comparison pmids_to_pubtator_matrix.R @ 0:34ed44f3f85c draft

"planemo upload for repository https://github.com/dlal-group/simtext commit fd3f5b7b0506fbc460f2a281f694cb57f1c90a3c-dirty"

0:34ed44f3f85c

#!/usr/bin/env Rscript
#tool: pmids_to_pubtator_matrix
#
#The tool uses all PMIDs per row and extracts "Gene", "Disease", "Mutation", "Chemical" and "Species" terms of the 
#corresponding abstracts, using PubTator annotations. The user can choose from which categories terms should be extracted. 
#The extracted terms are united in one large binary matrix, with 0= term not present in abstracts of that row and 1= term 
#present in abstracts of that row. The user can decide if the extracted scientific terms should be extracted and used as 
#they are or if they should be grouped by their geneIDs/ meshIDs (several terms can often be grouped into one ID). 
#äAlso, by default all terms are extracted, otherwise the user can specify a number of most frequent words to be extracted per row.
#
#Input: Output of abstracts_by_pmids or tab-delimited table with columns containing PMIDs. 
#The names of the PMID columns should start with "PMID", e.g. "PMID_1", "PMID_2" etc.
#
#Output: Binary matrix in that each column represents one of the extracted terms.
#
# usage: $ pmids_to_pubtator_matrix.R [-h] [-i INPUT] [-o OUTPUT] [-n NUMBER] 
# [-c {Genes,Diseases,Mutations,Chemicals,Species} [{Genes,Diseases,Mutations,Chemicals,Species} ...]]
# 
# optional arguments:
#   -h, --help                 show help message
#   -i INPUT, --input INPUT    input file name. add path if file is not in workind directory
#   -n NUMBER, --number NUMBER Number of most frequent terms/IDs to extract. By default all terms/IDs are extracted.
#   -o OUTPUT, --output OUTPUT output file name. [default "pmids_to_pubtator_matrix_output"]
#   -c {Gene,Disease,Mutation,Chemical,Species} [{Genes,Diseases,Mutations,Chemicals,Species} ...], --categories {Gene,Disease,Mutation,Chemical,Species} [{Gene,Disease,Mutation,Chemical,Species} ...]
#      Pubtator categories that should be considered.  [default "('Gene', 'Disease', 'Mutation','Chemical')"]

if ( '--install_packages' %in% commandArgs()) {
  print('Installing packages')
  if (!require('argparse')) install.packages('argparse',repo="http://cran.rstudio.com/");
  if (!require('stringr')) install.packages('stringr',repo="http://cran.rstudio.com/");
  if (!require('RCurl')) install.packages('RCurl',repo="http://cran.rstudio.com/");
  if (!require('stringi')) install.packages('stringi',repo="http://cran.rstudio.com/");
}

suppressPackageStartupMessages(library("argparse"))
library('stringr')
library('stringi')
library('RCurl')

parser <- ArgumentParser()

parser$add_argument("-i", "--input", 
                    help = "input fie name. add path if file is not in workind directory")
parser$add_argument("-o", "--output", default="pmids_to_pubtator_matrix_output",
                    help = "output file name. [default \"%(default)s\"]")
parser$add_argument("-c", "--categories", choices=c("Gene", "Disease", "Mutation", "Chemical", "Species"), nargs="+", 
                    default= c("Gene", "Disease", "Mutation", "Chemical"),
                    help = "Pubtator categories that should be considered. [default \"%(default)s\"]")
parser$add_argument("-b", "--byid", action="store_true", default=FALSE,
                    help="If you want to find common gene IDs / mesh IDs instead of scientific terms.")
parser$add_argument("-n", "--number", default=NULL, type="integer",
                    help="Number of most frequent terms/IDs to extract. By default all terms/IDs are extracted.")
parser$add_argument("--install_packages", action="store_true", default=FALSE,
                    help="If you want to auto install missing required packages.")

args <- parser$parse_args()


data = read.delim(args$input, stringsAsFactors=FALSE, header = TRUE, sep='\t')

pmid_cols_index <- grep(c("PMID"), names(data))
word_matrix = data.frame()
dict.table = data.frame()
pmids_count <- 0
pubtator_max_ids = 100

get_pubtator_terms = function(pmids, categories){

      table = NULL
      for (pmid_split in split(pmids, ceiling(seq_along(pmids)/pubtator_max_ids))){
        out.data = NULL
        try_num <- 1
        t_0 <- Sys.time()
        
        while(TRUE) {
        
        # Timing check: kill at 3 min
        if (try_num > 1){
          cat("Connection problem. Please wait. Try number:",try_num,"\n") 
          Sys.sleep(time = 2*try_num)
        }
        try_num <- try_num + 1

        t_1 <- Sys.time()
        
        if(as.numeric(difftime(t_1, t_0, units = "mins")) > 3){
          message("Killing the request! Something is not working. Please, try again later","\n")
          return(table)
        }
        out.data <- tryCatch({    
          getURL(paste("https://www.ncbi.nlm.nih.gov/research/pubtator-api/publications/export/pubtator?pmids=", 
                       paste(pmid_split, collapse=","), sep = ""))
        }, error = function(e) {
          print(e)
          next
        }, finally = {
            Sys.sleep(0)
        })

      if(!is.null(out.data)){
        out.data = unlist(strsplit(out.data, "\n", fixed = T))
        
        # skip first few lines, is this needed?
        for (i in 3:length(out.data)) {
          temps = unlist(strsplit(out.data[i], "\t", fixed = T))
          if (length(temps) == 5) {
            # make 5 be 6
            temps = c(temps, NA)
          }
          if (length(temps) == 6) {
            # keep only 6
            table = rbind(table, temps)
          }
        }
        break
      }
      
     } #end while loop
    }
      
    index.categories = c()
    categories = as.character(unlist(categories))
    
    if(ncol(table) == 6){
      
          for(i in categories){
            tmp.index = grep(TRUE, i == as.character(table[,5]))
            
            if(length(tmp.index) > 0){
              index.categories = c(index.categories,tmp.index)
            } 
          }
        
        table = as.data.frame(table, stringsAsFactors=FALSE)
        table = table[index.categories,c(4,6)]
        table = table[!is.na(table[,2]),]
        table = table[!(table[,2] == "NA"),]
        table = table[!(table[,1] == "NA"),]
        
        if(args$byid){
          if(!is.null(args$number)){
            #retrieve top X mesh.ids
            table.mesh = as.data.frame(table(table[,2]))
            colnames(table.mesh)[1] = "mesh.id"
            table = table[order(table.mesh$Freq, decreasing = TRUE),]
            table = table[1:min(args$number, nrow(table.mesh)),]
            table.mesh$mesh.id = as.character(table.mesh$mesh.id)
            #subset table for top X mesh.ids
            table = table[which(as.character(table$V6) %in% as.character(table.mesh$mesh.id)),]
            table = table[!duplicated(table[,2]),]
          }else{
           table = table[!duplicated(table[,2]),]
          }
        } else {
          if(!is.null(args$number)){
            table[,1] = tolower(as.character(table[,1]))
            table = as.data.frame(table(table[,1]))
            colnames(table)[1] = "term"
            table = table[order(table$Freq, decreasing = TRUE),]
            table = table[1:min(args$number, nrow(table)),]
            table$term = as.character(table$term)
            
          }else{
            table[,1] = tolower(as.character(table[,1]))
            table = table[!duplicated(table[,1]),]
          }
        }
          
      return(table)
       
      } else {
      return(NULL)
      }
    }


#for all PMIDs of a row get PubTator terms and add them to the matrix
for (i in 1:nrow(data)){
  
  pmids = as.character(data[i,pmid_cols_index])
  pmids = pmids[!pmids == "NA"]
  

     if ( (pmids_count > 10000)){
        cat("Break (10s) to avoid killing of requests. Please wait.",'\n')
        Sys.sleep(10)
        pmids_count = 0
     }
  
  pmids_count = pmids_count + length(pmids)

    #get puptator terms with get_pubtator_terms function
    if (length(pmids) >0){
      table = get_pubtator_terms(pmids, args$categories)
      
      if(!is.null(table)){
        
        colnames(table)= c("term","mesh.id")
        
        # add data in binary matrix
        if (args$byid){
          mesh.ids = as.character(table$mesh.id)
          if (length(mesh.ids) > 0 ){
            word_matrix[i,mesh.ids] <- 1 
            cat(length(mesh.ids), " IDs for PMIDs of row", i," were added",'\n')
            # add data in dictionary
            dict.table = rbind(dict.table, table)
            dict.table = dict.table[!duplicated(as.character(dict.table[,2])),]
          }
        } else {
          terms = as.character(table[,1])
          if (length(terms) > 0 ){
            word_matrix[i,terms] <- 1 
            cat(length(terms), " terms for PMIDs of row", i," were added.",'\n')
          }
         }
        }
      
    } else {
      cat("No terms for PMIDs of row", i," were found.",'\n')
   }
  }

  if (args$byid){
  #change column names of matrix: exchange mesh ids/ids with term
  index_names = match(names(word_matrix), as.character(dict.table[[2]]))
  names(word_matrix) = dict.table[index_names,1]
  }

colnames(word_matrix) = gsub("[^[:print:]]","",colnames(word_matrix))
colnames(word_matrix) = gsub('\"', "", colnames(word_matrix), fixed = TRUE)

#merge duplicated columns
word_matrix = as.data.frame(do.call(cbind, by(t(word_matrix),INDICES=names(word_matrix),FUN=colSums)))

#save binary matrix
word_matrix <- as.matrix(word_matrix)
word_matrix[is.na(word_matrix)] <- 0
cat("Matrix with ",nrow(word_matrix)," rows and ",ncol(word_matrix)," columns generated.","\n")
#write.table(word_matrix, args$output)
write.table(word_matrix, args$output, row.names = FALSE, sep = '\t')