Plot subgroups of PCA results as biplots

Source: R/PCA.R

A helper function draws biplots of selected PCA results from TCGA and GTEX combined data.

.selected_biplot(res.pca, df, sample_type, column_name, color)

Arguments

res.pca

PCA results from from TCGA and GTEX combined RNAseq data

df

combined RNAseq data with sample type annotation

sample_type

sample types for plot labeling

column_name

column name of annotation of primary diseases or healthy tissues for color of individuals

color

color scheme used for individual sample on the PCA

folder

sub directory name to store the output files

Details

This function

  • uses RNAseq data generated from .get_df_subset(.TCGA_GTEX_sampletype_subset, "All") for PCA

  • calls .biplot_title() to generate plot title using the input argument sample_type

It should not be used directly, only inside .plot_PCA_TCGA_GTEX() function.

Side effects:

(1) PCA biplots (PCA score plot + loading plot) on screen and as pdf files: PCA score plot shows the clusters of samples based on their similarity and loading plot shows how strongly each characteristic influences a principal component.

See also

Other helper function for PCA plotting: .biplot_title(), .biplot()

Examples

if (FALSE) {
.selected_biplot(
  res.pca = .RNAseq_PCA(df[[1]], 10), df = df[[2]],
  x = "Healthy Tissue (GTEx)", y = "sample.type", color = "#D55E00"
)
.selected_biplot(
  res.pca = .RNAseq_PCA(df[[1]], 10), df = df[[2]],
  x = "Healthy Tissue (GTEx)", y = "primary.site", color = col_vector
)
}