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Nesvilab / philosopher

PeptideProphet, PTMProphet, ProteinProphet, iProphet, Abacus, and FDR filtering
https://philosopher.nesvilab.org
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panic: runtime error: index out of range [0] with length 0 when running Label-free quantification #241

Closed vinayakvsv closed 3 years ago

vinayakvsv commented 3 years ago

When I am running Philosopher (version 3.4.13) on a set of TMT10-MS3 samples, I am reaching the "label-free quantification step" and experiencing the following error message:

...
time="10:23:04" level=info msg="Creating combined protein inference"
INFO: mu=1.12246e-05, db_size=45499165
time="10:25:02" level=info msg="Executing filter on Protein_01"
time="10:25:02" level=info msg="Processing peptide identification files"
time="10:25:12" level=info msg="Printing models"
time="10:25:17" level=info msg="1+ Charge profile" decoy=0 target=0
time="10:25:17" level=info msg="2+ Charge profile" decoy=2351 target=37046
time="10:25:17" level=info msg="3+ Charge profile" decoy=1899 target=30132
time="10:25:17" level=info msg="4+ Charge profile" decoy=489 target=6935
time="10:25:17" level=info msg="5+ Charge profile" decoy=93 target=590
time="10:25:17" level=info msg="6+ Charge profile" decoy=0 target=0
time="10:25:17" level=info msg="Database search results" ions=56525 peptides=50157 psms=79535
time="10:25:18" level=info msg="Converged to 1.00 % FDR with 61389 PSMs" decoy=619 threshold=0.7643 total=62008
time="10:25:21" level=info msg="Converged to 1.00 % FDR with 35606 Peptides" decoy=358 threshold=0.8511 total=35964
time="10:25:22" level=info msg="Converged to 1.00 % FDR with 40866 Ions" decoy=412 threshold=0.8337 total=41278
time="10:25:27" level=info msg="Protein inference results" decoy=297 target=7805
time="10:25:27" level=info msg="Converged to 1.01 % FDR with 7146 Proteins" decoy=72 threshold=0.9258 total=7218
time="10:25:31" level=info msg="Applying sequential FDR estimation" ions=38550 peptides=33551 psms=56978
time="10:25:32" level=info msg="Converged to 0.13 % FDR with 56899 PSMs" decoy=79 threshold=0.7643 total=56978
time="10:25:33" level=info msg="Converged to 0.20 % FDR with 33482 Peptides" decoy=69 threshold=0.9001 total=33551
time="10:25:35" level=info msg="Converged to 0.18 % FDR with 38480 Ions" decoy=70 threshold=0.7644 total=38550
time="10:25:36" level=info msg="Post processing identifications"
time="10:25:43" level=info msg="Mapping modifications"
time="10:26:01" level=info msg="Processing modifications"
time="10:27:57" level=info msg="Processing protein inference"
time="10:28:15" level=info msg="Assigning protein identifications to layers"
time="10:28:17" level=info msg="Updating razor PSM assignment to proteins"
time="10:28:18" level=info msg="Calculating spectral counts"
time="10:28:18" level=info msg=Saving
time="10:28:34" level=info msg="Executing label-free quantification on Protein_01"
time="10:28:50" level=info msg="Indexing PSM information"
time="10:28:51" level=info msg="Reading spectra and tracing peaks"
time="10:28:51" level=info msg="Processing f04538_Prot_01_F01"
panic: runtime error: index out of range [0] with length 0

goroutine 1 [running]:
philosopher/lib/mzn.processSpectrum(0xc076d9e040, 0x1b, 0xc0c6bc3768, 0x8, 0x0, 0x0, 0x0, 0xc0c6bbe4e0, 0x2e, 0xc0c6bc3788, ...)
        /workspace/philosopher/lib/mzn/mzn.go:247 +0x11bd
philosopher/lib/mzn.(*MsData).Read(0xc000190d50, 0xc0214c8690, 0xe9)
        /workspace/philosopher/lib/mzn/mzn.go:98 +0x198
philosopher/lib/qua.peakIntensity(0x0, 0x0, 0x0, 0xc00e0980e0, 0x62, 0x1086108, 0x1, 0xc0596e3e09, 0x5, 0xc0596e3e40, ...)
        /workspace/philosopher/lib/qua/lfq.go:82 +0x10ca
philosopher/lib/qua.RunLabelFreeQuantification(0xc002afc2d0, 0xe2, 0xbefa0a, 0x4, 0xbef972, 0x4, 0xc00002c2a0, 0xd1, 0x0, 0x0, ...)
        /workspace/philosopher/lib/qua/qua.go:44 +0x155
philosopher/lib/pip.FreeQuant(0xc00002a5d0, 0x24, 0xc00002ca80, 0xd1, 0xc00002a600, 0x29, 0xc00002cb60, 0xe0, 0xc00002cc40, 0xd7, ...)
        /workspace/philosopher/lib/pip/pip.go:534 +0x538
philosopher/cmd.glob..func13(0x79aebe0, 0xc0000e3830, 0x1, 0x3)
        /workspace/philosopher/cmd/pipeline.go:109 +0xa25
github.com/spf13/cobra.(*Command).execute(0x79aebe0, 0xc0000e37d0, 0x3, 0x3, 0x79aebe0, 0xc0000e37d0)
        /home/prvst/go/pkg/mod/github.com/spf13/cobra@v0.0.6/command.go:844 +0x2c2
github.com/spf13/cobra.(*Command).ExecuteC(0x79af660, 0x0, 0x0, 0x0)
        /home/prvst/go/pkg/mod/github.com/spf13/cobra@v0.0.6/command.go:945 +0x336
github.com/spf13/cobra.(*Command).Execute(...)
        /home/prvst/go/pkg/mod/github.com/spf13/cobra@v0.0.6/command.go:885
philosopher/cmd.Execute()
        /workspace/philosopher/cmd/root.go:35 +0x2d
main.main()
        /workspace/philosopher/main.go:22 +0x6e

Attached is my philosopher.yml file. I am running MSFragger version 3.1.1 (the same bug comes with MSFragger 3.2) and TMT-Integrator version 2.4. 

# Philosopher pipeline configuration file.
# May 31, 2021
# The pipeline mode automates the processing done by Philosopher and other tools. First, check
# the steps you want to execute in the commands section and change them to
# 'yes'. For each selected command, go to its section and adjust the parameters
# accordingly to your analysis.
#
# If you want to include MSFragger and TMT-Integrator into your analysis, you will
# have to download them separately, and then add their location in their
# configuration section.
#
# Usage:
# philosopher pipeline --config <this_configuration_file> [list_of_data_set_folders]

analytics: 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: yes                  # precursor label-free quantification inspired by moFF
  Isobaric Quantification: yes                    # isobaric labeling-based relative quantification for TMT and iTRAQ
  Bio Cluster Quantification: yes                 # 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 3.1 & Comet
  protein_database: /hps/research1/icortes/vvv776/referenceProteomes/2021-02-19-decoys-reviewed-contam-UP000005640.fas                  # path to the target-decoy protein database
  decoy_tag: rev_                                # prefix tag used added to decoy sequences
  search_engine: msfragger                           # search engine options include "comet" and "msfragger"
  comet:                                         # Comet v2019011
    noindex: false                                # skip mzML file indexing
    param:                                       # comet parameter file (default "comet.params.txt")
    raw: mzML                                    # format of the spectra file
  msfragger:                                     # MSFragger v3.0
    path: /hps/research1/icortes/vvv776/pipelines_tempfolder/cptac3/pipeline/ebi_proteomic_pipelines/yml_templates/../MSFragger-3.2/MSFragger-3.2.jar            # path to MSFragger jar
    memory: 8                                    # how much memory in GB to use
    param:                                       # MSFragger parameter file
    raw: mzML                                    # spectra format
    num_threads: 0                               # 0=poll CPU to set num threads; else specify num threads directly (max 64)
    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
    precursor_true_tolerance: 20                 # true precursor mass tolerance (window is +/- this value)
    precursor_true_units: 1                      # 0=Daltons, 1=ppm
    fragment_mass_tolerance: 0.6                  # fragment mass tolerance (window is +/- this value)
    fragment_mass_units: 0                       # fragment mass tolerance units (0 for Da, 1 for ppm)
    calibrate_mass: 0                            # 0=Off, 1=On, 2=On and find optimal parameters # should I put this at "2"
    deisotope: 1                                 # activates deisotoping.
    isotope_error: -1/0/1/2/3                         # 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)
    precursor_mass_mode: selected                # selected or isolated
    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
    search_enzyme_name: Trypsin                  # name of enzyme to be written to the pepXML file
    search_enzyme_cutafter: KR                   # residues after which the enzyme cuts
    search_enzyme_butnotafter: P                 # residues that the enzyme will not cut before
    num_enzyme_termini: 2                        # 2 for enzymatic, 1 for semi-enzymatic, 0 for nonspecific digestion
    allowed_missed_cleavage: 1                   # maximum value is 5
    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: 42.01060 [^ 1               # variable modification
    variable_mod_03: 229.162932 n^ 1                            # variable modification
    variable_mod_04: 229.162932 S 1                            # variable modification
    variable_mod_05:                             # 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
    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
    minimum_peaks: 15                            # required minimum number of peaks in spectrum to search (default 10)
    use_topN_peaks: 100                          # pre-process experimental spectrum to only use top N peaks
    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: 125.5 131.5                      # 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.
    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.
    labile_search_mode: "off"                    # type of search (nglycan, labile, or off). Off means non-labile/typical search.
    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
    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: 0.000000                       # 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 v6.0
  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)

Isobaric Quantification:                         # Labelquant
  bestPSM: false                                 # select the best PSMs for protein quantification
  level: 3                                       # 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)

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: true                                   # use razor peptides for protein FDR scoring
  picked: true                                  # apply the picked FDR algorithm before the protein scoring
  mapMods: true                                 # map modifications acquired by an open search
  models: true                                  # print model distribution
  sequential: true                              # 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

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 v1.1.10
  path: /hps/research1/icortes/vvv776/pipelines_tempfolder/cptac3/pipeline/ebi_proteomic_pipelines/yml_templates/../fragpipe/tools/tmt-integrator-2.4.0.jar      # path to TMT-Integrator jar
  memory: 6                                      # memory allocation, in Gb
  output: ./
  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

I made sure to remove white-spaces from my annotation.txt file -- previously, annotation.txt file formatting issues were throwing this bug for me when running on TMT11-MS3 data.

Based on the bug, it seems like the label-free quantification step isn't receiving or recognizing my pepXML files, but I am not sure what might be causing it.

Please let me know if I am doing anything wrong or what might be the source of the error. Thanks.

--Vinay

vinayakvsv commented 3 years ago

I am closing this issue because I fixed the problem -- I reconverted my raw files with msconvert, set noindex: false, and found that MSFragger 3.2 works on the files I was trying to analyze.