R/mouse2human_eset.R

In IOBR/IOBR: Immune Oncology Biological Research

#' Converting mouse gene symbol to human gene symbol of expression set.
#' 
#' This function converts mouse gene symbols to human gene symbols in an expression dataset. It supports using either an online resource (Ensembl) or a local dataset for conversion.
#'
#'
#' @param eset expression matrix or data frame
#' @param source default is ensembl, if an error is reported, set parameter to `local` and mus_human_gene_symbol will be use to convert gene symbols
#' @param is_matrix Boolean indicating if 'eset' is a matrix; defaults to TRUE. If FALSE, 'column_of_symbol' must be specified.
#' @param column_of_symbol default is null.Name of the column in 'eset' that contains gene symbols, if 'eset' is not a matrix. This parameter must be specified if 'is_matrix' is FALSE.
#'
#' @return Returns the expression set with human gene symbols for further analysis.
#' @export
#'
#' @examples
#' # Set the number of rows and columns
#' num_rows <- 200
#' num_cols <- 10
#' 
#' # Generate sample names and mouse gene symbols
#' sample_names <- paste0("Sample", 1:num_cols)
#' mouse_genes <- paste0("MouseGene", 1:num_rows)
#' 
#' # Create random data for the data frame
#' data <- matrix(runif(num_rows * num_cols), nrow = num_rows, ncol = num_cols)
#' df <- data
#' 
#' rownames(df) <- anno_gc_vm32$symbol[1:200]
#' human_data <- mouse2human_eset(df, source = "local", is_matrix = TRUE)
mouse2human_eset<-function(eset, source = "ensembl", is_matrix = TRUE, column_of_symbol = NULL, verbose = FALSE){


  if(is_matrix){
    genes<-rownames(eset)
  }else{
    eset<-remove_duplicate_genes(eset = eset, column_of_symbol = column_of_symbol)
    genes<-rownames(eset)
  }


  if(source=="ensembl"){

    require("biomaRt")
    ensembl = biomaRt:: useEnsembl(biomart="ensembl")
    if(verbose)  print(head(listDatasets(ensembl)))
    # Basic function to convert mouse to human gene names

    human = useMart("ensembl", dataset = "hsapiens_gene_ensembl")
    mouse = useMart("ensembl", dataset = "mmusculus_gene_ensembl")

    probe_data = getLDS(attributes = c("mgi_symbol"),
                        filters = "mgi_symbol",
                        values = genes ,
                        mart = mouse,
                        attributesL = c("hgnc_symbol"),
                        martL = human,
                        uniqueRows=T)
    colnames(probe_data)<-c("gene_symbol_mus", "gene_symbol_human")

  }else if(source=="local"){

    probe_data<-mus_human_gene_symbol

  }

  eset<-anno_eset(eset = eset, annotation = probe_data, symbol = "gene_symbol_human", probe = "gene_symbol_mus",method = "mean")
  return(eset)
}