summarize_auroc: Compute separability (AUROC) of cell types based on marker...
In gillislab/MetaMarkers: Extract robust markers from multiple datasets
Description
Usage
Arguments
Value
Description
Compute separability (AUROC) of cell types based on marker sets.
Usage
1
summarize_auroc(scores, true_labels)
Arguments
scores
A marker score matrix as returned by score_cells or compute_marker_enrichment.
true_labels
Ground truth labels for the target cells.
Value
A marker set x true label AUROC matrix. For a given combination, the
marker scores are used as a predictor and the true labels define a binary
classification problem (do cells belong to the given cell type?).
gillislab/MetaMarkers documentation built on April 24, 2021, 9:25 p.m.
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Description Usage Arguments Value
Description
Compute separability (AUROC) of cell types based on marker sets.
Usage
1 | summarize_auroc(scores, true_labels)
|
Arguments
scores |
A marker score matrix as returned by score_cells or compute_marker_enrichment. |
true_labels |
Ground truth labels for the target cells. |
Value
A marker set x true label AUROC matrix. For a given combination, the marker scores are used as a predictor and the true labels define a binary classification problem (do cells belong to the given cell type?).
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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