SIMLR_Large_Scale {SIMLR} | R Documentation

## SIMLR Large Scale

### Description

perform the SIMLR clustering algorithm for large scale datasets

### Usage

    SIMLR_Large_Scale(X, c, k = 10, kk = 100, if.impute = FALSE, normalize = FALSE)

### Arguments

`X` | an (m x n) data matrix of gene expression measurements of individual cells or and object of class SCESet
`c` | number of clusters to be estimated over X
`k` | tuning parameter
`kk` | number of principal components to be assessed in the PCA
`if.impute` | should I traspose the input data?
`normalize` | should I normalize the input data?

### Value

clusters the cells based on SIMLR Large Scale and their similarities

list of 8 elements describing the clusters obtained by SIMLR, of which y are the resulting clusters: y = results of k-means clusterings, S0 = similarities computed by SIMLR, F = results from the large scale iterative procedure, ydata = data referring the the results by k-means, alphaK = clustering coefficients, val = distances from the k-nearest neighbour search, ind = indeces from the k-nearest neighbour search, execution.time = execution time of the present run

### Examples

    resized = ZeiselAmit$in_X[, 1:340]
    ## Not run:
    SIMLR_Large_Scale(X = resized, c = ZeiselAmit$n_clust, k = 5, kk = 5)

    ## End(Not run)

[Package SIMLR version 1.16.0 Index]