

## Description

Visualize the clusters in given similarity matrix

## Usage

 `1` ```displayClusters(W, group) ```

## Arguments

 `W` Similarity matrix `group` A vector containing the labels for each sample in W.

## Value

Plots given similarity matrix with patients ordered to form clusters.

## Author(s)

Dr. Anna Goldenberg, Bo Wang, Aziz Mezlini, Feyyaz Demir

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39``` ```## First, set all the parameters: K = 20; # number of neighbors, usually (10~30) alpha = 0.5; # hyperparameter, usually (0.3~0.8) T = 10; # Number of Iterations, usually (10~20) ## Data1 is of size n x d_1, ## where n is the number of patients, d_1 is the number of genes, ## Data2 is of size n x d_2, ## where n is the number of patients, d_2 is the number of methylation data(Data1) data(Data2) ## Here, the simulation data (SNFdata) has two data types. They are complementary to each other. ## And two data types have the same number of points. ## The first half data belongs to the first cluster; the rest belongs to the second cluster. truelabel = c(matrix(1,100,1),matrix(2,100,1)); ## the ground truth of the simulated data ## Calculate distance matrices ## (here we calculate Euclidean Distance, you can use other distance, e.g,correlation) ## If the data are all continuous values, we recommend the users to perform ## standard normalization before using SNF, ## though it is optional depending on the data the users want to use. # Data1 = standardNormalization(Data1); # Data2 = standardNormalization(Data2); ## Calculate the pair-wise distance; ## If the data is continuous, we recommend to use the function "dist2" as follows Dist1 = (dist2(as.matrix(Data1),as.matrix(Data1)))^(1/2) Dist2 = (dist2(as.matrix(Data2),as.matrix(Data2)))^(1/2) ## next, construct similarity graphs W1 = affinityMatrix(Dist1, K, alpha) W2 = affinityMatrix(Dist2, K, alpha) ## These similarity graphs have complementary information about clusters. displayClusters(W1, truelabel); displayClusters(W2, truelabel); ```

SNFtool documentation built on June 11, 2021, 9:06 a.m.