Description Usage Arguments Value Examples

Iterative clustering algorithm for single cell RNAseq dataset

1 2 | ```
iter_clust(norm.dat, select.cells = colnames(norm.dat), prefix = NULL,
split.size = 10, result = NULL, method = "auto", ...)
``` |

`norm.dat` |
normalized expression data matrix in log transform, using genes as rows, and cells and columns. Users can use log2(FPKM+1) or log2(CPM+1) |

`select.cells` |
The cells to be clustered |

`prefix` |
The character string to indicate current iteration. |

`split.size` |
The minimal cluster size for further splitting |

`result` |
The current clustering result as basis for further splitting. |

`method` |
Clustering method. It can be "auto", "louvain", "hclust" |

`...` |
Other parameters passed to method 'onestep_clust()' |

Clustering result is returned as a list with two elements: cl: cluster membership for each cell markers: top markers that seperate clusters

1 2 | ```
clust.result <- iter_clust(norm.dat)
clust.result <- iter_clust(norm.dat, de.param = de_param(q1.th = 0.5, de.score.th = 100))
``` |

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