runPCA: Dimension reduction using PCA
In sqjin/CellChat: Inference and analysis of cell-cell communication from single-cell and spatial transcriptomics data
runPCA R Documentation
Dimension reduction using PCA
Description
Dimension reduction using PCA
Usage
runPCA(data.use, do.fast = T, dimPC = 50, seed.use = 42, weight.by.var = T)
Arguments
data.use
input data (samples in rows, features in columns)
do.fast
whether do fast PCA
dimPC
the number of components to keep
seed.use
set a seed
weight.by.var
whether use weighted pc.scores
sqjin/CellChat documentation built on Nov. 10, 2023, 4:29 a.m.
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| runPCA | R Documentation |
Dimension reduction using PCA
Description
Dimension reduction using PCA
Usage
runPCA(data.use, do.fast = T, dimPC = 50, seed.use = 42, weight.by.var = T)
Arguments
data.use |
input data (samples in rows, features in columns) |
do.fast |
whether do fast PCA |
dimPC |
the number of components to keep |
seed.use |
set a seed |
weight.by.var |
whether use weighted pc.scores |
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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