Class: GeneValidator::AlignmentValidation

Inherits:
ValidationTest show all
Extended by:
Forwardable
Defined in:
lib/genevalidator/validation_alignment.rb

Overview

This class contains the methods necessary for validations based on multiple alignment

Instance Attribute Summary collapse

Attributes inherited from ValidationTest

#cli_name, #description, #header, #hits, #prediction, #run_time, #short_header, #type, #validation_report

Instance Method Summary collapse

Constructor Details

#initialize(prediction, hits) ⇒ AlignmentValidation

Initilizes the object Params: prediction: a Sequence object representing the blast query hits: a vector of Sequence objects (representing blast hits) plot_path: name of the fasta file



106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
 
# File 'lib/genevalidator/validation_alignment.rb', line 106

def initialize(prediction, hits)
  super
  @short_header       = 'MissingExtraSequences'
  @cli_name           = 'align'
  @header             = 'Missing/Extra Sequences'
  @description        = 'Finds missing and extra sequences in the' \
                        ' prediction, based on the multiple alignment of' \
                        ' the best hits. Also counts the percentage of' \
                        ' the conserved regions that appear in the' \
                        ' prediction.'
  @raw_seq_file       = opt[:raw_sequences]
  @index_file_name    = config[:raw_seq_file_index]
  @raw_seq_file_load  = config[:raw_seq_file_load]
  @db                 = opt[:db]
  @multiple_alignment = []
  @num_threads        = opt[:mafft_threads]
  @type               = config[:type]
end

Instance Attribute Details

#index_file_name ⇒ Object (readonly)

Returns the value of attribute index_file_name.



97
98
99
 
# File 'lib/genevalidator/validation_alignment.rb', line 97

def index_file_name
  @index_file_name
end

#multiple_alignment ⇒ Object (readonly)

Returns the value of attribute multiple_alignment.



95
96
97
 
# File 'lib/genevalidator/validation_alignment.rb', line 95

def multiple_alignment
  @multiple_alignment
end

#raw_seq_file ⇒ Object (readonly)

Returns the value of attribute raw_seq_file.



96
97
98
 
# File 'lib/genevalidator/validation_alignment.rb', line 96

def raw_seq_file
  @raw_seq_file
end

#raw_seq_file_load ⇒ Object (readonly)

Returns the value of attribute raw_seq_file_load.



98
99
100
 
# File 'lib/genevalidator/validation_alignment.rb', line 98

def raw_seq_file_load
  @raw_seq_file_load
end

Instance Method Details

#array_to_ranges(ar) ⇒ Object

converts an array of integers into array of ranges



379
380
381
382
383
384
385
386
387
388
389
 
# File 'lib/genevalidator/validation_alignment.rb', line 379

def array_to_ranges(ar)
  prev = ar[0]

  ranges = ar.slice_before do |e|
    prev2 = prev
    prev = e
    prev2 + 1 != e
  end.map { |a| a[0]..a[-1] }

  ranges
end

#consensus_validation(prediction_raw, consensus) ⇒ Object

Returns the percentage of consesnsus residues from the ma that are in the prediction Params: prediction_raw: String corresponding to the prediction sequence consensus: String corresponding to the statistical model Output: Fixnum with the score



308
309
310
311
312
313
314
315
316
317
318
319
 
# File 'lib/genevalidator/validation_alignment.rb', line 308

def consensus_validation(prediction_raw, consensus)
  return 1 if prediction_raw.length != consensus.length
  # no of conserved residues among the hits
  no_conserved_residues = consensus.length - consensus.scan(/[\?-]/).length

  return 1 if no_conserved_residues.zero?

  # no of conserved residues from the hita that appear in the prediction
  no_conserved_pred = consensus.split(//).each_index.count { |j| consensus[j] != '-' && consensus[j] != '?' && consensus[j] == prediction_raw[j] }

  no_conserved_pred / (no_conserved_residues + 0.0)
end

#extra_sequence_validation(prediction_raw, sm) ⇒ Object

Returns the percentage of extra sequences in the prediction with respect to the statistical model Params: prediction: String corresponding to the prediction sequence sm: String corresponding to the statistical model Output: Fixnum with the score



289
290
291
292
293
294
295
296
297
298
 
# File 'lib/genevalidator/validation_alignment.rb', line 289

def extra_sequence_validation(prediction_raw, sm)
  return 1 if prediction_raw.length != sm.length
  # find residues that are in the prediction
  # but not in the statistical model
  no_insertions = 0
  (0..sm.length - 1).each do |i|
    no_insertions += 1 if prediction_raw[i] != '-' && sm[i] == '-'
  end
  no_insertions / (sm.length + 0.0)
end

#gap_validation(prediction_raw, sm) ⇒ Object

Returns the percentage of gaps in the prediction with respect to the statistical model Params: prediction: String corresponding to the prediction sequence sm: String corresponding to the statistical model Output: Fixnum with the score



270
271
272
273
274
275
276
277
278
279
 
# File 'lib/genevalidator/validation_alignment.rb', line 270

def gap_validation(prediction_raw, sm)
  return 1 if prediction_raw.length != sm.length
  # find gaps in the prediction and
  # not in the statistical model
  no_gaps = 0
  (0..sm.length - 1).each do |i|
    no_gaps += 1 if prediction_raw[i] == '-' && sm[i] != '-'
  end
  no_gaps / (sm.length + 0.0)
end

#get_consensus(ma) ⇒ Object

Returns the consensus regions among a set of multiple aligned sequences i.e positions where there is the same element in all sequences Params: ma: array of Strings, corresponding to the multiple aligned sequences Output: String with the consensus regions



257
258
259
260
 
# File 'lib/genevalidator/validation_alignment.rb', line 257

def get_consensus(ma)
  align = Bio::Alignment.new(ma)
  align.consensus
end

#get_sm_pssm(ma, threshold = 0.7) ⇒ Object

Builds a statistical model from a set of multiple aligned sequences based on PSSM (Position Specific Matrix) Params: ma: array of Strings, corresponding to the multiple aligned sequences threshold: percentage of genes that are considered in statistical model Output: String representing the statistical model Array with the maximum frequeny of the majoritary residue for each position



332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
 
# File 'lib/genevalidator/validation_alignment.rb', line 332

def get_sm_pssm(ma, threshold = 0.7)
  sm = ''
  freq = []
  (0..ma[0].length - 1).each do |i|
    freqs = Hash.new(0)
    ma.map { |seq| seq[i] }.each { |res| freqs[res] += 1 }
    # get the residue with the highest frequency
    max_freq = freqs.map { |_res, n| n }.max
    residue = freqs.map { |res, n| n == max_freq ? res : [] }.flatten[0]

    freq << residue == '-' ? 0 : (max_freq / ma.length.to_f)
    sm += (max_freq / ma.length.to_f) >= threshold ? residue : '?'
  end
  [sm, freq]
end

#isalpha(str) ⇒ Object

Returns true if the string contains only letters and false otherwise



373
374
375
 
# File 'lib/genevalidator/validation_alignment.rb', line 373

def isalpha(str)
  !str.match(/[^A-Za-z]/)
end

#multiple_align_mafft(prediction, hits) ⇒ Object

Builds the multiple alignment between all the hits and the prediction using MAFFT tool Also creates a fasta file with the alignment Params: prediction: a Sequence object representing the blast query hits: a vector of Sequience objects (usually representing blast hits) path: path of mafft installation Output: Array of Strings, corresponding to the multiple aligned sequences the prediction is the last sequence in the vector



226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
 
# File 'lib/genevalidator/validation_alignment.rb', line 226

def multiple_align_mafft(prediction, hits)
  raise unless prediction.is_a?(Query) && hits[0].is_a?(Query)

  opt = ['--maxiterate', '1000', '--localpair', '--anysymbol', '--quiet',
         '--thread', @num_threads.to_s]
  mafft = Bio::MAFFT.new('mafft', opt)
  sequences = hits.map do |h|
    # remove the seq id - as MAFFT sometimes has an issue with this
    f = Bio::FastaFormat.new(h.raw_sequence)
    # check if fasta sequence otherwise returne original entry
    f.seq.empty? ? h.raw_sequence : f.seq
  end
  sequences.push(prediction.protein_translation)

  report = mafft.query_align(sequences)
  alignment = report.alignment.map(&:to_s)
  raise NoMafftInstallationError if alignment.empty?
  alignment
rescue StandardError
  raise NoMafftInstallationError
end

#plot_alignment(freq, ma = @multiple_alignment) ⇒ Object

Generates a json file cotaining data used for plotting lines for multiple hits alignment, prediction and statistical model Params: freq: String residue frequency from the statistical model output: plot_path of the json file ma: String array with the multiple alignmened hits and prediction



397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
 
# File 'lib/genevalidator/validation_alignment.rb', line 397

def plot_alignment(freq, ma = @multiple_alignment)
  # get indeces of consensus in the multiple alignment
  consensus = get_consensus(ma[0..ma.length - 2])
  consensus_idxs = consensus.split(//).each_index.select { |j| isalpha(consensus[j]) }
  consensus_ranges = array_to_ranges(consensus_idxs)

  consensus_all = get_consensus(ma)
  consensus_all_idxs = consensus_all.split(//).each_index.select { |j| isalpha(consensus_all[j]) }
  consensus_all_ranges = array_to_ranges(consensus_all_idxs)

  match_alignment = ma[0..ma.length - 2].each_with_index.map { |seq, _j| seq.split(//).each_index.select { |j| isalpha(seq[j]) } }
  match_alignment_ranges = match_alignment.map { |e| array_to_ranges(e) }

  query_alignment = ma[ma.length - 1].split(//).each_index.select { |j| isalpha(ma[ma.length - 1][j]) }
  query_alignment_ranges = array_to_ranges(query_alignment)

  len = ma[0].length

  # plot statistical model
  data = freq.each_with_index.map { |h, j| { 'y' => ma.length, 'start' => j, 'stop' => j + 1, 'color' => 'orange', 'height' => h } } +
         # hits
         match_alignment_ranges.each_with_index.map { |ranges, j| ranges.map { |range| { 'y' => ma.length - j - 1, 'start' => range.first, 'stop' => range.last, 'color' => 'red', 'height' => -1 } } }.flatten +
         ma[0..ma.length - 2].each_with_index.map { |_seq, j| consensus_ranges.map { |range| { 'y' => j + 1, 'start' => range.first, 'stop' => range.last, 'color' => 'yellow', 'height' => -1 } } }.flatten +
         # plot prediction
         [{ 'y' => 0, 'start' => 0, 'stop' => len, 'color' => 'gray', 'height' => -1 }] +
         query_alignment_ranges.map { |range| { 'y' => 0, 'start' => range.first, 'stop' => range.last, 'color' => 'red', 'height' => -1 } }.flatten +

         # plot consensus
         consensus_all_ranges.map { |range| { 'y' => 0, 'start' => range.first, 'stop' => range.last, 'color' => 'yellow', 'height' => -1 } }.flatten

  y_axis_values = 'Prediction'
  (1..ma.length - 1).each { |i| y_axis_values << ", hit #{i}" }

  y_axis_values << ', Statistical Model'

  Plot.new(data,
           :align,
           'Missing/Extra sequences Validation: Multiple Align. &' \
           'Statistical model of hits',
           'Aligned Hit Sequence, red; Conserved Region, Yellow',
           'Offset in the Alignment',
           '',
           ma.length + 1,
           y_axis_values)
end

#remove_isolated_residues(seq, len = 2) ⇒ Object

Remove isolated residues inside long gaps from a given sequence Params: seq:String: sequence of residues len:Fixnum: number of isolated residues to be removed Output: String: the new sequence



356
357
358
359
360
361
362
363
364
365
366
367
368
 
# File 'lib/genevalidator/validation_alignment.rb', line 356

def remove_isolated_residues(seq, len = 2)
  gap_starts = seq.to_enum(:scan, /(-\w{1,#{len}}-)/i).map { |_m| $`.size + 1 }
  # remove isolated residues
  gap_starts.each do |i|
    (i..i + len - 1).each { |j| seq[j] = '-' if isalpha(seq[j]) }
  end
  # remove isolated gaps
  res_starts = seq.to_enum(:scan, /([?\w]-{1,2}[?\w])/i).map { |_m| $`.size + 1 }
  res_starts.each do |i|
    (i..i + len - 1).each { |j| seq[j] = '?' if seq[j] == '-' }
  end
  seq
end

#run ⇒ Object

Find gaps/extra regions based on the multiple alignment of the first n hits Output: AlignmentValidationOutput object



130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
 
# File 'lib/genevalidator/validation_alignment.rb', line 130

def run
  n = opt[:min_blast_hits] < 10 ? 10 : opt[:min_blast_hits]
  n = 50 if n > 50

  raise NotEnoughHitsError if hits.length < n
  raise unless prediction.is_a?(Query) && hits[0].is_a?(Query)

  start = Time.new
  # get the first n hits
  n_hits = [n - 1, @hits.length].min
  less_hits = @hits[0..n_hits]
  # get raw sequences for less_hits
  less_hits.delete_if do |hit|
    if hit.raw_sequence.nil?
      hit.raw_sequence = FetchRawSequences.run(hit.identifier,
                                               hit.accession_no)
    end
    hit.raw_sequence.nil? ? true : false
  end

  raise NoInternetError if less_hits.length.zero?
  # in case of nucleotide prediction sequence translate into protein
  # translate with the reading frame of all hits considered for alignment
  reading_frames = less_hits.map(&:reading_frame).uniq
  raise ReadingFrameError if reading_frames.length != 1

  if @type == :nucleotide
    s = Bio::Sequence::NA.new(prediction.raw_sequence)
    prediction.protein_translation = s.translate(reading_frames[0])
  end

  # multiple align sequences from less_hits with the prediction
  # the prediction is the last sequence in the vector
  @multiple_alignment = multiple_align_mafft(prediction, less_hits)

  out = get_sm_pssm(@multiple_alignment[0..@multiple_alignment.length - 2])
  sm = out[0]
  freq = out[1]

  # remove isolated residues from the predicted sequence
  index          = @multiple_alignment.length - 1
  prediction_raw = remove_isolated_residues(@multiple_alignment[index])
  # remove isolated residues from the statistical model
  sm = remove_isolated_residues(sm)

  a1 = get_consensus(@multiple_alignment[0..@multiple_alignment.length - 2])

  plot1     = plot_alignment(freq)
  gaps      = gap_validation(prediction_raw, sm)
  extra_seq = extra_sequence_validation(prediction_raw, sm)
  consensus = consensus_validation(prediction_raw, a1)

  @validation_report = AlignmentValidationOutput.new(@short_header, @header,
                                                     @description, gaps,
                                                     extra_seq, consensus)
  @validation_report.plot_files.push(plot1)
  @validation_report.run_time = Time.now - start
  @validation_report
rescue NotEnoughHitsError
  @validation_report = ValidationReport.new('Not enough evidence',
                                            :warning, @short_header,
                                            @header, @description)
rescue NoMafftInstallationError
  @validation_report = ValidationReport.new('Mafft error', :error,
                                            @short_header, @header,
                                            @description)
  @validation_report.errors.push NoMafftInstallationError
rescue NoInternetError
  @validation_report = ValidationReport.new('Internet error', :error,
                                            @short_header, @header,
                                            @description)
  @validation_report.errors.push NoInternetError
rescue ReadingFrameError
  @validation_report = ValidationReport.new('Multiple reading frames',
                                            :error, @short_header,
                                            @header, @description)
  @validation_report.errors.push 'Multiple reading frames Error'
rescue StandardError
  @validation_report = ValidationReport.new('Unexpected error', :error,
                                            @short_header, @header,
                                            @description)
  @validation_report.errors.push 'Unexpected Error'
end