Chart the original Euclidean distances between data points (x-axis) versus Euclidean distances in reduced 2-dimensional space. The Spearman's rank correlation coefficient is shown.

This blog post describe the interpretation of plots with dimension reduction performed by different algorithms.

Note that t-SNE is particularly sensitive to the choice of random seed (which can be amended via the R code) and consequently the t-SNE correlation coefficient may vary depending on the seed.

## Example

**Example output:**

**Input Example:**

An analysis using t-SNE, MDS, or PCA.

## Options

**Dimension Reduction** An R Output containing a principal components, multidimensional scaling or t-SNE analysis.

**Maximum points** The maximum number of points to plot. If the object contains more data points, a random sample is taken.

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