ge_pca: ge_pca

In oriolarques/GEGVIC: A workflow to analyse Gene Expression, Genetic Variations and Immune cell Composition of tumour samples using Next Generation Sequencing data.

ge_pca

Description

Creates a PCA plot from gene expression data using the VST transformation from the plotPCA function from the DESeq2 package.

Usage

ge_pca(
  counts,
  genes_id,
  metadata,
  response,
  design,
  colors = c("orange", "black")
)

Arguments

counts	Data frame that contains gene expression data as raw counts.
genes_id	Name of the column that contains gene identifiers. Should be one of the following:'entrezgene_id', 'ensembl_gene_id' or 'hgnc_symbol'.
metadata	Data frame that contains supporting variables to the data.
response	Unquoted name of the variable indicating the groups to analyse.
design	Variables in the design formula in the form of: 'Var1 + Var2 + ... Var_n'.
colors	Character vector indicating the colors of the different groups to compare. Default values are two: black and orange.

Value

Returns a ggplot object.

Examples

ge_pca(counts = sample_counts,
       genes_id = 'ensembl_gene_id',
       metadata = sample_metadata,
       response = MSI_status,
       design = 'MSI_status',
       colors = c('orange', 'black'))

oriolarques/GEGVIC documentation built on Oct. 30, 2024, 10:44 p.m.