Description Usage Arguments Value Examples

perform the SIMLR clustering algorithm for large scale datasets

1 | ```
SIMLR_Large_Scale(X, c, k = 10, kk = 100, if.impute = FALSE, normalize = FALSE)
``` |

`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? |

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

1 2 3 4 5 | ```
resized = ZeiselAmit$in_X[, 1:340]
## Not run:
SIMLR_Large_Scale(X = resized, c = ZeiselAmit$n_clust, k = 5, kk = 5)
## End(Not run)
``` |

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