splitTestClusters: Split test clusters according to AUROC similarity to train...
In MetaNeighbor: Single cell replicability analysis
Description
Usage
Arguments
Value
See Also
Description
This function computes hierarchical clustering to group similar test
clusters, using similarity to train clusters as features, then uses a
standard tree cutting algorithm to obtain groups of similar clusters.
Note that the cluster hierarchy does *not* correspond to the row ordering of
plotHeatmapPretrained function, which uses a different heuristic.
Usage
1
splitTestClusters(mn_scores, k)
Arguments
mn_scores
An AUROC matrix as generated by MetaNeighborUS, usually with
the "trained_model" option.
k
The number of desired cluster sets.
Value
A list of cluster sets, each cluster set is a character vector
containg cluster labels.
See Also
MetaNeighbor documentation built on Nov. 8, 2020, 5:40 p.m.
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Description Usage Arguments Value See Also
Description
This function computes hierarchical clustering to group similar test clusters, using similarity to train clusters as features, then uses a standard tree cutting algorithm to obtain groups of similar clusters. Note that the cluster hierarchy does *not* correspond to the row ordering of plotHeatmapPretrained function, which uses a different heuristic.
Usage
1 | splitTestClusters(mn_scores, k)
|
Arguments
mn_scores |
An AUROC matrix as generated by MetaNeighborUS, usually with the "trained_model" option. |
k |
The number of desired cluster sets. |
Value
A list of cluster sets, each cluster set is a character vector containg cluster labels.
See Also
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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