hclust_tree: Build the hierarchical clustering tree.
In ananjysong/SCclust: Single Cell Copy Number Analysis and Clustering
hclust_tree R Documentation
Build the hierarchical clustering tree.
Description
Hierarchical clustering with Fisher's test p-values as distance matrix.
Also add feature coverage information for each node in the tree.
Usage
hclust_tree(pinmat, mat_fdr, mat_dist, hc_method = "average")
Arguments
pinmat
The incidence table generated by findpins.
mat_fdr
The FDR matrix generated by fdr_fisherPV
mat_dist
The dissmilarity based on Fisher's test p-values for hierarchical clustering.
hc_method
Default: average
Value
A hclust objects with new items added.
ananjysong/SCclust documentation built on April 18, 2022, 10:06 p.m.
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| hclust_tree | R Documentation |
Build the hierarchical clustering tree.
Description
Hierarchical clustering with Fisher's test p-values as distance matrix. Also add feature coverage information for each node in the tree.
Usage
hclust_tree(pinmat, mat_fdr, mat_dist, hc_method = "average")
Arguments
pinmat |
The incidence table generated by |
mat_fdr |
The FDR matrix generated by |
mat_dist |
The dissmilarity based on Fisher's test p-values for hierarchical clustering. |
hc_method |
Default: average |
Value
A hclust objects with new items added.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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