# The output file
learn.file.novorOutput = nonspecific-hcd-ft.novor

# The base directory of the data files
learn.file.dataBaseDir = ./data/

# The data file used to learn
learn.file.trainingData = Hela_ACT_HCD.mgf, Hela_ALT_HCD.mgf, Hela_ArgC-GluC_HCD.mgf, Hela_AspN-GluC_HCD.mgf, Hela_GCT_HCD.mgf, Hela_GluC-Chytry_HCD.mgf, Hela_LysC-Chytry_HCD.mgf, Hela_AGL_HCD.mgf, Hela_ArgC-AspN_HCD.mgf, Hela_ArgC-LysC_HCD.mgf, Hela_AspN-LysC_HCD.mgf, Hela_GLC_HCD.mgf, Hela_GluC-LysC_HCD.mgf, Hela_LysC-Trypsin_HCD.mgf, Hela_ALC_HCD.mgf, Hela_ArgC-Chytry_HCD.mgf, Hela_AspN-Chytry_HCD.mgf, Hela_AspN-Trypsin_HCD.mgf, Hela_GLT_HCD.mgf, Hela_LCT_HCD.mgf

# The peptide file for each spectrum
learn.file.peptideDir = ./dbsearch/
learn.file.peptideType = peaksdb

# Number of concurrent threads for learning
learn.nThreads = 40

# Decision tree learning parameters
learn.minLeafWeight = 500
learn.minEntropyReduction = 10

#used for comparing the target sequence with the de novo sequence
# for high res.
learn.error.prefix = 0.1Da
learn.error.aa = 0.05Da

# for low res.
#learn.error.prefix = 0.5Da
#learn.error.aa = 0.1Da

# Algorithm parameters.
alg.algResolution = 200
alg.maxAnchorPeaks = 250
alg.maxShortTagMass = 500
alg.backtraceQueueSize = 100
alg.massAnalyzer = FT
alg.enzyme = Nonspecific

# User controlled parameters
user.error.product = 0.1Da
user.error.precursor = 20ppm

# Variable modifications will make algorithm to consider both modified and the original residue
user.modification.var = Carbamidomethyl (C), Oxidation (M)

# Fixed modifications will turn off the unmodified residue from consideration
#user.modification.fix = Carbamidomethyl (C),

# Do not use the following simple residues
user.residue.forbidden = I, U
