Description Usage Arguments Value Note Author(s) References See Also Examples
Function SNFc
performs SNF but first a normalization over all objects
is performed before taking the k neighbours of each object as a subset in
obtaining the kernel matrix. The function is based on the functions affinityMatrix
and snf
from the SNFtool package.
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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". |
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 |
method |
A method of normalization. Should be one of "Quantile","Fisher-Yates", "standardize","Range" or any of the first letters of these names. |
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 |
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 |
For now, only hierarchical clustering with the agnes
function is implemented.
Marijke Van Moerbeke
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
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