[BUG] FDR to QValue Numba Typing Error

[singjc]

Hi @RalfG,

I'm not sure if I should make the issue here or in the ms2rescore repo, but the downstream error seems to be in Mokapot.

When performing rescoring using MS2Rescore (v3.1.4) on Sage search results (Bruker immunopeptidomics data from the Thunder-DDA-PASEF paper), Mokapot (v0.10.0) seems to run into an error when computing the confidence estimates. I'm not entirely sure what the error is, but it seems to be an issue with Numba (see log below).

If you would like the sage results tsv file for debugging, let me know.

Best,

Justin

Log

2025-01-23 09:57:20 INFO     ms2rescore.feature_generators.im2deep // Running   
                             IM2Deep for PSMs from run (18/18):                 
                             `G230411_026_Slot2-29_1_9464`...                   
2025-01-23 10:10:13 INFO     ms2rescore.core // Removed 0 PSMs with rank >= 1.  
2025-01-23 10:10:40 ERROR    ms2rescore.__main__ // Failed in nopython mode     
                             pipeline (step: nopython frontend)                 
                             non-precise type array(pyobject, 1d, C)            
                             During: typing of argument at                      
                             /home/roestlab/anaconda3/envs/py310_JS/lib/python3.
                             10/site-packages/mokapot/qvalues.py (186)          
                                                                                
                             File                                               
                             "../../../../../../../../home/roestlab/anaconda3/en
                             vs/py310_JS/lib/python3.10/site-packages/mokapot/qv
                             alues.py", line 186:                               
                             def crosslink_tdc(scores, num_targets, desc=True): 
                                 <source elided>                                
                                                                                
                             @nb.njit                                           
                             ^

Full Traceback Error Log

2025-01-23 09:57:20 INFO     ms2rescore.feature_generators.im2deep // Running   
                             IM2Deep for PSMs from run (18/18):                 
                             `G230411_026_Slot2-29_1_9464`...                   
2025-01-23 10:10:13 INFO     ms2rescore.core // Removed 0 PSMs with rank >= 1.  
2025-01-23 10:10:40 ERROR    ms2rescore.__main__ // Failed in nopython mode     
                             pipeline (step: nopython frontend)                 
                             non-precise type array(pyobject, 1d, C)            
                             During: typing of argument at                      
                             /home/roestlab/anaconda3/envs/py310_JS/lib/python3.
                             10/site-packages/mokapot/qvalues.py (186)          
                                                                                
                             File                                               
                             "../../../../../../../../home/roestlab/anaconda3/en
                             vs/py310_JS/lib/python3.10/site-packages/mokapot/qv
                             alues.py", line 186:                               
                             def crosslink_tdc(scores, num_targets, desc=True): 
                                 <source elided>                                
                                                                                
                             @nb.njit                                           
                             ^
                                                                                
                             ╭─────── Traceback (most recent call last) ───────╮
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/ms2rescore/__main__.py:237 │
                             │  in main                                        │
                             │                                                 │
                             │   234 │   │   │   profiled_rescore = profile(re │
                             │   235 │   │   │   profiled_rescore(configuratio │
                             │   236 │   │   else:                             │
                             │ ❱ 237 │   │   │   rescore(configuration=config) │
                             │   238 │   except Exception as e:                │
                             │   239 │   │   LOGGER.exception(e)               │
                             │   240 │   │   sys.exit(1)                       │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/ms2rescore/core.py:168 in  │
                             │ rescore                                         │
                             │                                                 │
                             │   165 │   if all(psm_list["pep"] == 1.0):       │
                             │   166 │   │   psm_list = _fix_constant_pep(psm_ │
                             │   167 │   psm_list = _filter_by_rank(psm_list,  │
                             │ ❱ 168 │   psm_list = _calculate_confidence(psm_ │
                             │   169 │   _ = _log_id_psms_after(psm_list, id_p │
                             │       max_rank=config["max_psm_rank_output"])   │
                             │   170 │                                         │
                             │   171 │   # Write output                        │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/ms2rescore/core.py:317 in  │
                             │ _calculate_confidence                           │
                             │                                                 │
                             │   314 │   )                                     │
                             │   315 │                                         │
                             │   316 │   # Recalculate confidence              │
                             │ ❱ 317 │   new_confidence = lin_psm_data.assign_ │
                             │   318 │                                         │
                             │   319 │   # Add new confidence estimations to P │
                             │   320 │   add_psm_confidence(psm_list, new_conf │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/mokapot/dataset.py:607 in  │
                             │ assign_confidence                               │
                             │                                                 │
                             │   604 │   │                                     │
                             │   605 │   │   if self._group_column is None:    │
                             │   606 │   │   │   LOGGER.info("Assigning confid │
                             │ ❱ 607 │   │   │   return LinearConfidence(      │
                             │   608 │   │   │   │   self,                     │
                             │   609 │   │   │   │   scores,                   │
                             │   610 │   │   │   │   eval_fdr=eval_fdr,        │
                             │                                                 │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/mokapot/confidence.py:375  │
                             │ in __init__                                     │
                             │                                                 │
                             │   372 │   │   self._perform_tdc(self._psm_colum │
                             │   373 │   │   LOGGER.info("\t- Found %i PSMs fr │
                             │   374 │   │                                     │
                             │ ❱ 375 │   │   self._assign_confidence(desc=desc │
                             │   376 │   │                                     │
                             │   377 │   │   self.accepted = {}                │
                             │   378 │   │   for level in self.levels:         │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/mokapot/confidence.py:455  │
                             │ in _assign_confidence                           │
                             │                                                 │
                             │   452 │   │   │                                 │
                             │   453 │   │   │   # Estimate q-values and assig │
                             │   454 │   │   │   LOGGER.info("Assiging q-value │
                             │ ❱ 455 │   │   │   data["mokapot q-value"] = qva │
                             │   456 │   │   │                                 │
                             │   457 │   │   │   # Make output tables pretty   │
                             │   458 │   │   │   data = data.drop(self._target │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/mokapot/qvalues.py:109 in  │
                             │ tdc                                             │
                             │                                                 │
                             │   106 │   with open('other_args.pkl', 'wb') as  │
                             │   107 │   │   pickle.dump(other_args, psm_file) │
                             │   108 │                                         │
                             │ ❱ 109 │   qvals = _fdr2qvalue(fdr, num_total, u │
                             │   110 │   qvals = np.flip(qvals)                │
                             │   111 │   qvals = qvals[np.argsort(srt_idx)]    │
                             │   112                                           │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/numba/core/dispatcher.py:4 │
                             │ 23 in _compile_for_args                         │
                             │                                                 │
                             │    420 │   │   │   │   │      f"by the followin │
                             │    421 │   │   │   │   e.patch_message(msg)     │
                             │    422 │   │   │                                │
                             │ ❱  423 │   │   │   error_rewrite(e, 'typing')   │
                             │    424 │   │   except errors.UnsupportedError a │
                             │    425 │   │   │   # Something unsupported is p │
                             │    426 │   │   │   error_rewrite(e, 'unsupporte │
                             │                                                 │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/py310_JS/lib/pyth │
                             │ on3.10/site-packages/numba/core/dispatcher.py:3 │
                             │ 64 in error_rewrite                             │
                             │                                                 │
                             │    361 │   │   │   if config.FULL_TRACEBACKS:   │
                             │    362 │   │   │   │   raise e                  │
                             │    363 │   │   │   else:                        │
                             │ ❱  364 │   │   │   │   raise e.with_traceback(N │
                             │    365 │   │                                    │
                             │    366 │   │   argtypes = []                    │
                             │    367 │   │   for a in args:                   │
                             ╰─────────────────────────────────────────────────╯
                             TypingError: Failed in nopython mode pipeline      
                             (step: nopython frontend)                          
                             non-precise type array(pyobject, 1d, C)            
                             During: typing of argument at                      
                             /home/roestlab/anaconda3/envs/py310_JS/lib/python3.
                             10/site-packages/mokapot/qvalues.py (186)          
                                                                                
                             File                                               
                             "../../../../../../../../home/roestlab/anaconda3/en
                             vs/py310_JS/lib/python3.10/site-packages/mokapot/qv
                             alues.py", line 186:                               
                             def crosslink_tdc(scores, num_targets, desc=True): 
                                 <source elided>                                
                                                                                
                             @nb.njit                                           
                             ^

To Reproduce:

Command

ms2rescore -p ./ms2rescore_mars/results.sage.tsv -t sage -c ./ms2rescore_mars/ms2rescore_config.json

MS2Rescore Config

{
    "$schema": "./config_schema.json",
    "ms2rescore": {
        "feature_generators": {
            "deeplc": {
                "calibration_set_size": 0.6,
                "deeplc_retrain": false
            },
            "ms2pip": {
                "model": "HCD",
                "ms2_tolerance": 0.02
            },
            "im2deep": {
                "reference_dataset": "/media/roestlab/Data1/User/JustinS/jpst002044_pxd040385_thunder_ddapasef/results/20241206_no_redeem_lda/ms2rescore_mars/reference_ccs"
            }
        },
        "rescoring_engine": {
            "mokapot": {
                "write_weights": true,
                "write_flashlfq": false
            }
        },
        "config_file": "/media/roestlab/Data1/User/JustinS/jpst002044_pxd040385_thunder_ddapasef/results/20241206_no_redeem_lda/ms2rescore_mars/ms2rescore_config.json",
        "psm_file": [
            "/media/roestlab/Data1/User/JustinS/jpst002044_pxd040385_thunder_ddapasef/results/20241206_no_redeem_lda/ms2rescore_mars//results.sage.tsv"
        ],
        "psm_file_type": "sage",
        "psm_reader_kwargs": {},
        "spectrum_path": "/media/roestlab/Data1/User/JustinS/jpst002044_pxd040385_thunder_ddapasef/results/20241206_no_redeem_lda/G230411_data/",
        "output_path": "/media/roestlab/Data1/User/JustinS/jpst002044_pxd040385_thunder_ddapasef/results/20241206_no_redeem_lda/ms2rescore_mars/",
        "log_level": "info",
        "id_decoy_pattern": "rev_",
        "psm_id_pattern": null,
        "spectrum_id_pattern": null,
        "lower_score_is_better": false,
        "modification_mapping": {
            "+15.9949": "U:Oxidation",
            "+57.0215": "U:Carbamidomethyl"
        },
        "fixed_modifications": {},
        "processes": 30,
        "rename_to_usi": false,
        "fasta_file": null,
        "write_report": true
    }
}

System

OS:

• Ubuntu 18.04.6 LTS
• 187Gb RAM
• 18 CPU cores

Python:

• Python 3.10 (Anaconda Env)
• MS2Rescore v3.1.4
• Mokapot v0.10.0

[jspaezp]

Hey there @singjc!

Thanks for reporting the error! On the next release of mokapot (which hopefully will happen in ~1 month) we will be removing the numba dependency, so this should not be a problem.

I noticed you are using py3.10 Python 3.10 (Anaconda Env), would you mind checking if py3.9 works for you?

Best,
Sebastian

[singjc]

Hey there @singjc!

Thanks for reporting the error! On the next release of mokapot (which hopefully will happen in ~1 month) we will be removing the numba dependency, so this should not be a problem.

I noticed you are using py3.10 Python 3.10 (Anaconda Env), would you mind checking if py3.9 works for you?

Best, Sebastian

Hi, sorry I meant to follow-up on this. I tested python3.9, but that resulted in a different error which seemed to be from ms2rescore/ms2pip side.

Is there a dev branch I could test with the mokapot numba dependency removed?

Best,

Justin

2025-01-31 11:30:01 ERROR    ms2rescore.__main__ // Decompression fails         
                             RemoteTraceback:                                   
                             """                                                
                             Traceback (most recent call last):                 
                               File                                             
                             "/home/roestlab/anaconda3/envs/ms2rescore_env/lib/p
                             ython3.9/multiprocessing/pool.py", line 125, in    
                             worker                                             
                                 result = (True, func(*args, **kwds))           
                               File                                             
                             "/home/roestlab/anaconda3/envs/ms2rescore_env/lib/p
                             ython3.9/site-packages/ms2pip/core.py", line 911,  
                             in _process_spectra                                
                                 for spectrum in read_spectrum_file(spec_file): 
                               File                                             
                             "/home/roestlab/anaconda3/envs/ms2rescore_env/lib/p
                             ython3.9/site-packages/ms2pip/spectrum_input.py",  
                             line 33, in read_spectrum_file                     
                                 spectra = get_ms2_spectra(str(spectrum_file))  
                             Exception: Decompression fails                     
                             """                                                
                                                                                
                             The above exception was the direct cause of the    
                             following exception:

Full error log

MS²Rescore (v3.1.4)
Developed at CompOmics, VIB / Ghent University, Belgium.
Please cite: Buur & Declercq et al. JPR (2024)

2025-01-31 09:19:42 INFO     ms2rescore.parse_psms // Reading PSMs from PSM file
                             (1/1): 'ms2rescore_mars/results.sage.tsv'...       
2025-01-31 09:21:11 INFO     ms2rescore.parse_psms // Removed 0 PSMs with rank  
                             >= 10.                                             
2025-01-31 09:21:14 WARNING  ms2rescore.parse_psms // Removed 2 PSMs with       
                             invalid amino acids.                               
2025-01-31 09:21:18 INFO     ms2rescore.parse_psms // Found 1152514 PSMs, of    
                             which 29.02% are decoys.                           
2025-01-31 09:21:26 WARNING  ms2rescore.parse_psms // Non-mapped modifications  
                             found: {'-17.026548', '+119.0041', '-18.010565',   
                             '+42.010567'}                                      
                             This can be ignored if they are Unimod modification
                             labels.                                            
2025-01-31 09:21:32 INFO     ms2rescore.core // Found 335390 identified PSMs    
                             with rank <= 1 at 0.01 FDR before rescoring.       
2025-01-31 09:21:37 INFO     ms2rescore.feature_generators.deeplc // Adding     
                             DeepLC-derived features to PSMs.                   
2025-01-31 09:21:39 INFO     ms2rescore.feature_generators.deeplc // Running    
                             DeepLC for PSMs from run (1/18):                   
                             `G230411_023_Slot2-28_1_9461`... 
...
2025-01-31 11:26:19 INFO     ms2rescore.feature_generators.ms2pip // Running    
                             MS²PIP for PSMs from run (12/18)                   
                             `G230411_028_Slot2-29_1_9466`...                   
2025-01-31 11:26:21 INFO     ms2pip.core // Processing spectra and peptides...  
2025-01-31 11:26:26.370343: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2025-01-31 11:26:26.383974: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1738340786.407310   17523 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2025-01-31 11:30:01 ERROR    ms2rescore.__main__ // Decompression fails         
                             RemoteTraceback:                                   
                             """                                                
                             Traceback (most recent call last):                 
                               File                                             
                             "/home/roestlab/anaconda3/envs/ms2rescore_env/lib/p
                             ython3.9/multiprocessing/pool.py", line 125, in    
                             worker                                             
                                 result = (True, func(*args, **kwds))           
                               File                                             
                             "/home/roestlab/anaconda3/envs/ms2rescore_env/lib/p
                             ython3.9/site-packages/ms2pip/core.py", line 911,  
                             in _process_spectra                                
                                 for spectrum in read_spectrum_file(spec_file): 
                               File                                             
                             "/home/roestlab/anaconda3/envs/ms2rescore_env/lib/p
                             ython3.9/site-packages/ms2pip/spectrum_input.py",  
                             line 33, in read_spectrum_file                     
                                 spectra = get_ms2_spectra(str(spectrum_file))  
                             Exception: Decompression fails                     
                             """                                                
                                                                                
                             The above exception was the direct cause of the    
                             following exception:                               
                                                                                
                             ╭─────── Traceback (most recent call last) ───────╮
                             │ /home/roestlab/anaconda3/envs/ms2rescore_env/li │
                             │ b/python3.9/site-packages/ms2rescore/__main__.p │
                             │ y:237 in main                                   │
                             │                                                 │
                             │   234 │   │   │   profiled_rescore = profile(re │
                             │   235 │   │   │   profiled_rescore(configuratio │
                             │   236 │   │   else:                             │
                             │ ❱ 237 │   │   │   rescore(configuration=config) │
                             │   238 │   except Exception as e:                │
                             │   239 │   │   LOGGER.exception(e)               │
                             │   240 │   │   sys.exit(1)                       │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/ms2rescore_env/li │
                             │ b/python3.9/site-packages/ms2rescore/core.py:79 │
                             │  in rescore                                     │
                             │                                                 │
                             │    76 │   │   conf = config.copy()              │
                             │    77 │   │   conf.update(fgen_config)          │
                             │    78 │   │   fgen = FEATURE_GENERATORS[fgen_na │
                             │ ❱  79 │   │   fgen.add_features(psm_list)       │
                             │    80 │   │   logger.debug(f"Adding features fr │
                             │    81 │   │   feature_names[fgen_name] = set(fg │
                             │    82                                           │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/ms2rescore_env/li │
                             │ b/python3.9/site-packages/ms2rescore/feature_ge │
                             │ nerators/ms2pip.py:194 in add_features          │
                             │                                                 │
                             │   191 │   │   │   │   spectrum_filename = infer │
                             │   192 │   │   │   │   logger.debug(f"Using spec │
                             │   193 │   │   │   │   try:                      │
                             │ ❱ 194 │   │   │   │   │   ms2pip_results = corr │
                             │   195 │   │   │   │   │   │   psms=psm_list_run │
                             │   196 │   │   │   │   │   │   spectrum_file=str │
                             │   197 │   │   │   │   │   │   spectrum_id_patte │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/ms2rescore_env/li │
                             │ b/python3.9/site-packages/ms2pip/core.py:283 in │
                             │ correlate                                       │
                             │                                                 │
                             │    280 │   │   │   processes=processes,         │
                             │    281 │   │   )                                │
                             │    282 │   │   logger.info("Processing spectra  │
                             │ ❱  283 │   │   results = ms2pip_parallelized.pr │
                             │        spectrum_id_pattern)                     │
                             │    284 │                                        │
                             │    285 │   # Correlations also requested        │
                             │    286 │   if compute_correlations:             │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/ms2rescore_env/li │
                             │ b/python3.9/site-packages/ms2pip/core.py:706 in │
                             │ process_spectra                                 │
                             │                                                 │
                             │    703 │   │   │   spectrum_id_pattern,         │
                             │    704 │   │   │   annotations_only,            │
                             │    705 │   │   )                                │
                             │ ❱  706 │   │   results = self._execute_in_pool( │
                             │    707 │   │                                    │
                             │    708 │   │   # Validate number of results     │
                             │    709 │   │   if not results:                  │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/ms2rescore_env/li │
                             │ b/python3.9/site-packages/ms2pip/core.py:640 in │
                             │ _execute_in_pool                                │
                             │                                                 │
                             │    637 │   │   │   #         show_speed=False,  │
                             │    638 │   │   │   #     )                      │
                             │    639 │   │   │   # ]                          │
                             │ ❱  640 │   │   │   results = [r.get() for r in  │
                             │    641 │   │                                    │
                             │    642 │   │   # Sort results by input order    │
                             │    643 │   │   results = list(                  │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/ms2rescore_env/li │
                             │ b/python3.9/site-packages/ms2pip/core.py:640 in │
                             │ <listcomp>                                      │
                             │                                                 │
                             │    637 │   │   │   #         show_speed=False,  │
                             │    638 │   │   │   #     )                      │
                             │    639 │   │   │   # ]                          │
                             │ ❱  640 │   │   │   results = [r.get() for r in  │
                             │    641 │   │                                    │
                             │    642 │   │   # Sort results by input order    │
                             │    643 │   │   results = list(                  │
                             │                                                 │
                             │ /home/roestlab/anaconda3/envs/ms2rescore_env/li │
                             │ b/python3.9/multiprocessing/pool.py:771 in get  │
                             │                                                 │
                             │   768 │   │   if self._success:                 │
                             │   769 │   │   │   return self._value            │
                             │   770 │   │   else:                             │
                             │ ❱ 771 │   │   │   raise self._value             │
                             │   772 │                                         │
                             │   773 │   def _set(self, i, obj):               │
                             │   774 │   │   self._success, self._value = obj  │
                             ╰─────────────────────────────────────────────────╯
                             Exception: Decompression fails

[jspaezp]

Hey @singjc!

Well ... yes and no ... #132 would be the branch with the removed dependency... BUT I am sure it is non-backwards compatible with ms2rescore. I was planning on submitting a PR to ms2rescore once we got this merged as a pre-release.

FYI @RalfG @wfondrie

Some API changes affect here:
https://github.com/compomics/ms2rescore/blob/8a094aa1366aa51f4ab4e45ebd0c294b4495c3c1/ms2rescore/rescoring_engines/mokapot.py#L171-L184

Some column renaming affects here:
https://github.com/compomics/ms2rescore/blob/main/ms2rescore/report/charts.py

[jspaezp]

Looking into the ms2rescore code a bit more ...
The biggest thing is that the confidence_results.confidence_estimates api no longer exists and now is replace by confidence_results.confidence_writers[x].read() ... which I dont totally like.... it think its worth re-implementing that API.

[jspaezp]

taking a deeper look at this ... I am happy to take suggestions on API design ...

These are representative snippets of code within ms2rescore that use the mokapot api.

    try:
        confidence_results, models = brew(
            lin_psm_data, model=PercolatorModel(train_fdr=train_fdr), rng=8, **kwargs
        )
    except RuntimeError as e:
        raise RescoringError("Mokapot could not be run. Please check the input data.") from e

    add_psm_confidence(psm_list, confidence_results)
    add_peptide_confidence(psm_list, confidence_results)

    mokapot_values_targets = (
        confidence_results.confidence_estimates["psms"].set_index("index").sort_index()[keys]
    )
    mokapot_values_decoys = (
        confidence_results.decoy_confidence_estimates["psms"].set_index("index").sort_index()[keys]
    )

...

    q = np.full((len(psm_list), 3), np.nan)
    q[mokapot_values_targets.index] = mokapot_values_targets.values
    q[mokapot_values_decoys.index] = mokapot_values_decoys.values

    # Add Mokapot results to PSMList
    psm_list["score"] = q[:, 0]
    psm_list["qvalue"] = q[:, 1]
    psm_list["pep"] = q[:, 2]

    # Reset ranks to match new scores
    psm_list.set_ranks(lower_score_better=False)

now ....

there are two main issues

1. The brew api signature is no longer brew(Dataset, ...) -> tuple[confidence, list[models]], now is brew(list[Dataset], ...) -> tuple[list[models], list[scores]], which is then fed to mokapot.assign_confidence, which has signature mokapot.assign_confidence(list[Dataset), Optional[List[Scores]]) -> list[Confidence].

which means that ....

confidence_results, models = brew(
    lin_psm_data, model=PercolatorModel(train_fdr=train_fdr), rng=8, **kwargs
)

becomes

data = [lin_psm_data]
models, scores = brew(
    lin_psm_data, model=PercolatorModel(train_fdr=train_fdr), rng=8, **kwargs
)
confidence_results = mokapot.assign_confidence(data, ...)[0]
# the default scores are passed bc they internally get assigned to the data.
# Note the extraction of the first element here.

2. Mokapot no longer preserves the index (nmerically) of the dataframe ... so the current usage would not really assure the order is the same (q[mokapot_values_decoys.index] = mokapot_values_decoys.values; psm_list["score"] = q[:, 0] would not match in order ... ). The safe way of doing it would be to make a join on whatever was defined as spectrum_columns + peptide + id. (after getting the data with confidence_results[0].psms ... also note the targets/decoys will always be together as long as assign_confidence was called with write_decoys=True)

#137