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= {ms-error_rate}[http://mspire.rubyforge.org/projects/ms-error_rate] An {Mspire}[http://mspire.rubyforge.org] library for calculating or dealing with error rates. These may be from target-decoy searches, sample bias validation, or other sources. == Examples === Target-Decoy with Mascot Generate q-values (right now only with Mascot and MascotPercolator): require 'ms/error_rate/qvalue' target_hits = Ms::ErrorRate::Qvalue::Mascot.qvalues(target_files, decoy_files) # target_hit is a PeptideHit Struct (:filename, :query_title, :charge, :sequence, :mowse, :qvalue) # or on the commandline: % qvalues.rb <target>.dat <decoy>.dat The same output can be produced from Mascot-Percolator output: require 'ms/error_rate/qvalue' target_hits = Ms::ErrorRate::Qvalue::Mascot::Percolator.qvalues(datp_files, tab_dot_text_files) # or commandline: % qvalues.rb <target>.datp <target>.tab.txt === Sample Bias Validation Sample Bias Validation allows error rate determination based on expected biases in sample composition. Here is an example using transmembrane sequence content. We will assume a fasta file called `proteins.fasta`: # create a peptide-centric database fasta_to_peptide_centric_db.rb proteins.fasta # defaults 2 missed cleavages, min aaseq 4 # generates a file: proteins.msd_clvg2.min_aaseq4.yml # create a transmembrane sequence prediction file fasta_to_phobius.rb proteins.fasta # => generates proteins.phobius generate_sbv_input_hashes.rb proteins.msd_clvg2.min_aaseq4.yml --tm proteins.phobius,1 # creates two files: # proteins.msd_clvg2.min_aaseq4.tm_min1.by_aaseq.yml # proteins.msd_clvg2.min_aaseq4.tm_min1.freq_by_length.yml # cytosolic fraction (transmembrane sequences not expected): error_rate qvalues.yml --fp-sbv proteins.msd_clvg2.min_aaseq4.tm_min1.by_aaseq.yml,\ proteins.msd_clvg2.min_aaseq4.tm_min1.freq_by_length.yml,0.05 == Installation gem install ms-error_rate == Copyright See LICENSE
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