feature_select_PCA | R Documentation |
Extract genes, i.e. "features", based on the top loadings of principal components formed from the bulk expression data set
feature_select_PCA( mat = NULL, pcs = NULL, n_pcs = 10, percentile = 0.99, if_log = TRUE )
mat |
Expression matrix. Rownames are genes, colnames are single cell cluster name, and values are average single cell expression (log transformed). |
pcs |
Precalculated pcs if available, will skip over processing on mat. |
n_pcs |
Number of PCs to selected gene loadings from. See the explore_PCA_corr.Rmd vignette for details. |
percentile |
Select the percentile of absolute values of PCA loadings to select genes from. E.g. 0.999 would select the top point 1 percent of genes with the largest loadings. |
if_log |
whether the data is already log transformed |
vector of genes
feature_select_PCA( cbmc_ref, if_log = FALSE )
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