mds_plot: MDS Plot

Description Usage Arguments Value Examples

View source: R/mds_plot.R

Description

Calculates a simmilarity/dissimlarity index or metrix for each sample-sample pair and reduces the resulting dist matrix into two dimensions

Usage

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mds_plot(
  your_SE,
  group_by = "SAMPLENAME",
  method_dist = "bray",
  assay = "proportions",
  your_title = NULL,
  point_size = 3,
  text_size = 12,
  return_table = FALSE,
  kmeans_cluster = FALSE,
  k.param = 3,
  draw_ellipses = FALSE
)

Arguments

your_SE

Summarized Experiment object containing clonal tracking data as created by the barcodetrackR 'create_SE' function.

group_by

Column of metadata to color samples by. Can also specify "kmeans_cluster" if kmeans_cluster argument is set to TRUE, and then the grouping variables will be the clusterinng result.

method_dist

Dissimilarity index from vegan. One of "manhattan", "euclidean", "canberra", "clark", "bray", "kulczynski", "jaccard", "gower", "altGower", "morisita", "horn", "mountford", "raup", "binomial", "chao", or "cao".

assay

The assay to calculate the index on

your_title

Character. The title for the plot.

point_size

Numeric. The size of the points.

text_size

Numeric. Size of text in plot.

return_table

Logical. If set to true, the function will return a dataframe containing each samples reduced measure of dissimilarity coordinates.

kmeans_cluster

Logical. If set to true, each sample will be assigned a cluster computed by kmeans on the chosen assay.

k.param

Numeric. If kmeans_cluster is TRUE, provide the number of kmeans clusters to identify.

draw_ellipses

Logical. If kmeans_cluster is TRUE, draw ellipses around the different kmeans clusters.

Value

Plots dissimilarity indices between samples in your_SE. Or if return table is set to TRUE, returns a dataframe of each sample's reduced measures of dissimilarity coordinates.

Examples

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data(wu_subset)
mds_plot(your_SE = wu_subset, method_dist = "bray", group_by = "celltype")
# "

d93espinoza/barcodetrackR documentation built on April 28, 2021, 1:58 p.m.