# Similarity Network Fusion - version b

### Description

Function `SNFb`

performs SNF but first determines the subsets
of neighbours and then normalization is performed on the neighbours only.
The function is based on the functions `affinityMatrix`

and `snf`

from the SNFtool package.

### Usage

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### Arguments

`List` |
A list of matrices of the same type. It is assumed the rows are corresponding with the objects. |

`type` |
Type indicates whether the provided matrices in "List" are either data matrices, distance matrices or clustering results obtained from the data. If type="dist" the calculation of the distance matrices is skipped and if type="clusters" the single source clustering is skipped. Type should be one of "data", "dist" or"clusters". |

`distmeasure` |
A vector of the distance measures to be used on each data matrix. Should be of "tanimoto", "euclidean", "jaccard","hamming". |

`method` |
A method of normalization. Should be one of "Quantile","Fisher-Yates", "standardize","Range" or any of the first letters of these names. |

`normalize` |
Logical. Indicates whether to normalize the distance matrices or not.
This is recommended if different distance types are used. More details
on standardization in |

`NN` |
The number of neighbours to be used in the procedure. |

`mu` |
The parameter epsilon. The value is recommended to be between 0.3 and 0.8. |

`T` |
The number of iterations. |

`clust` |
Choice of clustering function (character). Defaults to "agnes". |

`linkage` |
Choice of inter group dissimilarity (character). Defaults to "ward". |

`alpha` |
The parameter alpha to be used in the "flexible" linkage of the agnes function. Defaults to 0.625 and is only used if the linkage is set to "flexible" |

`StopRange` |
Logical. Indicates whether the distance matrices with values not between zero and one should be standardized to have so.
If FALSE the range normalization is performed. See |

### Value

The returned value is a list with two elements:

`FusedM ` |
The fused similarity matrix |

`DistM ` |
The distance matrix computed by subtracting FusedM from one |

`Clust` |
The resulting clustering |

### Note

For now, only hierarchical clustering with the `agnes`

function link is implemented.

### Author(s)

Marijke Van Moerbeke

### References

WANG, B., MEZLINI, M. A., DEMIR, F., FIUME, M., TU, Z., BRUDNO, M., HAIBE-KAINS, B., GOLDENBERG, A. (2014). Similarity Network Fusion for aggregating data types on a genomic scale. Nature. 11(3) pp. 333-337. WANG, B., MEZLINI, M. A., DEMIR, F., FIUME, M., TU, Z., BRUDNO, M., HAIBE-KAINS, B., GOLDENBERG, A. (2014). SNFtool: Similarity Network Fusion. R package version 2.2

### See Also

`SNF`

,`SNFa`

,`SNFc`

### Examples

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