hclust_tree: Build the hierarchical clustering tree.
In KrasnitzLab/SCclust: Clustering of Single Cell Sequencing Copy Number Profiles to Identify Clones
Description
Usage
Arguments
Value
Description
Hierarchical clustering with Fisher's test p-values as distance matrix.
Also add feature coverage information for each node in the tree.
Usage
1
hclust_tree(pinmat, mat_fdr, mat_dist, hcmethod = "average")
Arguments
pinmat
The incidence table generated by calc_pinmat.
mat_fdr
The FDR matrix generated by fisher_fdr
mat_dist
The dissmilarity based on Fisher's test p-values for
hierarchical clustering.
hcmethod
Default: average
Value
A hclust objects with new items added.
KrasnitzLab/SCclust documentation built on Dec. 11, 2021, 5:12 p.m.
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Description Usage Arguments Value
Description
Hierarchical clustering with Fisher's test p-values as distance matrix. Also add feature coverage information for each node in the tree.
Usage
1 | hclust_tree(pinmat, mat_fdr, mat_dist, hcmethod = "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. |
hcmethod |
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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