performPCA: Calculate Principal Components for the Enrichment Scores
In escape: Easy single cell analysis platform for enrichment
Description
Usage
Arguments
Value
Author(s)
Examples
Description
Using all or selected enrichment scores of individual
single-cells, this function will calculate
principal components using scaled values and attach
to the output columns to use to graph later.
Usage
1
performPCA(enriched, groups)
Arguments
enriched
The output of enrichIt.
groups
The column headers to use in future graphing functions.
Value
Data frame of principal compoenents
Author(s)
Nick Borcherding
Examples
1
2
3
ES2 <- readRDS(url(
"https://ncborcherding.github.io/vignettes/escape_enrichment_results.rds"))
PCA <- performPCA(enriched = ES2, groups = c("Type", "Cluster"))
escape documentation built on Nov. 8, 2020, 8:21 p.m.
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Description Usage Arguments Value Author(s) Examples
Description
Using all or selected enrichment scores of individual single-cells, this function will calculate principal components using scaled values and attach to the output columns to use to graph later.
Usage
1 | performPCA(enriched, groups)
|
Arguments
enriched |
The output of |
groups |
The column headers to use in future graphing functions. |
Value
Data frame of principal compoenents
Author(s)
Nick Borcherding
Examples
1 2 3 | ES2 <- readRDS(url(
"https://ncborcherding.github.io/vignettes/escape_enrichment_results.rds"))
PCA <- performPCA(enriched = ES2, groups = c("Type", "Cluster"))
|
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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