diff pmids_to_pubtator_matrix.R @ 0:02e46a96e98a draft default tip

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tools/simtext commit 63a5e13cf89cdd209d20749c582ec5b8dde4e208"

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pmids_to_pubtator_matrix.R	Wed Mar 24 08:34:22 2021 +0000
@@ -0,0 +1,231 @@
+#!/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("RCurl")
+library("stringi")
+
+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
+
+
+merge_pubtator_table <- function(out_data, table) {
+  out_data <- unlist(strsplit(out_data, "\n", fixed = T))
+  for (i in 3:length(out_data)) {
+    temps <- unlist(strsplit(out_data[i], "\t", fixed = T))
+    if (length(temps) == 5) {
+      temps <- c(temps, NA)
+    }
+    if (length(temps) == 6) {
+      table <- rbind(table, temps)
+    }
+  }
+  return(table)
+}
+
+
+get_pubtator_terms <- function(pmids) {
+  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)) {
+        table <- merge_pubtator_table(out_data, table)
+        break
+      }
+    }
+  }
+  return(table)
+}
+
+extract_category_terms <- function(table, categories) {
+  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"), ]
+  }else{
+    return(NULL)
+  }
+}
+
+extract_frequent_ids_or_terms <- function(table) {
+  if (is.null(table)) {
+    return(NULL)
+    break
+  }
+  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$term)
+    } else {
+      table[, 1] <- tolower(as.character(table[, 1]))
+      table <- table[!duplicated(table[, 1]), ]
+    }
+  }
+  return(table)
+}
+
+
+#for all PMIDs of a row get PubTator terms and add them to the matrix
+for (i in seq(nrow(data))) {
+  pmids <- as.character(data[i, pmid_cols_index])
+  pmids <- pmids[!pmids == "NA"]
+  if (pmids_count > 10000) {
+    cat("Break (10s) to avoid killing of requests. Please wait.", "\n")
+    Sys.sleep(10)
+    pmids_count <- 0
+  }
+  pmids_count <- pmids_count + length(pmids)
+  #get puptator terms and process them with functions
+  if (length(pmids) > 0) {
+    table <- get_pubtator_terms(pmids)
+    table <- extract_category_terms(table, args$categories)
+    table <- extract_frequent_ids_or_terms(table)
+    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, row.names = FALSE, sep = "\t", quote = FALSE)