ewce_para: EWCE parallel

In neurogenomics/MultiEWCE: Multi-Scale Target Explorer

EWCE parallel

Description

Runs EWCE in parallel on multiple gene lists.

Usage

ewce_para(
  ctd,
  gene_data,
  list_name_column = "hpo_id",
  gene_column = "gene_symbol",
  list_names = unique(gene_data[[list_name_column]]),
  reps = 100,
  annotLevel = 1,
  force_new = FALSE,
  genelistSpecies = "human",
  sctSpecies = "human",
  bg = get_bg(species1 = genelistSpecies, species2 = sctSpecies, overwrite = force_new),
  min_genes = 4,
  save_dir_tmp = tempdir(),
  parallel_boot = FALSE,
  cores = 1,
  verbose = FALSE,
  ...
)

Arguments

ctd	CellTypeDataset generated using generate_celltype_data.
gene_data	data frame of gene list names and genes (see get_gene_lists).
list_name_column	The name of the gene_data column that has the gene list names.
gene_column	The name of the gene_data column that contains the genes.
list_names	character vector of gene list names.
reps	Number of random gene lists to generate (Default: 100, but should be >=10,000 for publication-quality results).
annotLevel	An integer indicating which level of sct_data to analyse (Default: 1).
force_new	Overwrite previous results in the save_dir_tmp.
genelistSpecies	Species that hits genes came from (no longer limited to just "mouse" and "human"). See list_species for all available species.
sctSpecies	Species that sct_data is currently formatted as (no longer limited to just "mouse" and "human"). See list_species for all available species.
bg	List of gene symbols containing the background gene list (including hit genes). If bg=NULL, an appropriate gene background will be created automatically.
min_genes	Minimum number of genes per list (default: 4)
save_dir_tmp	Folder to save intermediate results files to (one file per gene list). Set to NULL to skip saving temporary files.
parallel_boot	Parallelise at the level of bootstrap iterations, rather than across gene lists.
cores	The number of cores to run in parallel (e.g. 8) int.
verbose	Print messages.
...	Arguments passed on to EWCE::bootstrap_enrichment_test sct_data List generated using generate_celltype_data. hits List of gene symbols containing the target gene list. Will automatically be converted to human gene symbols if geneSizeControl=TRUE. sctSpecies_origin Species that the sct_data originally came from, regardless of its current gene format (e.g. it was previously converted from mouse to human gene orthologs). This is used for computing an appropriate backgrund. output_species Species to convert sct_data and hits to (Default: "human"). See list_species for all available species. method R package to use for gene mapping: "gprofiler" : Slower but more species and genes. "homologene" : Faster but fewer species and genes. "babelgene" : Faster but fewer species and genes. Also gives consensus scores for each gene mapping based on a several different data sources. no_cores Number of cores to parallelise bootstrapping reps over. geneSizeControl Whether you want to control for GC content and transcript length. Recommended if the gene list originates from genetic studies (Default: FALSE). If set to TRUE, then hits must be from humans. controlledCT [Optional] If not NULL, and instead is the name of a cell type, then the bootstrapping controls for expression within that cell type. mtc_method Multiple-testing correction method (passed to p.adjust). sort_results Sort enrichment results from smallest to largest p-values. localHub If working offline, add argument localHub=TRUE to work with a local, non-updated hub; It will only have resources available that have previously been downloaded. If offline, Please also see BiocManager vignette section on offline use to ensure proper functionality.

Value

Paths to saved results at "(save_dir)/(list_name).rds" (when save_dir!=NULL), or a nested list of results (when save_dir==NULL).

Examples

gene_data <- HPOExplorer::load_phenotype_to_genes()
ctd <- MSTExplorer::load_example_ctd()
list_names <- unique(gene_data$hpo_id)[seq(3)]
res_files <- ewce_para(ctd = ctd,
                       gene_data = gene_data,
                       list_names = list_names,
                       reps = 10)

neurogenomics/MultiEWCE documentation built on Sept. 28, 2024, 2:27 a.m.