Class: Transrate::Assembly
- Inherits:
-
Object
- Object
- Transrate::Assembly
- Extended by:
- Forwardable
- Includes:
- Enumerable
- Defined in:
- lib/transrate/assembly.rb
Overview
Container for a transcriptome assembly and its associated metadata.
Instance Attribute Summary collapse
-
#assembly ⇒ Array<Bio::FastaFormat>
readonly
The assembly.
-
#contig_metrics ⇒ Object
Returns the value of attribute contig_metrics.
-
#file ⇒ String
Path to the assembly FASTA file.
-
#has_run ⇒ BOOL
readonly
Whether the basic metrics have been generated.
-
#n50 ⇒ Integer
readonly
Assembly n50.
-
#n_bases ⇒ Object
Returns the value of attribute n_bases.
-
#orss_ublast_db ⇒ String
Path to a ublast database generated from the orfs extracted from this assembly.
-
#ublast_db ⇒ String
Path to a ublast database generated from this assembly.
Instance Method Summary collapse
-
#basic_bin_stats(bin) ⇒ Object
Calculate basic statistics in an single thread for a bin of contigs.
-
#basic_stats(threads = 1) ⇒ Hash
Return a hash of statistics about this assembly.
-
#classify_contigs(cutoff) ⇒ Object
basic_bin_stats.
- #good_contigs ⇒ Object
-
#initialize(file) ⇒ Assembly
constructor
Create a new Assembly.
-
#run(threads = 8) ⇒ Object
Generate and store the basic statistics for this assembly.
Constructor Details
#initialize(file) ⇒ Assembly
Create a new Assembly.
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# File 'lib/transrate/assembly.rb', line 43 def initialize file @file = File. 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 |
Instance Attribute Details
#assembly ⇒ Array<Bio::FastaFormat> (readonly)
Returns 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. 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 |
#contig_metrics ⇒ Object
Returns the value of attribute contig_metrics.
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# File 'lib/transrate/assembly.rb', line 38 def contig_metrics @contig_metrics end |
#file ⇒ String
Returns path to the assembly FASTA file.
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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. 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 |
#has_run ⇒ BOOL (readonly)
Returns whether the basic metrics have been generated.
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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. 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 |
#n50 ⇒ Integer (readonly)
Returns assembly n50.
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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. 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 |
#n_bases ⇒ Object
Returns the value of attribute n_bases.
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# File 'lib/transrate/assembly.rb', line 36 def n_bases @n_bases end |
#orss_ublast_db ⇒ String
Returns path to a ublast database generated from the orfs extracted from this 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. 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 |
#ublast_db ⇒ String
Returns path to a ublast database generated from this 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. 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 |
Instance Method Details
#basic_bin_stats(bin) ⇒ Object
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
representing contigs in the assembly
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# File 'lib/transrate/assembly.rb', line 123 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_stats(threads = 1) ⇒ Hash
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.
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# File 'lib/transrate/assembly.rb', line 97 def basic_stats threads=1 return @basic_stats if @basic_stats bin = @assembly.values @basic_stats = basic_bin_stats bin @basic_stats end |
#classify_contigs(cutoff) ⇒ Object
basic_bin_stats
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# File 'lib/transrate/assembly.rb', line 207 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 |
#good_contigs ⇒ Object
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# File 'lib/transrate/assembly.rb', line 225 def good_contigs good = 0 @assembly.each do |name, contig| good += 1 if contig.classification == :good end good end |
#run(threads = 8) ⇒ Object
Generate and store the basic statistics for this assembly
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# File 'lib/transrate/assembly.rb', line 76 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 |