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filter_sites_with_BMGE.rb
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filter_sites_with_BMGE.rb
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# m_matschiner Tue May 15 13:35:40 CEST 2018
module Enumerable
def sum
self.inject(0){|accum, i| accum + i }
end
def mean
if self.length == 0
nil
else
self.sum/self.length.to_f
end
end
def sample_variance
if self.length == 0
nil
else
m = self.mean
sum = self.inject(0){|accum, i| accum +(i-m)**2 }
sum/(self.length - 1).to_f
end
end
def standard_deviation
if self.length == 0
nil
else
return Math.sqrt(self.sample_variance)
end
end
def median
if self.length == 0
nil
else
sorted_array = self.sort
if self.size.modulo(2) == 1
sorted_array[self.size/2]
else
(sorted_array[(self.size/2)-1]+sorted_array[self.size/2])/2.0
end
end
end
def rough_percentile(p)
if self.length == 0
nil
else
raise "p should be between 0 and 1!" if p < 0.0 or p > 1.0
sorted_array = self.sort
index = (sorted_array.size*p).floor
if index > sorted_array.size-1
index = sorted_array.size-1
elsif index < 0
index = 0
end
sorted_array[index]
end
end
def lower_quartile(method = 1)
# The first and second quartile computing methods on http://en.wikipedia.org/wiki/Quartile are implemented.
sorted_array = self.sort
lower_half = []
if method == 1
sorted_array.each {|i| lower_half << i if i < self.median}
elsif method == 2
sorted_array.each {|i| lower_half << i if i <= self.median}
else
raise "Unknown quartile method!"
end
lower_half.median
end
def upper_quartile(method = 1)
# The first and second quartile computing methods on http://en.wikipedia.org/wiki/Quartile are implemented.
sorted_array = self.sort
upper_half = []
if method == 1
sorted_array.each {|i| upper_half << i if i > self.median}
elsif method == 2
sorted_array.each {|i| upper_half << i if i >= self.median}
else
raise "Unknown quartile method!"
end
upper_half.median
end
def inter_quartile_range(method = 1)
# The first and second quartile computing methods on http://en.wikipedia.org/wiki/Quartile are implemented.
if method == 1
self.upper_quartile(method = 1) - self.lower_quartile(method = 1)
elsif method == 2
self.upper_quartile(method = 2) - self.lower_quartile(method = 2)
else
raise "Unknown quartile method!"
end
end
def lower_whisker(method = 1)
# The first and second quartile computing methods on http://en.wikipedia.org/wiki/Quartile are implemented.
sorted_array = self.sort
lw = 0
if method == 1
(sorted_array.size-1).downto(0) {|x| lw = sorted_array[x] if sorted_array[x] >= self.lower_quartile(method = 1) - 1.5*self.inter_quartile_range(method = 1)}
elsif method == 2
(sorted_array.size-1).downto(0) {|x| lw = sorted_array[x] if sorted_array[x] >= self.lower_quartile(method = 2) - 1.5*self.inter_quartile_range(method = 2)}
else
raise "Unknown quartile method!"
end
return lw
end
def upper_whisker(method = 1)
# The first and second quartile computing methods on http://en.wikipedia.org/wiki/Quartile are implemented.
sorted_array = self.sort
uw = 0
if method == 1
0.upto(sorted_array.size-1) {|x| uw = sorted_array[x] if sorted_array[x] <= self.upper_quartile(method = 1) + 1.5*self.inter_quartile_range(method = 1)}
elsif method == 2
0.upto(sorted_array.size-1) {|x| uw = sorted_array[x] if sorted_array[x] <= self.upper_quartile(method = 2) + 1.5*self.inter_quartile_range(method = 2)}
else
raise "Unknown quartile method!"
end
return uw
end
def hpd_lower(proportion)
raise "The interval should be between 0 and 1!" if proportion >= 1 or proportion <= 0
sorted_array = self.sort
hpd_index = 0
min_range = sorted_array[-1]
diff = (proportion*self.size).round
(self.size-diff).times do |i|
min_value = sorted_array[i]
max_value = sorted_array[i+diff-1]
range = max_value - min_value
if range < min_range
min_range = range
hpd_index = i
end
end
sorted_array[hpd_index]
end
def hpd_upper(proportion)
raise "The interval should be between 0 and 1!" if proportion >= 1 or proportion <= 0
sorted_array = self.sort
hpd_index = 0
min_range = sorted_array[-1]
diff = (proportion*self.size).round
(self.size-diff).times do |i|
min_value = sorted_array[i]
max_value = sorted_array[i+diff-1]
range = max_value - min_value
if range < min_range
min_range = range
hpd_index = i
end
end
sorted_array[hpd_index+diff-1]
end
end
# Get the command line arguments.
alignment_directory_in = ARGV[0].chomp("/")
alignment_directory_out = ARGV[1].chomp("/")
bmge_path = ARGV[2]
gap_rate_cut_off = ARGV[3].to_f
entropy_like_score = ARGV[4].to_f
# Create the output directory if it does not exist yet.
unless Dir.exists?(alignment_directory_out)
Dir.mkdir(alignment_directory_out)
end
# Collect names of nucleotide fasta files in the input directory.
dir_entries_in = Dir.entries(alignment_directory_in).sort
filenames_in = []
dir_entries_in.each do |e|
if e.match(/.*_nucl.fasta/)
filenames_in << e
end
end
# Do for each fasta file in the input directory.
n_discarded_sites_overall = 0
filenames_in.each do |f|
# Feedback.
print "Analysing file #{f}..."
# Read the fasta file.
fasta_file = File.open("#{alignment_directory_in}/#{f}")
fasta_lines = fasta_file.readlines
fasta_ids = []
fasta_seqs = []
fasta_lines.each do |l|
if l[0] == ">"
fasta_ids << l[1..-1].strip.gsub(/\[.+\]/,"")
fasta_seqs << ""
else
fasta_seqs.last << l.strip
end
end
# Make sure that all sequences are the same length.
fasta_seqs.each do |s|
if s.size != fasta_seqs[0].size
puts "ERROR: Sequences have different lengths!"
exit 1
end
end
# Make sure that the file actually contains non-zero length sequences.
discarded_sites = []
if fasta_seqs[0].size > 0
# Run BMGE.
system("java -jar #{bmge_path} -i #{alignment_directory_in}/#{f} -t DNA -g 0.99 -oh tmp.html > /dev/null")
# Read the BMGE HTML file, and then delete it.
html_file = File.open("tmp.html")
html_lines = html_file.readlines
File.delete("tmp.html")
# Parse the HTML file.
smoothed_entropies = []
gap_rates = []
in_table = false
html_lines.each do |l|
if l.match(/ch\.\s+entropy\s+smooth\. entr.\s+gap rate/)
in_table = true
elsif l.match(/<\/span>/)
in_table = false
elsif in_table
smoothed_entropies << l.split[2].to_f
gap_rates << l.split[3].to_f
end
end
# Make sure that entropy scores and gap rates are found for each site.
if fasta_seqs[0].size != smoothed_entropies.size or fasta_seqs[0].size != gap_rates.size
raise "Alignment scores were not found for all positions!"
end
# Determine the sites to be discarded.
(fasta_seqs[0].size/3).times do |codon_pos|
keep_codon = true
if smoothed_entropies[3*codon_pos] > entropy_like_score or gap_rates[3*codon_pos] > gap_rate_cut_off
keep_codon = false
elsif smoothed_entropies[3*codon_pos+1] > entropy_like_score or gap_rates[3*codon_pos+1] > gap_rate_cut_off
keep_codon = false
elsif smoothed_entropies[3*codon_pos+2] > entropy_like_score or gap_rates[3*codon_pos+2] > gap_rate_cut_off
keep_codon = false
end
if keep_codon == false
discarded_sites << 3*codon_pos
discarded_sites << 3*codon_pos+1
discarded_sites << 3*codon_pos+2
end
end
end
# Prepare the string for a new fasta file.
new_fasta_string = ""
fasta_ids.size.times do |x|
new_fasta_string << ">#{fasta_ids[x]}\n"
fasta_seqs[x].size.times do |pos|
unless discarded_sites.include?(pos)
new_fasta_string << fasta_seqs[x][pos]
end
end
new_fasta_string << "\n"
end
# Write the corrected fasta file.
new_fasta_file = File.open("#{alignment_directory_out}/#{f}","w")
new_fasta_file.write(new_fasta_string)
# Feedback.
if discarded_sites.size > 0
puts " done. Removed #{discarded_sites.size} sites."
n_discarded_sites_overall += discarded_sites.size
else
puts " done."
end
end
# Feedback.
puts "Removed #{n_discarded_sites_overall} sites overall."