summarize_fold_change: Compute signal-to-noise ratio (fold change) of cell types...
In gillislab/MetaMarkers: Extract robust markers from multiple datasets
Description
Usage
Arguments
Value
Description
Compute signal-to-noise ratio (fold change) of cell types based on marker sets.
Usage
1
summarize_fold_change(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 fold change matrix. For a given combination, the
marker scores are used as the statistic and the true labels are used to
define the two classes to compare (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 signal-to-noise ratio (fold change) of cell types based on marker sets.
Usage
1 | summarize_fold_change(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 fold change matrix. For a given combination, the marker scores are used as the statistic and the true labels are used to define the two classes to compare (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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