runUmap | R Documentation |
Run umap on the cell-cisTopic/region-cisTopic distributions.
runUmap(object, target, method = "Z-score", seed = 123, ...)
object |
Initialized cisTopic object, after the object@selected.model has been filled. |
target |
Whether dimensionality reduction should be applied on cells ('cell') or regions (region). Note that for speed and clarity reasons, dimesionality reduction on regions will only be done using the regions assigned to topics with high confidence (see binarizecisTopics()). |
method |
Select the method for processing the cell assignments: 'Z-score' and 'Probability'. In the case of regions, an additional method, 'NormTop' is available (see getRegionScores()). |
seed |
Integer for making the results reproducible. |
... |
See |
'Z-score' computes the Z-score for each topic assingment per cell/region. 'Probability' divides the topic assignments by the total number
of assignments in the cell/region in the last iteration plus alpha. If using 'NormTop', regions are given an score defined by: \beta_{w, k} (\log
\beta_{w,k} - 1 / K \sum_{k'} \log \beta_{w,k'})
.
Returns a cisTopic object with the umap coordinates stored in object@dr in object@dr$cell$umap or object@dr$region$umap depending on the target.
cisTopicObject <- runtSNE(cisTopicobject, target='cell', method='Z-score')
cisTopicObject
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