# dist2: Pairwise squared Euclidean distances In SNFtool: Similarity Network Fusion

## Description

Computes the squared Euclidean distances between all pairs of data point given

## Usage

 `1` ```dist2(X, C) ```

## Arguments

 `X` A data matrix where each row is a different data point `C` A data matrix where each row is a different data point. If this matrix is the same as X, pairwise distances for all data points are computed.

## Value

Returns an N x M matrix where N is the number of rows in X and M is the number of rows in M. element (n,m) is the squared Euclidean distance between nth data point in X and mth data point in C

## Author(s)

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

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## 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) ## Calculate distance matrices(here we calculate Euclidean Distance, ## you can use other distance, e.g. correlation) Dist1 = dist2(as.matrix(Data1), as.matrix(Data1)) Dist2 = dist2(as.matrix(Data2), as.matrix(Data2)) ```

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