An Mspire library for calculating or dealing with error rates. These may be from target-decoy searches, sample bias validation, or other sources.
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 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
gem install ms-error_rate
See LICENSE