Module: RankProduct
- Defined in:
- lib/MARQ/rankproduct.rb
Class Method Summary collapse
- .permutations(num_signatures, num = 1000) ⇒ Object
- .permutations_full(signature_sizes) ⇒ Object
- .rankproduct(signatures, options = {}) ⇒ Object
- .ranks(dataset, experiment, from_FC = false, invert = false) ⇒ Object
- .score(gene_ranks, signature_sizes) ⇒ Object
Class Method Details
.permutations(num_signatures, num = 1000) ⇒ Object
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# File 'lib/MARQ/rankproduct.rb', line 40 def self.permutations(num_signatures, num = 1000) scores = [] num.times{ value = 0 num_signatures.times{|size_and_log| value += Math::log(rand) } scores << value } scores end |
.permutations_full(signature_sizes) ⇒ Object
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# File 'lib/MARQ/rankproduct.rb', line 52 def self.permutations_full(signature_sizes) gene_ranks = {} signature_sizes.each{|size| (1..size).to_a.shuffle.each_with_index{|gene, pos| gene_ranks[gene] ||= [] gene_ranks[gene] << pos + 1 } } gene_ranks.delete_if{|code, positions| positions.length != signature_sizes.length} scores = score(gene_ranks, signature_sizes) scores.values end |
.rankproduct(signatures, options = {}) ⇒ Object
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# File 'lib/MARQ/rankproduct.rb', line 66 def self.rankproduct(signatures, = {}) invert, from_FC, cross_platform = { :invert => [], :from_FC => false, :cross_platform => false, }.merge().values_at(:invert, :from_FC, :cross_platform) # Gather gene ranks from signatures ranks = {} signatures.each{|signature| dataset, experiment = signature.match(/^([^\:]*): (.*)/).values_at(1,2) dataset = dataset + '_cross_platform' if cross_platform ranks[signature] = self.ranks(dataset, experiment, from_FC, invert.include?(signature)) } # Invert the hash, from signature keys to gene keys gene_ranks = {} sizes = [] ranks.each{|signature, orders| sizes << orders.length orders.each{|code, position| next if position.nil? gene_ranks[code] ||= [] gene_ranks[code] << position } } # Remove incomplete genes gene_ranks.delete_if{|code, positions| positions.length != signatures.uniq.length} # Compute scores scores = score(gene_ranks, sizes) # Compute permutations num_permutations = 50000 permutation_scores = permutations(sizes.length, num_permutations) permutation_scores = permutation_scores.sort # Compute p-values from permutations results = {} scores.each {|gene, score| pos = permutation_scores.count_smaller(score) results[gene] = [score, pos.to_f / num_permutations] } # Complete the information with pfp num_genes = results.length results.sort {|a,b| a[1][0] <=> b[1][0] }.each_with_index{|p,i| info = p[1] pvalue = info[1] pfp = pvalue * num_genes / (i + 1) info << pfp } results end |
.ranks(dataset, experiment, from_FC = false, invert = false) ⇒ Object
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# File 'lib/MARQ/rankproduct.rb', line 4 def self.ranks(dataset, experiment , from_FC = false, invert = false) codes = MARQ::Dataset.codes(dataset) if from_FC ratios = MARQ::Dataset.logratios(dataset)[experiment.strip] sorted_genes = codes.zip(ratios). reject {|p| p[1].nil? }. sort_by {|p| p[1] }. collect {|p| p[0] } sorted_genes.reverse! unless invert ranks = Hash[*sorted_genes.zip((1..sorted_genes.length).to_a).flatten] (codes - sorted_genes).each {|gene| ranks[gene] = nil} else orders = MARQ::Dataset.orders(dataset)[experiment.strip] if invert num_genes = codes.length + 1 orders.collect! {|pos| pos.nil? ? nil : num_genes - pos } end ranks = Hash[*codes.zip(orders).flatten] end ranks end |
.score(gene_ranks, signature_sizes) ⇒ Object
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# File 'lib/MARQ/rankproduct.rb', line 29 def self.score(gene_ranks, signature_sizes) scores = {} log_sizes = signature_sizes.collect{|size| Math::log(size)} gene_ranks.each{|gene, positions| scores[gene] = positions.zip(log_sizes). collect{|p| Math::log(p[0]) - p[1]}. # Take log and substract from size (normalize) inject(0){|acc, v| acc += v } } scores end |