Column descriptions for Luciphor output

This site provides descriptions of the columns that are reported in the Luciphor output.

There are two types of output Luciphor can generate: default and "Full Monty". In the default output, only 1 entry is reported for each phospho-peptide permutation that was scored. So if you have a 17 PSMs supporting the phospho-peptide permutation ELVIS[167]STYK, the PSM with the best delta score for that permutation is reported. The default output also indicates how many PSMs were also assigned the same phospho-permutation.

In the "Full Monty" output differs in that all PSMs are reported, not just the representative ones. This can be useful if you are interested in seeing how a specific PSM was scored. Or if you simply want to see everything. Fields exclusive to the "Full Monty" column are in red.

Field Name Example Description
repSpecId
or
specId
ppeptidemix1_CID_Orbi.2154.2154.2 The TPP-formatted spectrum identifier for the reproted scoring PSM in the default output file. This is taken directly from the input pepXML file given to Luciphor. This PSM is the most confidently scored PSM for the phospho-permutation associated with it. In the "Full Monty" output this field is called specId.
peptideSeq YSRQLLEK/+3 The peptide sequence assigned to this PSM along with it's charge state. This sequence will contain no modificaiton information.
origTPP Y[243]S[167]RQLLEK The original phospho-permutation reported for this PSM in the TPP pepXML file.
predictedPep_1 Y[243]S[167]RQLLEK The top scoring Luciphor phospho-permutation for this PSM.
predictedPep_2 Y[243]SRQ[208]LLEK The second best scoring Luciphor phospho-permutation for this PSM
score 0.999 This is the score assigned to the PSM by the original search engine used to analyze the data. The field title actually varies based upon the parameters used in Luciphor ( -M & -P). Current possible values are 'tppScore', 'mascot', 'xtandem', and 'sequest'.
nss 17 Number of Supporting Spectra. This is the number of PSMs whose top-scoring Luciphor phospho-permutation was the same as the string reported in the predictedPep_1 field described above.
numRPS 2 Number of Reported Phosphorylation Sites. This is the number of S, T, or Y residues in the sequence that are reported to be phosphorylated in the peptide.
numPPS 2 Number of Potential Phosphorylation Sites. This is the number of S, T, or Y residues in the peptide sequence that can undergo phosphorylation
localFLR 0.01 Local False Localization Rate. This the local estimated false localization rate for the top-scoring phospho-permutation reported by Luciphor of the given PSM. This FLR is based upon the PSMs with similar delta scores. This value will be NA for any decoy-permutation PSMs
globalFLR 0.01 Global False Localization Rate. This the global estimated false localization rate for the top-scoring phospho-permutation reported by Luciphor of the given PSM. This FLR is based upon the scores of all the reproted PSMs in the data. This value will be NA for any decoy-matched PSMs
delta_score 54.321 The difference in the score between the top two phospho-permutations for the given PSM. This is the value upon which the FLR estimations are based. The larger this value is, the more confident you can be in the correctness of the phospho-permutation reported in the predictedPep_1 field.
Luciphor_score_(1 or 2) 123.00 The raw score assigned to the best (or second best) phospho-permutations for the given PSM.
isDecoy(1 or 2) 0 or 1 Binary classifier indicating if the assigned phospho-permutation for the given PSM is a decoy permutation (1) or not (0).
totalNumPeaks 123 Total number of peaks in the spectrum for this PSM that were considered for peak matching.
numMatchedPeaks(1 or 2) 20 Total number of peaks in the spectrum for this PSM that were matched in either phospho-permutation 1 or 2.
fractionIonsMatched1 0.1626 The number of matched peaks divided by the total number of peaks in the spectrum for the top phospho-permutation prediction.
scoreTime 0 The number of seconds it took for Luciphor to score this particular PSM. This is useful in figuring out which PSMs are taking the most time to score in a data set.