pca_analysis: Generate plot for Principal Component Analysis

In Facottons/DOAGDC: A Package to Download, Organize and Analyze Genomic Data Commons (GDC) Data

Description

Generate plot for Principal Component Analysis

Usage

pca_analysis(
  tool,
  name,
  work_dir,
  pair_name = "G2_over_G1",
  width = 4,
  height = 2,
  res = 300,
  unit = "in",
  image_format = "png",
  env
)

Arguments

tool	A character string indicating which differential expression analysis tool was last used.
name	A character string indicating the desired values to be used in next analysis. For instance, "HIF3A" in the legacy gene expression matrix, "mir-1307" in the miRNA quantification matrix, or "HER2" in the protein quantification matrix.
work_dir	A character string specifying the path to work directory.
pair_name	A character string indicating which condition name should be used. When there are only two groups the default is "G2_over_G1".
width	Graphical parameters. See par for more details. As default width = 2000, height = 1500, res = 300 and unit = "px".
height	Graphical parameters. See par for more details. As default width = 2000, height = 1500, res = 300 and unit = "px".
res	Graphical parameters. See par for more details. As default width = 2000, height = 1500, res = 300 and unit = "px".
unit	Graphical parameters. See par for more details. As default width = 2000, height = 1500, res = 300 and unit = "px".
image_format	A character string indicating which image_format will be used. It could be "png" or "svg". The only unit available in "svg" is inches ('in'). The default is "png".
env	A character string containing the environment name that should be used. If none has been set yet, the function will create one in global environment following the standard criteria: 'tumor_data_base_data_type_tumor_data' or 'tumor_data_base_data_type_both_data' (for tumor and not tumor data in separated matrices).

Value

the PCAs plots.

Examples

library(DOAGDC)

# data already downloaded using the 'download_gdc' function
concatenate_expression("gene",
   name = "HIF3A",
   data_base = "legacy",
   tumor = "CHOL",
   work_dir = "~/Desktop"
)

# separating gene HIF3A expression data patients in two groups
groups_identification_mclust("gene", 2,
   name = "HIF3A",
   modelName = "E",
   env = CHOL_LEGACY_gene_tumor_data,
   tumor = "CHOL"
)

# load not normalized data
concatenate_expression("gene",
   normalization = FALSE,
   name = "HIF3A",
   data_base = "legacy",
   tumor = "CHOL",
   env = CHOL_LEGACY_gene_tumor_data,
   work_dir = "~/Desktop"
)

# start DE analysis
# considering concatenate_expression and groups_identification already runned
dea_edger(
   name = "HIF3A",
   group_gen = "mclust",
   env = CHOL_LEGACY_gene_tumor_data
)

pca_analysis("edgeR", "HIF3A", "~/Desktop",
   pair_name = "G2_over_G1",
   env = CHOL_LEGACY_gene_tumor_data
)

Facottons/DOAGDC documentation built on April 7, 2020, 3:17 a.m.