R/makeWordCloud.r

In geneXtendeR: Optimized Functional Annotation Of ChIP-seq Data

#' Makes word cloud from gene ontology terms
#'
#' Creates word cloud from gene ontology terms derived from either biological process (BP), cellular compartment (CC), or molecular function (MF) of genes-under-peaks that are unique between two different upstream extension levels.
#'
#'
#' @param organism Object name assigned from readGFF() command.
#' @param start Lower bound of upstream extension.
#' @param end Upper bound of upstream extension.
#' @param GOcategory Either BP, CC, or MF.
#' @param GOspecies Either org.Ag.eg.db (mosquito), org.Bt.eg.db (bovine), org.Ce.eg.db (worm), org.Cf.eg.db (canine), org.Dm.eg.db (fly), org.Dr.eg.db (zebrafish), org.Gg.eg.db (chicken), org.Hs.eg.db (human), org.Mm.eg.db (mouse), org.Mmu.eg.db (rhesus), org.Pt.eg.db (chimpanzee), org.Rn.eg.db (rat), org.Sc.sgd.db (yeast), org.Ss.eg.db (pig), or org.Xl.eg.db (frog).  
#'
#' @return A word cloud comprised of words gathered from gene ontology terms of either a BP, CC, or MF category.
#'
#' @examples
#' library(rtracklayer)
#' rat <- readGFF("ftp://ftp.ensembl.org/pub/release-84/gtf/rattus_norvegicus/Rattus_norvegicus.Rnor_6.0.84.gtf.gz")
#' fpath <- system.file("extdata", "somepeaksfile.txt", package="geneXtendeR")
#' peaksInput(fpath)
#' library(tm)
#' library(SnowballC)
#' library(wordcloud)
#' library(RColorBrewer)
#' library(org.Rn.eg.db)
#' makeWordCloud(rat, 0, 500, BP, org.Rn.eg.db)
#'
#' @useDynLib geneXtendeR, .registration = TRUE
#' 
#' @importFrom tm VectorSource removeWords stopwords
#' @importFrom wordcloud wordcloud
#' @importFrom RColorBrewer brewer.pal
#' @importFrom GO.db GO.db
#'
#' @export
makeWordCloud <- function(organism, start, end, GOcategory, GOspecies) {
  if(!file.exists("peaks.txt")){
    message("Please run peaksInput() function first!  See ?peaksInput for more information")
  } else {
    #oopts = options(warn=-1)
    #n.exit(options(oopts))
    
    run2 <- function(f1, f2, peakslist) {
      .C("extractpeaks", f1, f2, peakslist)[[3]]
    }
    
    sapply(c(start, end), .geneXtender, rat, FALSE)
    twogxFiles <- sprintf("geneXtender_gtf_%s.bed", c(start, end))
    linelen <- ""  
    n <- 500000
    peaksArray <- rep(linelen, n)
    peaksArray2 <- rep(linelen, n)
    cmdtmp1 <- run2(f1 = "peaks.txt", f2 = twogxFiles[[1]], as.character(peaksArray))
    cmdtmp2 <- run2(f1 = "peaks.txt", f2 = twogxFiles[[2]], as.character(peaksArray2))
    cmd1 <- cmdtmp1[cmdtmp1 != linelen]
    cmd2 <- cmdtmp2[cmdtmp2 != linelen]
    m = regexec("^(?:[^\t]+\t){3}", cmd1)
    first3.cmd1 = unlist(regmatches(cmd1, m))
    m = regexec("^(?:[^\t]+\t){3}", cmd2)
    first3.cmd2 = unlist(regmatches(cmd2, m))
    finalList = cmd2[!(first3.cmd2 %in% first3.cmd1)]
    DT <- data.table::as.data.table(do.call("rbind", strsplit(finalList, split = "\t")))
    gene_names <- DT[[8]]
    
    if (deparse(substitute(GOcategory)) == 'BP') {
      gene_names_annotated <- AnnotationDbi::select(GOspecies, gene_names, "GO", "SYMBOL")
      gene_names_annotated_DT <- as.data.table(gene_names_annotated)
      Gene <- gene_names_annotated_DT[gene_names_annotated_DT$ONTOLOGY == 'BP']
      gene <- as.data.frame(Gene)
      terms <- AnnotationDbi::select(GO.db, as.character(gene[,2]), "TERM", "GOID")
      symbol_GOID_terms <- cbind(gene$SYMBOL, terms)
      uniq_symbol_GOID_terms <- unique(symbol_GOID_terms)
    } else if (deparse(substitute(GOcategory)) == 'CC') {
      gene_names_annotated <- AnnotationDbi::select(GOspecies, gene_names, "GO", "SYMBOL")
      gene_names_annotated_DT <- as.data.table(gene_names_annotated)
      Gene <- gene_names_annotated_DT[gene_names_annotated_DT$ONTOLOGY == 'CC']
      gene <- as.data.frame(Gene)
      terms <- AnnotationDbi::select(GO.db, as.character(gene[,2]), "TERM", "GOID")
      symbol_GOID_terms <- cbind(gene$SYMBOL, terms)
      uniq_symbol_GOID_terms <- unique(symbol_GOID_terms)
    } else if (deparse(substitute(GOcategory)) == 'MF') {
      gene_names_annotated <- AnnotationDbi::select(GOspecies, gene_names, "GO", "SYMBOL")
      gene_names_annotated_DT <- as.data.table(gene_names_annotated)
      Gene <- gene_names_annotated_DT[gene_names_annotated_DT$ONTOLOGY == 'MF']
      gene <- as.data.frame(Gene)
      terms <- AnnotationDbi::select(GO.db, as.character(gene[,2]), "TERM", "GOID")
      symbol_GOID_terms <- cbind(gene$SYMBOL, terms)
      uniq_symbol_GOID_terms <- unique(symbol_GOID_terms)
      
    } else {
      stop("Not a valid GO category.  Must be either BP, CC, or MF.")
    }
    
  
  GO_terms <- uniq_symbol_GOID_terms$TERM
  GO_terms_corpus <- tm::Corpus(VectorSource(GO_terms))
  GO_terms_corpus <- tm::tm_map(GO_terms_corpus, removeWords, stopwords("english"))
  dtm <- tm::TermDocumentMatrix(GO_terms_corpus)
  doc_term_matrix <- as.matrix(dtm)
  v <- sort(rowSums(doc_term_matrix), decreasing = TRUE)
  d <- data.frame(word = names(v), freq = v)
  
  set.seed(1234)
  wordcloud(words = d$word, 
            freq = d$freq, 
            min.freq = 1, 
            max.words = 200, 
            random.order = FALSE, 
            rot.per = 0.35, 
            colors = brewer.pal(8, "Dark2"))
  
  }
}