gonto: Perform Gene-Ontology Pathways Enrichment

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

Description

Perform Gene-Ontology Pathways Enrichment

Usage

gonto(
  condition,
  use_genes_without_cat = TRUE,
  fdr_cutoff = 0.05,
  width = 2000,
  height = 2000,
  res = 300,
  unit = "px",
  image_format = "png",
  tool,
  id = "geneID",
  pair_name = "G2_over_G1",
  env
)

Arguments

condition	A character string containing which condition should be used: "Upregulated", "Downregulated" or "all".
use_genes_without_cat	Logical value where FALSE indicate that genes outside the category being tested will be ignored in the calculation of p-values. The default is "FALSE".
fdr_cutoff	Numerical value indicating the maximum value for FDR values. The default is 0.05.
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".
tool	A character string indicating which differential expression analysis tool was last used.
id	A character string indicating which id should be used: "hugo", "gene_symbol", "ensembl" , "refGene" or "geneid". The default is "geneid".
pair_name	A character string indicating which condition name should be used. When there are only two groups the default is "G2_over_G1".
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

Enriched terms.

Examples

# data already downloaded using the 'download_gdc' function
concatenate_exon("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_exon("gene",
    normalization = FALSE,
    name = "HIF3A",
    data_base = "legacy",
    tumor = "CHOL",
    env = CHOL_LEGACY_gene_tumor_data,
    work_dir = "~/Desktop"
)

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

gonto(
    condition = "Upregulated",
    tool = "edgeR", env = CHOL_LEGACY_gene_tumor_data
)

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