R/IDMapper-class.R

In PSICQUIC: Proteomics Standard Initiative Common QUery InterfaCe

setClass("IDMapper",
         slots=c(species="character",
                 mart="Mart"))

#----------------------------------------------------------------------------------------------------
#url.exists <- function(url) {
#   HEAD(url)$headers$status == "200"
#   }
#-------------------------------------------------------------------------------
IDMapper <- function(species)
{
    if(!species %in% "9606") {
        stop("IDMapper only supports human ID mapping for now")
        }

     # check (separately) 3 steps which must be working to create an IDMapper
    message("checking for biomart access...")
    host="www.ensembl.org"
    url <- paste0("http://", host)
    message(sprintf("   does '%s' respond?", url))
    stopifnot(url.exists(url))
    message("   creating ensembl mart");
    mart <- useMart(biomart = "ensembl", host=host)
    dataset <- "hsapiens_gene_ensembl"
    message(sprintf("   %s dataset provided?", dataset))
    available.datasets <- listDatasets(mart)$dataset

    stopifnot(dataset %in% listDatasets(mart)[,1])

    self <- new("IDMapper")
    if(species == "9606"){
       self@species <- "9606"
       message("connecting to biomart...")
       self@mart <- useMart(biomart="ENSEMBL_MART_ENSEMBL", dataset=dataset)
       }

    self

}
#-------------------------------------------------------------------------------
setGeneric("addGeneInfo", signature="object",
               function(object, tbl)
           standardGeneric("addGeneInfo"))

setGeneric("addStandardNames", signature="object",
               function(object, tbl)
           standardGeneric("addStandardNames"))

#-------------------------------------------------------------------------------
.categorize <- function(rawIDs)
{

    x <- rawIDs

    string.entries <- grep("string:", x, value=TRUE)
    uniprotkb.entries <- grep("uniprotkb:", x, value=TRUE)

        # string entries can be misconstrued as uniprot entries. prevent that
        # here

    if(length(string.entries) > 0)
        uniprotkb.entries <- setdiff(uniprotkb.entries, string.entries)

    locuslink.entries <- grep("locuslink:", x, value=TRUE)
    refseq.entries <- grep("refseq:", x, value=TRUE)
    ensembl.gene.entries <- grep("ensembl:ENSG", x, value=TRUE)
    ensembl.prot.entries <- grep("ensembl:ENSP", x, value=TRUE)
    recognized.entries <- c(uniprotkb.entries, locuslink.entries,
                            refseq.entries, ensembl.gene.entries,
                            ensembl.prot.entries, string.entries)
    unrecognized.entries <- setdiff(x, recognized.entries)

    list(ensemblGene=ensembl.gene.entries,
         ensemblProt=ensembl.prot.entries,
         locuslink=locuslink.entries,
         refseq=refseq.entries,
         string=string.entries,
         uniprotkb=uniprotkb.entries,
         unrecognized=unrecognized.entries)


} # .categorize
#-------------------------------------------------------------------------------
.translate.uniprotkb <- function(mart, entries)
{
    uniprots <- gsub(".*uniprotkb:([A-Z0-9]*).*", "\\1", entries)
    names(uniprots) <- entries
    biomart.filter <- "uniprotsptrembl"
    columns = c (biomart.filter, "entrezgene_id", "hgnc_symbol");
    tbl.uniprot.trembl <- getBM(filters=biomart.filter, values=uniprots,
                                attributes=columns, mart=mart)
    colnames(tbl.uniprot.trembl) <- c("id", "geneID", "symbol")
    raw.ids <- names(uniprots)[match(tbl.uniprot.trembl$id,
                                     as.character(uniprots))]
    tbl.uniprot.trembl$raw.id <- raw.ids

    biomart.filter <- "uniprotswissprot"
    columns = c (biomart.filter, "entrezgene_id", "hgnc_symbol");
    tbl.uniprot <- getBM(filters=biomart.filter, values=uniprots, attributes=columns,
                         mart=mart)
    colnames(tbl.uniprot) <- c("id", "geneID", "symbol")
    raw.ids <- names(uniprots)[match(tbl.uniprot$id, as.character(uniprots))]
    tbl.uniprot$raw.id <- raw.ids

    tbl <- rbind(tbl.uniprot.trembl, tbl.uniprot)
    tbl$geneID <- as.character(tbl$geneID)

        # sometimes (e.g., P34896) we get multiple geneIDs for one protein ID,
        # which shows up as multiple rows.  handle that here

    dup.ids <- names(which(as.list(table(tbl$id)) > 1))
    removers <- c()

        # for each dup'd geneID, find and store the numerically larger one/s
    for(r in seq_len(length(dup.ids))){
       geneID.int <- as.integer(subset(tbl, id == dup.ids[r])$geneID)
       biggerThanMin <- geneID.int[which(geneID.int != min(geneID.int))]
       removers <- c(removers, biggerThanMin)
       } # for r

       # find the rows with these removers, one or more big, dup'd geneIDs
    if(length(removers) > 0){
       indices.to.remove <- match(as.character(removers), tbl$geneID)
       tbl <- tbl[-indices.to.remove,]
       } # if length

    tbl

} # translate.uniprotkb
#-------------------------------------------------------------------------------
.translate.string <- function(mart, entries)
{
    tbl.string <- data.frame(id=character(0), geneID=character(0),
                             symbol=character(0), raw.id=character(0))
    if(length(entries) == 0)
        return(tbl.string)

    string.ensps <- gsub(".*\\.(ENSP[0-9]*)\\|.*", "\\1", entries)
    names(string.ensps) <- entries
    biomart.filter <- "ensembl_peptide_id"
    columns = c (biomart.filter, "entrezgene_id", "hgnc_symbol");
    tbl.string <- getBM(filters=biomart.filter, values=string.ensps,
                        attributes=columns, mart=mart)
    colnames(tbl.string) <- c("id", "geneID", "symbol")
    raw.ids <- names(string.ensps)[match(tbl.string$id, as.character(string.ensps))]
    tbl.string$raw.id <- raw.ids
    tbl.string$geneID <- as.character(tbl.string$geneID)

    tbl.string

} # .translate.string
#-------------------------------------------------------------------------------
.translate.ensemblGene <- function(mart, entries)
{
    tbl.ensg <- data.frame(id=character(0), geneID=character(0),
                             symbol=character(0), raw.id=character(0))
    if(length(entries) == 0)
        return(tbl.ensg)

    ensembl.genes <- gsub(".*ensembl:([A-Z0-9_]*).*", "\\1", entries)
    names(ensembl.genes) <- entries
    biomart.filter <- "ensembl_gene_id"
    columns = c (biomart.filter, "entrezgene_id", "hgnc_symbol");

    tbl.ensg <- getBM(filters=biomart.filter, values=ensembl.genes,
                     attributes=columns, mart=mart)
    colnames(tbl.ensg) <- c("id", "geneID", "symbol")
    raw.ids  <- names(ensembl.genes)[match(tbl.ensg$id,
                                           as.character(ensembl.genes))]
    tbl.ensg$raw.id <- raw.ids

    tbl.ensg$geneID <- as.character(tbl.ensg$geneID)

    tbl.ensg


} # .translate.ensemblGene
#-------------------------------------------------------------------------------
.translate.ensemblProt <- function(mart, entries)
{
    tbl.ensp <- data.frame(id=character(0), geneID=character(0),
                           symbol=character(0), raw.id=character(0))

    if(length(entries) == 0)
        return(tbl.ensp)

    ensembl.prots <- gsub(".*ensembl:([A-Z0-9_]*).*", "\\1", entries)
    names(ensembl.prots) <- entries
    biomart.filter <- "ensembl_peptide_id"
    columns <- c(biomart.filter,  "entrezgene_id", "hgnc_symbol")
    tbl.ensp <- getBM(filters=biomart.filter, values=ensembl.prots,
                      attributes=columns, mart=mart)
    colnames(tbl.ensp) <- c("id", "geneID", "symbol")
    raw.ids <- names(ensembl.prots)[match(tbl.ensp$id,
                                          as.character(ensembl.prots))]
    tbl.ensp$raw.id <- raw.ids

    tbl.ensp$geneID <- as.character(tbl.ensp$geneID)

    tbl.ensp


} # .translate.ensemblProt
#-------------------------------------------------------------------------------
.translate.locuslink <- function(mart, entries)
{

   tbl.entrezs <- data.frame(id=character(0), geneID=character(0),
                             symbol=character(0), raw.id=character(0))

    if(length(entries) == 0)
        return(tbl.entrezs)

    entrezs <- gsub(".*locuslink:([A-Z0-9]*).*", "\\1", entries)
    names(entrezs) <- entries
    biomart.filter <- "entrezgene_id"
    columns <- c(biomart.filter,  "entrezgene_id", "hgnc_symbol")
    tbl.entrezs <- getBM(filters=biomart.filter, values=entrezs, attributes=columns, mart=mart)
    colnames(tbl.entrezs) <- c("id", "geneID", "symbol")
    raw.ids <- names(entrezs)[match(tbl.entrezs$id, as.character(entrezs))]
    tbl.entrezs$raw.id <- raw.ids

    tbl.entrezs$geneID <- as.character(tbl.entrezs$geneID)

    tbl.entrezs


} # .translate.locuslink
#-------------------------------------------------------------------------------
.translate.refseq <- function(mart, entries)
{
    tbl.refseq <- data.frame(id=character(0), geneID=character(0),
                             symbol=character(0), raw.id=character(0))
    if(length(entries) == 0)
        return(tbl.refseq)

    refseqs <- gsub(".*refseq:([A-Z0-9_]*).*", "\\1", entries)
    names(refseqs) <- entries
    biomart.filter <- "refseq_peptide"
    columns <- c(biomart.filter,  "entrezgene_id", "hgnc_symbol")
    tbl.refseqs <- getBM(filters=biomart.filter, values=refseqs,
                          attributes=columns, mart=mart)
    colnames(tbl.refseqs) <- c("id", "geneID", "symbol")
    raw.ids <- names(refseqs)[match(tbl.refseqs$id, as.character(refseqs))]
    tbl.refseqs$raw.id <- raw.ids

    tbl.refseqs$geneID <- as.character(tbl.refseqs$geneID)

    tbl.refseqs

} # .translate.refseq
#-------------------------------------------------------------------------------
.translate.geneSymbol <- function(mart, entries)
{
    tbl.geneSymbol <- data.frame(id=character(0), geneID=character(0),
                                 symbol=character(0), raw.id=character(0))
    if(length(entries) == 0)
        return(NA)

    refseqs <- gsub(".*refseq:([A-Z0-9_]*).*", "\\1", entries)
    names(refseqs) <- entries
    biomart.filter <- "refseq_peptide"
    columns <- c(biomart.filter,  "entrezgene_id", "hgnc_symbol")
    tbl.refseqs <- getBM(filters=biomart.filter, values=refseqs,
                          attributes=columns, mart=mart)
    colnames(tbl.refseqs) <- c("id", "geneID", "symbol")
    raw.ids <- names(refseqs)[match(tbl.refseqs$id, as.character(refseqs))]
    tbl.refseqs$raw.id <- raw.ids

    tbl.refseqs$geneID <- as.character(tbl.refseqs$geneID)

    tbl.refseqs

} # .translate.geneSymbol
#-------------------------------------------------------------------------------
.translateAll <- function(mart, raw.ids)
{
    categories <- .categorize(raw.ids)
    result <- data.frame()
    for(category in names(categories)){
        ids <- categories[[category]]
        if(length(ids) > 0){
            if(category == "ensemblGene")
                result <- rbind(result, .translate.ensemblGene(mart, ids))
             if(category == "ensemblProt")
                result <- rbind(result, .translate.ensemblProt(mart, ids))
            if(category == "locuslink")
                result <- rbind(result, .translate.locuslink(mart, ids))
            if(category == "refseq")
                result <- rbind(result, .translate.refseq(mart, ids))
            if(category == "string")
                result <- rbind(result, .translate.string(mart, ids))
            if(category == "uniprotkb")
                result <- rbind(result, .translate.uniprotkb(mart, ids))
          } # if length
       } # for category

    result

} # .translateAll
#-------------------------------------------------------------------------------
setMethod("addGeneInfo", signature=c(object="IDMapper"),

   function(object, tbl) {

          # default assumption: all rows need geneInfo added
      unmapped.rows <- seq_len(nrow(tbl))

          # but in fact, some may not
      some.geneInfo.present <- all(c("A.name", "B.name", "A.id", "B.id")
                                   %in% colnames(tbl))
      if(some.geneInfo.present)
         unmapped.rows <- which(tbl$A.name == "-")

      A <- tbl$A[unmapped.rows]
      B <- tbl$B[unmapped.rows]

      raw.ids <- unique(c(A, B))

      tbl.xref <- .translateAll(object@mart, raw.ids)

         # create two named lists, for fast lookup of tbl$A and $B
      syms <- tbl.xref$symbol
      names(syms) <- tbl.xref$raw.id

      geneIDs <- tbl.xref$geneID
      names(geneIDs) <- tbl.xref$raw.id

      A.name <- as.character(syms[A])

      B.name <- as.character(syms[B])

      A.id <- as.character(geneIDs[A])
      B.id <- as.character(geneIDs[B])

      A.name[is.na(A.name)] <- "-"
      B.name[is.na(B.name)] <- "-"
      A.id[is.na(A.id)] <- "-"
      B.id[is.na(B.id)] <- "-"

      if(!some.geneInfo.present){
         empty.column <- rep("-", nrow(tbl))
         tbl <- cbind(tbl,
                      A.name=empty.column,
                      B.name=empty.column,
                      A.id=empty.column,
                      B.id=empty.column,
                      stringsAsFactors=FALSE)
         }# no previous geneInfo

      tbl$A.name[unmapped.rows] <- A.name
      tbl$B.name[unmapped.rows] <- B.name
      tbl$A.id[unmapped.rows] <- A.id
      tbl$B.id[unmapped.rows] <- B.id

      tbl

      }) # addGeneInfo
#-------------------------------------------------------------------------------
setMethod("addStandardNames", signature=c(object="IDMapper"),

   function(object, tbl) {

          # default assumption: all rows need geneInfo added
      unmapped.rows <- seq_len(nrow(tbl))

          # but in fact, some may not
      some.geneInfo.present <- all(c("A.name", "B.name", "A.id", "B.id")
                                   %in% colnames(tbl))
      if(some.geneInfo.present)
         unmapped.rows <- which(tbl$A.name == "-")

      A <- tbl$A[unmapped.rows]
      B <- tbl$B[unmapped.rows]

      raw.ids <- unique(c(A, B))

      tbl.xref <- .translateAll(object@mart, raw.ids)

         # create two named lists, for fast lookup of tbl$A and $B
      syms <- tbl.xref$symbol
      names(syms) <- tbl.xref$raw.id

      geneIDs <- tbl.xref$geneID
      names(geneIDs) <- tbl.xref$raw.id

      A.name <- as.character(syms[A])

      B.name <- as.character(syms[B])

      A.id <- as.character(geneIDs[A])
      B.id <- as.character(geneIDs[B])

      A.name[is.na(A.name)] <- "-"
      B.name[is.na(B.name)] <- "-"
      A.id[is.na(A.id)] <- "-"
      B.id[is.na(B.id)] <- "-"

      if(!some.geneInfo.present){
         empty.column <- rep("-", nrow(tbl))
         tbl <- cbind(tbl,
                      A.name=empty.column,
                      B.name=empty.column,
                      A.id=empty.column,
                      B.id=empty.column,
                      stringsAsFactors=FALSE)
         }# no previous geneInfo

      tbl$A.name[unmapped.rows] <- A.name
      tbl$B.name[unmapped.rows] <- B.name
      tbl$A.id[unmapped.rows] <- A.id
      tbl$B.id[unmapped.rows] <- B.id

      tbl

      }) # addGeneInfo
#-------------------------------------------------------------------------------