-
|
I'm having this issue running labelquant. See error message below: I'm running two plexes from the CPTAC LUAD cohort, 2 fractions for each plex. This is just a test run. The same issue appears when I run the steps separately (MSFragger -> peptideprophet -> iprophet -> proteinprophet -> filter -> labelquant) and using the #325 seems to be very relevant to my issue. That thread is locked so I'm opening a new one. Wondering if that problem has been resolved or not. See pipeline yaml hereanalytics: true # reports when a workspace is created for usage statistics
slackToken: # specify the Slack API token (how to generate a token: https://api.slack.com/legacy/custom-integrations/legacy-tokens)
slackChannel: # specify the channel name, or
slackUserID: # specify a user ID for a direct message
Steps:
Database Search: yes # peptide to spectrum matching with Comet or MSFragger
Peptide Validation: yes # peptide assignment validation with PeptideProphet
PTM Localization: no # PTM site localization with PTMProphet
Protein Inference: yes # protein identification validation with ProteinProphet
Label-Free Quantification: no # precursor label-free quantification inspired by moFF
Isobaric Quantification: yes # isobaric labeling-based relative quantification for TMT and iTRAQ
Bio Cluster Quantification: no # protein report based on Uniprot protein clusters
FDR Filtering: yes # statistical filtering, validation and false discovery r ates assessment
Individual Reports: yes # multi-level reporting for both narrow-searches and open-searches
Integrated Reports: yes # combined analysis of LC-MS/MS results inspired by Abacus
Integrated Isobaric Quantification: yes # integrates channel abundances from multiple isobaric-tagged samples with TMT-Integrator
Database Search: # MSFragger-3.5 & Comet v2019011
protein_database: /PATH/TO/database/database.fasta # path to the target-decoy protein database
decoy_tag: rev_ # prefix tag used added to decoy sequences
contaminant_tag: false # prefix tag used added to decoy sequences
search_engine: msfragger # search engine options include "comet" and "msfragger"
comet: # Comet v2019011
noindex: true # skip mzML file indexing
param: # comet parameter file (default "comet.params.txt")
extension: mzML # format of the spectra file
msfragger: # MSFragger v3.5
path: ./bin/MSFragger-3.3.jar # path to MSFragger jar
memory: 8 # how much memory in GB to use
param: # MSFragger parameter file
extension: mzML # spectra format
num_threads: 0 # number of CPU threads to use. 0=poll CPU to set num threads
precursor_mass_lower: -20 # lower bound of the precursor mass window
precursor_mass_upper: 20 # upper bound of the precursor mass window
precursor_mass_units: 1 # 0=Daltons, 1=ppm
data_type: 0 # 0 for DDA, 1 for DIA, 2 for DIA-narrow-window
precursor_true_tolerance: 20 # true precursor mass tolerance (window is +/- this value)
precursor_true_units: 1 # 0=Daltons, 1=ppm
fragment_mass_tolerance: 0.02 # fragment mass tolerance (window is +/- this value)
fragment_mass_units: 0 # fragment mass tolerance units (0 for Da, 1 for ppm)
calibrate_mass: 2 # 0=Off, 1=On, 2=On and find optimal parameters
use_all_mods_in_first_search: 0 # use all variable modifications in first search (0 for No, 1 for Yes).
write_calibrated_mgf: 0 # write calibrated MS2 scan to a MGF file (0 for No, 1 for Yes)
isotope_error: 0/1/2 # 0=off, 0/1/2 (standard C13 "error")
mass_offsets: 0 # allow for additional precursor mass window shifts. Multiplexed with isotope_error. mass_offsets = 0/79.966 can be used as a restricted ‘open’ search that looks for unmodified and phosphorylated peptides (on any residue)
restrict_deltamass_to: all # specify amino acids on which delta masses (mass offsets or search modifications) can occur. Allowed values are single letter codes (e.g. ACD), must
precursor_mass_mode: selected # one of isolated/selected/corrected.
localize_delta_mass: 0 # this allows shifted fragment ions - fragment ions with mass increased by the calculated mass difference, to be included in scoring
delta_mass_exclude_ranges: (-1.5,3.5) # exclude mass range for shifted ions searching
fragment_ion_series: b,y # ion series used in search
ion_series_definitions: # user defined ion series. (Example: b* N -17.026548;b0 N -18.010565)
search_enzyme_name_1: Trypsin # Name of the first enzyme.
search_enzyme_cut_1: KR # First enzyme's cutting amino acid.
search_enzyme_nocut_1: P # First enzyme's protecting amino acid.
allowed_missed_cleavage_1: 2 # First enzyme's allowed number of missed cleavages per peptide. Maximum value is 5.
search_enzyme_sense_1: C # First enzyme's cutting terminal.
search_enzyme_name_2: # Name of the second enzyme.
search_enzyme_cut_2: # Second enzyme's cutting amino acid.
search_enzyme_nocut_2: # Second enzyme's protecting amino acid.
allowed_missed_cleavage_2: # Second enzyme's allowed number of missed cleavages per peptide. Maximum value is 5.
search_enzyme_sense_2: C # Second enzyme's cutting terminal.
num_enzyme_termini: 2 # 2 for enzymatic, 1 for semi-enzymatic, 0 for nonspecific digestion
clip_nTerm_M: 1 # specifies the trimming of a protein N-terminal methionine as a variable modification (0 or 1)
variable_mod_01: 15.99490 M 3 # variable modification
variable_mod_02: 0.984016 N # variable modification
variable_mod_03: -17.026549 nQ # variable modification
variable_mod_04: 39.994915 nC # variable modification
variable_mod_05: 229.162932 n^ # variable modification
variable_mod_06: # variable modification
variable_mod_07: # variable modification
allow_multiple_variable_mods_on_residue: 0 # static mods are not considered
max_variable_mods_per_peptide: 3 # maximum of 5
max_variable_mods_combinations: 5000 # maximum of 65534, limits number of modified peptides generated from sequence
mass_diff_to_variable_mod: 0 # put mass diff as a variable modification. 0 for no; 1 for yes and change the original mass diff and the calculated mass accordingly; 2 for yes but do not change the original mass diff.
output_file_extension: pepXML # file extension of output files
output_format: pepXML # file format of output files (pepXML or tsv)
output_report_topN: 1 # reports top N PSMs per input spectrum
output_max_expect: 50 # suppresses reporting of PSM if top hit has expectation greater than this threshold
report_alternative_proteins: 0 # 0=no, 1=yes
precursor_charge: 1 4 # assume range of potential precursor charge states. Only relevant when override_charge is set to 1
override_charge: 0 # 0=no, 1=yes to override existing precursor charge states with precursor_charge parameter
digest_min_length: 7 # minimum length of peptides to be generated during in-silico digestion
digest_max_length: 50 # maximum length of peptides to be generated during in-silico digestion
digest_mass_range: 500.0 5000.0 # mass range of peptides to be generated during in-silico digestion in Daltons
max_fragment_charge: 2 # maximum charge state for theoretical fragments to match (1-4)
track_zero_topN: 0 # in addition to topN results, keep track of top results in zero bin
zero_bin_accept_expect: 0 # boost top zero bin entry to top if it has expect under 0.01 - set to 0 to disable
zero_bin_mult_expect: 1 # disabled if above passes - multiply expect of zero bin for ordering purposes (does not affect reported expect)
add_topN_complementary: 0 # inserts complementary ions corresponding to the top N most intense fragments in each experimental spectra
check_spectral_files: 1 # check the spectral files before searching.
minimum_peaks: 30 # required minimum number of peaks in spectrum to search (default 10)
use_topN_peaks: 150 # pre-process experimental spectrum to only use top N peaks
deisotope: 1 # activates deisotoping.
deneutralloss: 1 # performs deneutrallossing or not (0=no, 1=yes)
min_fragments_modelling: 2 # minimum number of matched peaks in PSM for inclusion in statistical modeling
min_matched_fragments: 4 # minimum number of matched peaks for PSM to be reported
minimum_ratio: 0.01 # filters out all peaks in experimental spectrum less intense than this multiple of the base peak intensity
clear_mz_range: 0.0 0.0 # for iTRAQ/TMT type data; will clear out all peaks in the specified m/z range
remove_precursor_peak: 0 # remove precursor peaks from tandem mass spectra. 0=not remove; 1=remove the peak with precursor charge; 2=remove the peaks with all charge states.
remove_precursor_range: -1.5,1.5 # m/z range in removing precursor peaks. Unit: Da.
intensity_transform: 0 # transform peaks intensities with sqrt root. 0=not transform; 1=transform using sqrt root.
labile_search_mode: off # type of search (nglycan, labile, or off). Off means non-labile/typical search.
diagnostic_intensity_filter: 0 # [nglycan/labile search_mode only]. Minimum relative intensity for SUM of all detected oxonium ions to achieve for spectrum to contain diagnostic fragment evidence. Calculated relative to spectrum base peak. 0 <= value.
Y_type_masses: # [nglycan/labile search_mode only]. Specify fragments of labile mods that are commonly retained on intact peptides (e.g. Y ions for glycans). Only used if 'Y' is included in fragment_ion_series.
diagnostic_fragments: # [nglycan/labile search_mode only]. Specify diagnostic fragments of labile mods that appear in the low m/z region. Only used if diagnostic_intensity_filter > 0.
add_Cterm_peptide: 0.000000 # c-term peptide fixed modifications
add_Cterm_protein: 0.000000 # c-term protein fixed modifications
add_Nterm_peptide: 0.000000 # n-term peptide fixed modifications
add_Nterm_protein: 0.000000 # n-term protein fixed modifications
add_A_alanine: 0.000000 # alanine fixed modifications
add_C_cysteine: 57.021464 # cysteine fixed modifications
add_D_aspartic_acid: 0.000000 # aspartic acid fixed modifications
add_E_glutamic_acid: 0.000000 # glutamic acid fixed modifications
add_F_phenylalanine: 0.000000 # phenylalanine fixed modifications
add_G_glycine: 0.000000 # glycine fixed modifications
add_H_histidine: 0.000000 # histidine fixed modifications
add_I_isoleucine: 0.000000 # isoleucine fixed modifications
add_K_lysine: 229.162932 # lysine fixed modifications
add_L_leucine: 0.000000 # leucine fixed modifications
add_M_methionine: 0.000000 # methionine fixed modifications
add_N_asparagine: 0.000000 # asparagine fixed modifications
add_P_proline: 0.000000 # proline fixed modifications
add_Q_glutamine: 0.000000 # glutamine fixed modifications
add_R_arginine: 0.000000 # arginine fixed modifications
add_S_serine: 0.000000 # serine fixed modifications
add_T_threonine: 0.000000 # threonine fixed modifications
add_V_valine: 0.000000 # valine fixed modifications
add_W_tryptophan: 0.000000 # tryptophan fixed modifications
add_Y_tyrosine: 0.000000 # tyrosine fixed modifications
Peptide Validation: # PeptideProphet v5.2
concurrent: false # Concurrent execution of multiple instaces
extension: pepXML # pepXML file extension
clevel: 0 # set Conservative Level in neg_stdev from the neg_mean, low numbers are less conservative, high numbers are more conservative
accmass: true # use Accurate Mass model binning
decoyprobs: true # compute possible non-zero probabilities for Decoy entries on the last iteration
enzyme: trypsin # enzyme used in sample (optional)
exclude: false # exclude deltaCn*, Mascot*, and Comet* results from results (default Penalize * results)
expectscore: true # use expectation value as the only contributor to the f-value for modeling
forcedistr: false # bypass quality control checks, report model despite bad modeling
glyc: false # enable peptide Glyco motif model
icat: false # apply ICAT model (default Autodetect ICAT)
instrwarn: false # warn and continue if combined data was generated by different instrument models
leave: false # leave alone deltaCn*, Mascot*, and Comet* results from results (default Penalize * results)
maldi: false # enable MALDI mode
masswidth: 5 # model mass width (default 5)
minpeplen: 7 # minimum peptide length not rejected (default 7)
minpintt: 2 # minimum number of NTT in a peptide used for positive pI model (default 2)
minpiprob: 0.9 # minimum probability after first pass of a peptide used for positive pI model (default 0.9)
minprob: 0.05 # report results with minimum probability (default 0.05)
minrtntt: 2 # minimum number of NTT in a peptide used for positive RT model (default 2)
minrtprob: 0.9 # minimum probability after first pass of a peptide used for positive RT model (default 0.9)
neggamma: false # use Gamma distribution to model the negative hits
noicat: false # do no apply ICAT model (default Autodetect ICAT)
nomass: false # disable mass model
nonmc: false # disable NMC missed cleavage model
nonparam: true # use semi-parametric modeling, must be used in conjunction with --decoy option
nontt: false # disable NTT enzymatic termini model
optimizefval: false # (SpectraST only) optimize f-value function f(dot,delta) using PCA
phospho: false # enable peptide Phospho motif model
pi: false # enable peptide pI model
ppm: true # use PPM mass error instead of Dalton for mass modeling
zero: false # report results with minimum probability 0
PTM Localization: # PTMProphet v6.1
autodirect: false # use direct evidence when the lability is high, use in combination with LABILITY
cions: # use specified C-term ions, separate multiple ions by commas (default: y for CID, z for ETD)
direct: false # use only direct evidence for evaluating PTM site probabilities
em: 2 # set EM models to 0 (no EM), 1 (Intensity EM Model Applied) or 2 (Intensity and Matched Peaks EM Models Applied)
static: false # use static fragppmtol for all PSMs instead of dynamically estimates offsets and tolerances
fragppmtol: 15 # when computing PSM-specific mass_offset and mass_tolerance, use specified default +/- MS2 mz tolerance on fragment ions
ifrags: false # use internal fragments for localization
keepold: false # retain old PTMProphet results in the pepXML file
lability: false # compute Lability of PTMs
massdiffmode: false # use the Mass Difference and localize
excludemassdiffmin: 0 # Minimum mass difference excluded for MASSDIFFFMODE analysis (default=0)
excludemassdiffmax: 0 # Maximun mass difference excluded for MASSDIFFFMODE analysis (default=0)
massoffset: 0 # adjust the massdiff by offset (0 = use default)
maxfragz: 0 # limit maximum fragment charge (default: 0=precursor charge, negative values subtract from precursor charge)
maxthreads: 4 # use specified number of threads for processing
mino: 0 # use specified number of pseudo-counts when computing Oscore (0 = use default)
minprob: 0 # use specified minimum probability to evaluate peptides
mods: # specify modifications
nions: # use specified N-term ions, separate multiple ions by commas (default: a,b for CID, c for ETD)
nominofactor: false # disable MINO factor correction when MINO= is set greater than 0 (default: apply MINO factor correction)
ppmtol: 1 # use specified +/- MS1 ppm tolerance on peptides which may have a slight offset depending on search parameters
verbose: false # produce Warnings to help troubleshoot potential PTM shuffling or mass difference issues
Protein Inference: # ProteinProphet v5.2
accuracy: false # equivalent to --minprob 0
allpeps: false # consider all possible peptides in the database in the confidence model
confem: false # use the EM to compute probability given the confidence
delude: false # do NOT use peptide degeneracy information when assessing proteins
excludezeros: false # exclude zero prob entries
fpkm: false # model protein FPKM values
glyc: false # highlight peptide N-glycosylation motif
icat: false # highlight peptide cysteines
instances: false # use Expected Number of Ion Instances to adjust the peptide probabilities prior to NSP adjustment
iprophet: false # input is from iProphet
logprobs: false # use the log of the probabilities in the Confidence calculations
maxppmdiff: 20 # maximum peptide mass difference in PPM (default 20)
minprob: 0.05 # peptideProphet probabilty threshold (default 0.05)
mufactor: 1 # fudge factor to scale MU calculation (default 1)
nogroupwts: false # check peptide's Protein weight against the threshold (default: check peptide's Protein Group weight against threshold)
nonsp: false # do not use NSP model
nooccam: false # non-conservative maximum protein list
noprotlen: false # do not report protein length
normprotlen: false # normalize NSP using Protein Length
protmw: false # get protein mol weights
softoccam: false # peptide weights are apportioned equally among proteins within each Protein Group (less conservative protein count estimate)
unmapped: false # report results for UNMAPPED proteins
Label-Free Quantification: # Freequant
peakTimeWindow: 0.4 # specify the time windows for the peak (minute) (default 0.4)
retentionTimeWindow: 3 # specify the retention time window for xic (minute) (default 3)
tolerance: 10 # m/z tolerance in ppm (default 10)
raw: false # read raw files instead of converted mzML, or mzXML
faims: false # use FAIMS information for the quantification
Isobaric Quantification: # Labelquant
bestPSM: false # select the best PSMs for protein quantification
level: 2 # ms level for the quantification
minProb: 0.7 # only use PSMs with a minimum probability score
plex: 10 # number of channels
purity: 0.5 # ion purity threshold (default 0.5)
removeLow: 0.0 # ignore the lower 3% PSMs based on their summed abundances
tolerance: 20 # m/z tolerance in ppm (default 20)
uniqueOnly: false # report quantification based on only unique peptides
brand: tmt # isobaric labeling brand (tmt, itraq)
raw: false # read raw files instead of converted mzML, or mzXML
Bio Cluster Quantification: # BioQuant
organismUniProtID: # UniProt proteome ID
level: 0.9 # cluster identity level (default 0.9)
FDR Filtering: # Filter
psmFDR: 0.01 # psm FDR level (default 0.01)
peptideFDR: 0.01 # peptide FDR level (default 0.01)
ionFDR: 0.01 # peptide ion FDR level (default 0.01)
proteinFDR: 0.01 # protein FDR level (default 0.01)
peptideProbability: 0.7 # top peptide probability threshold for the FDR filtering (default 0.7)
proteinProbability: 0.5 # protein probability threshold for the FDR filtering (not used with the razor algorithm) (default 0.5)
peptideWeight: 1 # threshold for defining peptide uniqueness (default 1)
razor: false # use razor peptides for protein FDR scoring
picked: false # apply the picked FDR algorithm before the protein scoring
mapMods: false # map modifications acquired by an open search
models: false # print model distribution
sequential: false # alternative algorithm that estimates FDR using both filtered PSM and Protein lists
Individual Reports: # Report
msstats: false # create an output compatible to MSstats
withDecoys: false # add decoy observations to reports
mzID: false # create a mzID output
prefix: false # add the project (folder) name as a prefix to the output files
Integrated Reports: # Abacus
protein: true # global level protein report
peptide: true # global level peptide report
proteinProbability: 0.9 # minimum protein probability (default 0.9)
peptideProbability: 0.5 # minimum peptide probability (default 0.5)
uniqueOnly: false # report TMT quantification based on only unique peptides
reprint: false # create abacus reports using the Reprint format
Integrated Isobaric Quantification: # TMT-Integrator v4.0.0
path: # path to TMT-Integrator jar
memory: 6 # memory allocation, in Gb
output: # the location of output files
channel_num: 10 # number of channels in the multiplex (e.g. 10, 11)
ref_tag: Bridge # unique tag for identifying the reference channel (Bridge sample added to each multiplex)
groupby: -1 # level of data summarization(0: PSM aggregation to the gene level; 1: protein; 2: peptide sequence; 3: PTM site; -1: generate reports at all levels)
psm_norm: false # perform additional retention time-based normalization at the PSM level
outlier_removal: true # perform outlier removal
prot_norm: -1 # normalization (0: None; 1: MD (median centering); 2: GN (median centering + variance scaling); -1: generate reports with all normalization options)
min_pep_prob: 0.9 # minimum PSM probability threshold (in addition to FDR-based filtering by Philosopher)
min_purity: 0.5 # ion purity score threshold
min_percent: 0.05 # remove low intensity PSMs (e.g. value of 0.05 indicates removal of PSMs with the summed TMT reporter ions intensity in the lowest 5% of all PSMs)
unique_pep: false # allow PSMs with unique peptides only (if true) or unique plus razor peptides (if false), as classified by Philosopher and defined in PSM.tsv files
unique_gene: 0 # additional, gene-level uniqueness filter (0: allow all PSMs; 1: remove PSMs mapping to more than one GENE with evidence of expression in the dataset; 2:remove all PSMs mapping to more than one GENE in the fasta file)
best_psm: true # keep the best PSM only (highest summed TMT intensity) among all redundant PSMs within the same LC-MS run
prot_exclude: none # exclude proteins with specified tags at the beginning of the accession number (e.g. none: no exclusion; sp|,tr| : exclude protein with sp| or tr|)
allow_overlabel: true # allow PSMs with TMT on S (when overlabeling on S was allowed in the database search)
allow_unlabeled: true # allow PSMs without TMT tag or acetylation on the peptide n-terminus
mod_tag: none # PTM info for generation of PTM-specific reports (none: for Global data; S[167],T[181],Y[243]: for Phospho; K[170]: for K-Acetyl)
min_site_prob: -1 # site localization confidence threshold (-1: for Global; 0: as determined by the search engine; above 0 (e.g. 0.75): PTMProphet probability, to be used with phosphorylation only)
ms1_int: true # use MS1 precursor ion intensity (if true) or MS2 summed TMT reporter ion intensity (if false) as part of the reference sample abundance estimation
top3_pep: true # use top 3 most intense peptide ions as part of the reference sample abundance estimation
print_RefInt: false # print individual reference sample abundance estimates for each multiplex in the final reports (in addition to the combined reference sample abundance estimate)
add_Ref: -1 # add an artificial reference channel if there is no reference channel (-1: don't add the reference; 0: use summation as the reference; 1: use average as the reference; 2: use median as the reference)
max_pep_prob_thres: 0 # the threshold for maximum peptide probability
min_ntt: 0 # minimum allowed number of enzymatic termini
aggregation_method: 0 # the aggregation method from the PSM level to the specified level (0: median, 1: weighted-ratio)
log2transformed: true # report ratio and abundance reports in the log2 scale |
Beta Was this translation helpful? Give feedback.
Answered by
fcyu
Nov 22, 2023
Replies: 1 comment 2 replies
-
|
I think the Philosopher pipeline is no longer under maintenance. Please use FragPipe instead: https://github.com/Nesvilab/FragPipe. It has both GUI and command line interface. Best, Fengchao |
Beta Was this translation helpful? Give feedback.
2 replies
-
|
Yeah FragPipe does work! Philosopher is included in FragPipe. Is philosopher no longer maintained as a stand-alone software but still maintained for FragPipe? |
Beta Was this translation helpful? Give feedback.
-
|
Philosopher is still under maintenance. Just the pipeline command is not. |
Beta Was this translation helpful? Give feedback.
Answer selected by
zhuchcn
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
I think the Philosopher pipeline is no longer under maintenance. Please use FragPipe instead: https://github.com/Nesvilab/FragPipe. It has both GUI and command line interface.
Best,
Fengchao