Method: Transrate::Assembly#assembly

Defined in:
lib/transrate/assembly.rb,
lib/transrate/assembly.rb

#assembly ⇒ Array<Bio::FastaFormat> (readonly)

Returns the assembly.

Returns:

  • (Array<Bio::FastaFormat>) —

    the assembly



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# File 'lib/transrate/assembly.rb', line 27

class Assembly

  include Enumerable
  extend Forwardable
  def_delegators :@assembly, :each, :each_value, :<<, :size, :length, :[]

  attr_accessor :file
  attr_reader :assembly
  attr_reader :has_run
  attr_accessor :n_bases
  attr_reader :n50
  attr_accessor :contig_metrics

  # Create a new Assembly.
  #
  # @param file [String] path to the assembly FASTA file
  def initialize file
    @file = File.expand_path file
    unless File.exist? @file
      raise TransrateIOError.new "Assembly file doesn't exist: #{@file}"
    end
    @assembly = {}
    @n_bases = 0
    Bio::FastaFormat.open(file).each do |entry|
      if entry.seq.length == 0
        logger.error "Entry found with no sequence #{entry.entry_id}"
        raise AssemblyError
      end
      @n_bases += entry.length
      contig = Contig.new(entry)
      if @assembly.key?(contig.name)
        logger.error "Non unique fasta identifier found"
        logger.error ">#{contig.name}"
        logger.error "Please make sure there are no duplicate entries in the assembly"
        logger.error "Contig name is taken from before the first | or space"
        logger.error "If you used Trinity, there is a known bug that breaks" +
                     "contig names to make them non-unique."
        logger.error "You can fix your Trinity assembly by replacing | with _"
        logger.error "e.g. `sed 's/\\|/_/' Trinity.fa > Trinity.fixed.fa`"
        raise AssemblyError
      end
      @assembly[contig.name] = contig
    end
    @contig_metrics = ContigMetrics.new self
  end

  # Generate and store the basic statistics for this assembly
  #
  # @param threads [Integer] number of threads to use
  def run threads=8
    stats = self.basic_stats threads
    stats.each_pair do |key, value|
      ivar = "@#{key.gsub(/\ /, '_')}".to_sym
      attr_ivar = "#{key.gsub(/\ /, '_')}".to_sym
      # creates accessors for the variables in stats
      singleton_class.class_eval { attr_accessor attr_ivar }
      self.instance_variable_set(ivar, value)
    end
    @contig_metrics.run
    @has_run = true
  end

  # Return a hash of statistics about this assembly. Stats are
  # calculated in parallel by splitting the assembly into
  # equal-sized bins and calling Assembly#basic_bin_stat on each
  # bin in a separate thread.
  #
  # @param threads [Integer] number of threads to use
  #
  # @return [Hash] basic statistics about the assembly
  def basic_stats threads=1
    return @basic_stats if @basic_stats
    bin = @assembly.values
    @basic_stats = basic_bin_stats bin
    @basic_stats
  end # basic_stats


  # Calculate basic statistics in an single thread for a bin
  # of contigs.
  #
  # Basic statistics are:
  #
  # - N10, N30, N50, N70, N90
  # - number of contigs >= 1,000 base pairs long
  # - number of contigs >= 10,000 base pairs long
  # - length of the shortest contig
  # - length of the longest contig
  # - number of contigs in the bin
  # - mean contig length
  # - total number of nucleotides in the bin
  # - mean % of contig length covered by the longest ORF
  #
  # @param [Array] bin An array of Bio::Sequence objects
  # representing contigs in the assembly

  def basic_bin_stats bin

    # cumulative length is a float so we can divide it
    # accurately later to get the mean length
    cumulative_length = 0.0

    # we'll calculate Nx for x in [10, 30, 50, 70, 90]
    # to do this we create a stack of the x values and
    # pop the first one to set the first cutoff. when
    # the cutoff is reached we store the nucleotide length and pop
    # the next value to set the next cutoff. we take a copy
    # of the Array so we can use the intact original to collect
    # the results later
    x = [90, 70, 50, 30, 10]
    x2 = x.clone
    cutoff = x2.pop / 100.0
    res = []
    n_under_200, n_over_1k, n_over_10k, n_with_orf, orf_length_sum = 0,0,0,0,0
    # sort the contigs in ascending length order
    # and iterate over them
    bin.sort_by! { |c| c.seq.length }
    bin.each do |contig|
      # increment our long contig counters if this
      # contig is above the thresholds
      if contig.length < 200
        # ignore contigs less than 200 bases,
        # but record how many there are
        n_under_200 += 1
        next
      end
      n_over_1k += 1 if contig.length > 1_000
      n_over_10k += 1 if contig.length > 10_000

      # add the length of the longest orf to the
      # running total
      orf_length = contig.orf_length
      orf_length_sum += orf_length
      # only consider orfs that are realistic length
      # (here we set minimum amino acid length as 50)
      n_with_orf += 1 if orf_length > 149

      # increment the cumulative length and check whether the Nx
      # cutoff has been reached. if it has, store the Nx value and
      # get the next cutoff
      cumulative_length += contig.length
      if cumulative_length >= @n_bases * cutoff
        res << contig.length
        if x2.empty?
          cutoff = 1
        else
          cutoff = x2.pop / 100.0
        end
      end
    end

    # if there aren't enough sequences we might have no value for some
    # of the Nx. Fill the empty ones in with the longest contig length.
    while res.length < x.length do
      res << bin.last.length
    end

    # calculate and return the statistics as a hash
    mean = cumulative_length / @assembly.size
    if @assembly.size * mean == 0
      mean_orf_percent = 0
    else
      mean_orf_percent = 300 * orf_length_sum / (@assembly.size * mean)
    end
    ns = Hash[x.map { |n| "n#{n}" }.zip(res)]
    {
      'n_seqs' => bin.size,
      'smallest' => bin.first.length,
      'largest' => bin.last.length,
      'n_bases' => n_bases,
      'mean_len' => mean,
      'n_under_200' => n_under_200,
      'n_over_1k' => n_over_1k,
      'n_over_10k' => n_over_10k,
      'n_with_orf' => n_with_orf,
      'mean_orf_percent' => mean_orf_percent
    }.merge ns

  end # basic_bin_stats

  def classify_contigs cutoff
    # create hash of file handles for each output
    base = File.basename @file
    files = {}
    %w(good bad).each do |type|
      files[type.to_sym] = File.open("#{type}.#{base}", "wb")
    end
    # loop through contigs writing them out to the appropriate file
    @assembly.each_pair do |name, contig|
      handle = files[contig.classify(cutoff)]
      handle.write contig.to_fasta
    end
    # close all the file handles
    files.each do |type, handle|
      handle.close
    end
  end

  def good_contigs
    good = 0
    @assembly.each do |name, contig|
      good += 1 if contig.classification == :good
    end
    good
  end

end