PubMedTrend.r

library("RCurl")
library("XML")
library("plyr")
library("ggplot2")
library("directlabels")
 
 
########################
# Download PubMed Data #
########################
 
PubMedTrend <- function(query, yrStart=1950, yrMax=2009) {
  
  ### Some error checking ###
  if (is.numeric(yrStart) == FALSE || is.numeric(yrMax) == FALSE) stop("One of the year values is not numeric")
  if (yrStart < 1800) stop(paste("Sure you want to look for hits from the 18th century (yrStart = " ,yrStart, ")?\n", sep=""))
  this.year <- Sys.time()
  this.year <- as.integer(format(this.year, "%Y"))
  if (yrMax > this.year) stop(paste("Are you from the future? Please check your year interval; yrMax =",yrMax,"\n"))
  if (yrMax < yrStart) stop("yrMax is smaller than yrMin!")
  
  ### Start main search function ###
  getCount <- function(query.term) {
    # convert spaces to '+'
    query.gsub <- gsub(" ", "+", query.term)
    # convert some characters to brower friendly text (better to be safe than sorry)
    query.gsub <- gsub('"', "%22", query.gsub)
    query.gsub <- gsub("\\[", "%5B", query.gsub)
    query.gsub <- gsub("\\]", "%5D", query.gsub)
    # add progressbar
    pb <- txtProgressBar(min = yrStart, max = yrMax, style = 3)
    # create empty data frame
    df <- data.frame(NULL)
    cat("Searching for: ", query.term,"\n")
    
    # Start retrieval loop
    for(i in yrStart:yrMax) {
      # tell progressbar how it's going
      setTxtProgressBar(pb, i)
      # add publication date [dp] to query
      query.parsed <- paste(query.gsub, "+AND+",i, "%5Bppdat%5D", sep="")
      # Get XML with number of hits for query.parsed
      pub.esearch <- getURL(paste("http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&rettype=count&term=", 
                                  query.parsed, sep = ""))
      # Parse XML
      pub.esearch <- xmlTreeParse(pub.esearch, asText = TRUE)
      # Get number of hits from XML
      pub.count <- as.numeric(xmlValue(pub.esearch[["doc"]][["eSearchResult"]][["Count"]]))
      # Don't add anything if count is 0
      if (pub.count != 0) df <- rbind(df, data.frame("year" = i, "count" = pub.count))
      # Wait 0.5 sec
      Sys.sleep(0.5)
    }
    # close progressbar
    close(pb)
    return(df)
  } 
  # Run getCount() for all query terms
  df <- ldply(query, getCount)
  
  ### Calculate relative frequencies ###
  # load file with pubmed total citations from 1947-2009
  load(file="total_table")
  # match year
  match <- match(df$year, total.table$year)
  # add total count
  df$total_count <- total.table$total_count[match]
  # compute relative count times 10 000, i.e. show number of matches per 1 million PubMed citations
  df$relative <- (df$count / df$total_count) * 10000
  cat("\nAll done!")
  return(df)
}
 
#######################
### Show total hits ###
#######################
PubTotalHits <- function(args=FALSE) {
  # Get column total for query 'x'
  GetCount <- function(x) {
    df <- data.frame("search_name" = x, "total_hits" = colSums(df[df$.id == x,][3]))
  }
  # Index all query names
  query.index <- unique(df$.id)
  # Use GetCount() for every term in 'query.index' and return as data.frame
  df <- ldply(query.index, GetCount)
  # if argument is 'query' add full query instead of query name. 
  # if there is no argument specified both name and query will be shown
  if (args == "query" || args == FALSE) {
    # remove names
    names(query) <- NULL
    # add queries to df
    df <- cbind(df, "query" = query)
    # reorder columns
    df <- df[,c(1,3,2)]
    # remove 'names' if we only want queries
    if (args == "query") df <- df[-1]
  }
  return(df)
}