FactorAssociation: Find the top gene or geneset markers for each NMF factor...
In yanwu2014/swne: Similarity Weighted Nonnegative Embedding: A method for visualizing high dimensional datasets
FactorAssociation R Documentation
Find the top gene or geneset markers for each NMF factor using pearson/spearman correlation,
or mutual information
Description
Find the top gene or geneset markers for each NMF factor using pearson/spearman correlation,
or mutual information
Usage
FactorAssociation(feature.mat, nmf.scores, n.cores = 8, metric = "IC")
Arguments
feature.mat
Feature matrix (features x samples)
nmf.scores
Factor scores (factors x samples)
n.cores
Number of cores to use
metric
Association metric: pearson, spearman, or IC (information coefficient)
Value
Features x factors matrix of associations or correlations
yanwu2014/swne documentation built on Aug. 5, 2023, 4:42 a.m.
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| FactorAssociation | R Documentation |
Find the top gene or geneset markers for each NMF factor using pearson/spearman correlation, or mutual information
Description
Find the top gene or geneset markers for each NMF factor using pearson/spearman correlation, or mutual information
Usage
FactorAssociation(feature.mat, nmf.scores, n.cores = 8, metric = "IC")
Arguments
feature.mat |
Feature matrix (features x samples) |
nmf.scores |
Factor scores (factors x samples) |
n.cores |
Number of cores to use |
metric |
Association metric: pearson, spearman, or IC (information coefficient) |
Value
Features x factors matrix of associations or correlations
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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