clustering {SingleCellSignalR} | R Documentation

## Clustering

### Description

Identifies the cell clusters, i.e. the cell subpopulations.

### Usage

    clustering(
      data,
      n.cluster = 0,
      n = 10,
      method = c("simlr", "kmeans"),
      plot = TRUE,
      pdf = TRUE,
      write = TRUE
    )

### Arguments

`data` | a data frame of n rows (genes) and m columns (cells) of read or UMI counts (note : rownames(data)=genes)
`n.cluster` | a number, an estimation of the ideal number of clusters is computed if equal to 0
`n` | a number, the maximum to consider for an automatic determination of the ideal number of clusters
`method` | "kmeans" or "simlr"
`plot` | a logical
`pdf` | a logical
`write` | a logical

### Details

If the user knows the number of clusters present in her data set, then 'n.cluster' can be set and the estimation of the number of clusters is skipped. 'n' is the maximum number of clusters that the automatic estimation of the number of clusters will consider. It is ignored if 'n.cluster' is provided. 'method' must be "simlr" or "kmeans" exclusively. If set to "simlr", then the function uses the **SIMLR()** function (**SIMLR** package) to perform clustering. If set to "kmeans" the function will perform a dimensionality reduction by principal component analysis (PCA) followed by K-means clustering and 2-dimensional projection by t-distributed stochastic neighbor embedding (t-SNE). Regardless of the value of 'method' ("simlr" or "kmeans"), in case 'n.cluster' is not provided, then the function relies on the **SIMLR_Estimate_Number_of_Clusters()** function to determine the number of clusters, between 2 and 'n'. If 'plot' is TRUE, then the function displays the t-SNE map with each cell colored according to the cluster it belongs to. If 'method' argument is "simlr", then it further displays a heatmap of the similarity matrix calculated by the **SIMLR()** function. If 'pdf' is TRUE, then the function exports the t-SNE plot in a pdf file in the *images* folder. The file is named "t-SNE_map-X.pdf", where X is the 'method' argument. If 'write' is TRUE, then the function writes two text files in the *data* folder. The first one is called "cluster-Y-X.txt", containing the cluster vector assigning each cell of 'data' to a cluster. The second one is called "tsne-Y-X.txt", containing the coordinates of each cell in the 2D t-SNE projection. "X" is the 'method' argument anf "Y" is the retained number of clusters.

### Value

The function returns a list containing a numeric vector specifying the cluster assignment for each cell, a 2D t-SNE projection, and the number of cells per cluster.

### Examples

    data=matrix(runif(100000,0,1),nrow=500,ncol=200)
    clustering(data,n.cluster=2,method="kmeans")

[Package SingleCellSignalR version 1.2.0 Index]