gsea_plotter: gsea_plotter

In atakanekiz/SCseqtools: Deal With Your Single Cell RNAseq Data With Ease

gsea_plotter

Description

A wrapper function to create gsea plots.

Usage

gsea_plotter(
  exprs = NULL,
  preranked_genes = NULL,
  pos_marker = NULL,
  neg_marker = NULL,
  sample_id = NULL,
  sample_cluster = NULL,
  reference_id = NULL,
  reference_cluster = NULL,
  method = "s2n",
  gene_set = "hallmark",
  top_n = 10,
  gseaParam = 1,
  plot_individual = NULL,
  append_title = F,
  top_plots_title = T,
  seed = 123,
  keep_results = T,
  save_png = F,
  png_units = "in",
  png_width = 4,
  png_height = 3,
  append_to_filename = "",
  verbose = T,
  annot_text_color = "black",
  annot_text_size = 4,
  annot_text_fontface = 2,
  ...
)

Arguments

exprs	A data frame containing the gene expression values, samples and cluster information (in columns) from single cells (rows). It must include lower case column name for 'sample' and 'cluster'. This can be generated from a Seurat object using 'df_extractor' function.
preranked_genes	A named numeric vector for ranked gene expression values. This can be obtained using 'gene_ranker' function. When this is provided, the arguments for subsetting and ranking 'exprs' data frame is ignored. The idea behind this argument is to speed up GSEA analyses on the same ranked gene expression data using different gene sets without the need to recalculate the ranking in each iteration.
pos_marker	A character vector of gene names to positively gate cells (cells expressing these genes will be included in sample and reference)
neg_marker	A character vector of gene names to negatively gate cells (cells expressing these genes will be excluded from sample and reference )
sample_id	String. Name of the samples to use for the ranking. As the genes will be ranked from sample to reference in decreasing order, samples will be on the left side of enrichment plots. Regex based string matching can be applied including logic operations such as '|'. Data for this parameter should match to entries under 'sample' column from the 'expr' data frame.
sample_cluster	Which clusters to include in the analysis. Data for this parameter should match to entried under 'cluster' column from 'expr' data frame.
reference_id	Same as 'sample_id', but for reference (right side of the enrichment plots i.e. tail end of the ranking)
reference_cluster	Same as sample_cluster but for reference (right side of the enrichment plots)
method	Specify method to use for gene ranking. It can be one of the following: 's2n' (default), 'ttest', 'difference', 'ratio', 'welch', 'mwt', 'bws'. See PMID: 18344518
gene_set	reference pathway sets. It can be one of "all", "hallmark", "go", "curated", "immune", "motif", or a named list object containing genes for specific pathways.
top_n	Specify how many of the top enriched pathways are shown
gseaParam	fgsea parameter to change bar sizes
plot_individual	Select pathway to plot
append_title	Add informative titles to individual plots
top_plots_title	Add informative titles to summary plots
seed	Random seed
keep_results	Logical to store results globally
save_png	Save resulting plot as png
png_units	Png size units
png_width	width
png_height	height
append_to_filename	Custom string to add to png file
verbose	Prints the analysis details
annot_text_color	color of NES-p val annotation text
annot_text_size	size of NES-pval annotation text
annot_text_fontface	fontface of annotation text (1,2,3,4, plain-bold-italic-bold and italic)
...	Additional parameters to pass into fgsea function call. This can include things like nperm (omit for the recommended 'fgseaMultilevel' call, provide a value for 'fgseaSimple' function call), minSize, maxSize etc.

atakanekiz/SCseqtools documentation built on April 18, 2023, 12:55 a.m.