Description Usage Arguments Value Examples

perform the SIMLR clustering algorithm

1 2 3 4 5 6 7 8 9 |

`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 |

`no.dim` |
number of dimensions |

`k` |
tuning parameter |

`if.impute` |
should I traspose the input data? |

`normalize` |
should I normalize the input data? |

`cores.ratio` |
ratio of the number of cores to be used when computing the multi-kernel |

clusters the cells based on SIMLR 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, S = similarities computed by SIMLR, F = results from network diffiusion, ydata = data referring the the results by k-means, alphaK = clustering coefficients, execution.time = execution time of the present run, converge = iterative convergence values by T-SNE, LF = parameters of the clustering

1 | ```
SIMLR(X = BuettnerFlorian$in_X, c = BuettnerFlorian$n_clust, cores.ratio = 0)
``` |

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