module_ic: module_ic

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

module_ic

Description

Estimates the composition of immune cell composition from RNA-seq raw data. Additionally it calculates an immunophenogram and immunophenoscores for each sample and groups of study.

Usage

module_ic(
  counts,
  genes_id,
  biomart,
  indications = NULL,
  cibersort = NULL,
  tumor = TRUE,
  rmgenes = NULL,
  scale_mrna = TRUE,
  expected_cell_types = NULL,
  metadata,
  response,
  compare = NULL,
  p_label = "p.format",
  colors = c("orange", "black"),
  points = TRUE
)

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:'entrez_gene_id', 'ensemblgene_id' or 'hgnc_symbol'.
biomart	Data frame containing a biomaRt query with the following attributes: ensembl_gene_id, hgnc_symbol, entrezgene_id, transcript_length, refseq_mrna. In the case of mus musculus data, external_gene_name must be obtained and then change the column name for hgnc_symbol. Uploaded biomaRt queries in GEGVIC: 'ensembl_biomartGRCh37', ensembl_biomartGRCh38_p13' and 'ensembl_biomartGRCm38_p6', 'ensembl_biomartGRCm39'.
indications	Character vector of cancer type codes for each sample in the tpm matrix.This is used by TIMER method. Indications supported can be checked using immunedeconv::timer_available_cancers. Default value is NULL.
cibersort	Path to the CIBERSORT.R and LM22.txt files. Default value is NULL.
tumor	Logical value to define if samples are tumors. If so EPIC and quanTIseq use a signature matrix/procedure optimized for tumor samples. Default value is TRUE.
rmgenes	A character vector of gene symbols. Exclude these genes from the analysis. Use this to exclude e.g. noisy genes.
scale_mrna	Logical. If FALSE, disable correction for mRNA content of different cell types. This is supported by methods that compute an absolute score (EPIC and quanTIseq). Default value is TRUE.
expected_cell_types	Limit the analysis to the cell types given in this list. If the cell types present in the sample are known a priori, setting this can improve results for xCell (see https://github.com/grst/immunedeconv/issues/1).
metadata	Data frame that contains supporting variables to the data.
response	Unquoted name of the variable indicating the groups to analyse.
compare	A character string indicating which method to be used for comparing means. Options are 't.test' and 'wilcox.test' for two groups or 'anova' and 'kruskal.test' for more groups. Default value is NULL.
p_label	Character string specifying label type. Allowed values include 'p.signif' (shows the significance levels), 'p.format' (shows the formatted p-value).
colors	Character vector indicating the colors of the different groups to compare. Default values are two: black and orange.
points	Logical value to decide if points are added to the plot.

Value

Returns ggplot objects showing predicted immune cell populations to be compared between or within samples. Also it returns a list of tables with the data necessary to produce the plots.

Examples

tables_module_ic <- module_ic(counts = sample_counts,
                              genes_id = 'ensembl_gene_id',
                              biomart = ensembl_biomart_GRCh38_p13,
                              indications = rep('coad', ncol(sample_counts[-1])),
                              cibersort = NULL,
                              metadata = sample_metadata,
                              response = MSI_status,
                              compare = 'wilcox.test',
                              p_label = 'p.format',
                              colors = c('orange', 'black'),
                              points = TRUE)

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