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vdemichev / DiaNN

DIA-NN - a universal automated software suite for DIA proteomics data analysis.
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DiaNN fails to read indexed and non-indexed mzML files #1013

Closed onurserce closed 4 months ago

onurserce commented 5 months ago

Dear @vdemichev,

First of all, thank you very much for the great software! I have used DiaNN before with its GUI on a Windows machine. However, I need to set up a linux based pipeline now and am running into some issues with it.

I have successfully installed mono on an HPC (SUSE linux) and I am able to convert .raw files (acquired on an Astral machine) to mzML using ThermoRawFileParser (version 1.4.3) with the following command: mono ThermoRawFileParser/ThermoRawFileParser.exe -d=$HOME/data/test_data -f=2 -m=1, where -f=2 is for indexed mzML (I have also tried non-indexed mzML -f=1) and -m=1 tells the program to give the metadata as txt format (https://github.com/compomics/ThermoRawFileParser#usage)

Output is:

``` 2024-05-11 23:42:06 INFO The folder contains 2 RAW files 2024-05-11 23:42:06 INFO Started parsing /u/onse/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.raw 2024-05-11 23:42:29 INFO Processing 43799 MS scans 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2024-05-11 23:50:14 INFO Finished parsing /u/onse/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.raw 2024-05-11 23:50:14 INFO Started parsing /u/onse/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.raw 2024-05-11 23:50:55 INFO Processing 83442 MS scans 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2024-05-12 00:04:39 INFO Finished parsing /u/onse/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.raw 2024-05-12 00:04:39 INFO Processing completed 0 errors, 0 warnings ```

So far, everything works as expected. However, if I now I try to quant the outputted .mzML files using DiaNN with the following command(s):

temp_dir="$HOME"/temp
fasta_file="$HOME"/data/UP000000589_10090.fasta

`diann-1.8.1 --f "~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML" --f "~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML" --cut "K*,R*,!*P" --fasta "$fasta_file" --fasta-search --gen-spec-lib --max-pep-len 30 --max-pr-charge 6 --min-pep-len 6 --met-excision --min-pr-mz 300 --missed-cleavages 1 --out test_output --pg-level 1 --predictor --reanalyse --relaxed-prot-inf --report-lib-info --smart-profiling --temp "$temp_dir" --threads 32 --verbose 4 --var-mods 1`

I get the following

output:

``` DIA-NN 1.8.1 (Data-Independent Acquisition by Neural Networks) Compiled on Apr 15 2022 08:45:18 Current date and time: Sat May 11 23:42:18 2024 Logical CPU cores: 144 In silico digest will involve cuts at K*,R* But excluding cuts at *P Library-free search enabled A spectral library will be generated Max peptide length set to 30 Max precursor charge set to 6 Min peptide length set to 6 N-terminal methionine excision enabled Min precursor m/z set to 300 Maximum number of missed cleavages set to 1 Implicit protein grouping: protein names; this determines which peptides are considered 'proteotypic' and thus affects protein FDR calculation Deep learning will be used to generate a new in silico spectral library from peptides provided A spectral library will be created from the DIA runs and used to reanalyse them; .quant files will only be saved to disk during the first step Highly heuristic protein grouping will be used, to reduce the number of protein groups obtained; this mode is recommended for benchmarking protein I D numbers; use with caution for anything else When generating a spectral library, in silico predicted spectra will be retained if deemed more reliable than experimental ones Thread number set to 32 Maximum number of variable modifications set to 1 DIA-NN will optimise the mass accuracy automatically using the first run in the experiment. This is useful primarily for quick initial analyses, when it is not yet known which mass accuracy setting works best for a particular acquisition scheme. Exclusion of fragments shared between heavy and light peptides from quantification is not supported in FASTA digest mode - disabled; to enable, generate an in silico predicted spectral library and analyse with this library 2 files will be processed [0:00] Loading FASTA /u/onse/data/UP000000589_10090.fasta [0:02] Processing FASTA [0:08] Assembling elution groups [0:13] 4072972 precursors generated [0:13] Gene names missing for some isoforms [0:13] Library contains 21675 proteins, and 21364 genes [0:15] Encoding peptides for spectra and RTs prediction [0:22] Predicting spectra and IMs Predictions generated: 4864 9728 ... ... Truncated for readability ... ... 1263040 1267904 [4:51] Decoding predicted spectra and IMs [4:59] Decoding RTs [5:01] Saving the library to lib.predicted.speclib [5:04] Initialising library [5:06] First pass: generating a spectral library from DIA data [5:06] File #1/2 [5:06] Loading run ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML No MS2 spectra: aborting ERROR: cannot load the file, skipping [5:06] 0 library precursors are potentially detectable [5:06] Processing [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Recalibrating with mass accuracy 0.0001, 3e-05 (MS2, MS1) [5:06] Processing [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Using MS1 mass accuracy: 20 ppm [5:06] Using mass accuracy: 20 ppm [5:06] Processing [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Restoring classifier and weights to 1 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Removing low confidence identifications [5:06] Removing interfering precursors [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Too few confident identifications, neural networks will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Calculating protein q-values [5:06] Number of proteins identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [5:06] Quantification [5:06] Quantification information saved to /u/onse/temp/~_data_test_data_20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0_mzML.quant. [5:06] File #2/2 [5:06] Loading run ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML No MS2 spectra: aborting ERROR: cannot load the file, skipping [5:06] 0 library precursors are potentially detectable [5:06] Processing [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Recalibrating with mass accuracy 0.0001, 3e-05 (MS2, MS1) [5:06] Processing [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Using MS1 mass accuracy: 20 ppm [5:06] Using mass accuracy: 20 ppm [5:06] Processing [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Restoring classifier and weights to 1 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 [5:06] Precursor search [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Removing low confidence identifications [5:06] Removing interfering precursors [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:06] Too few confident identifications, neural networks will not be used [5:06] Calculating q-values [5:06] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:06] Calibrating retention times [5:06] Calculating protein q-values [5:06] Number of proteins identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [5:06] Quantification [5:06] Quantification information saved to /u/onse/temp/~_data_test_data_20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0_mzML.quant. ERROR: DIA-NN tried but failed to load the following files: ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML, ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML [5:06] Cross-run analysis [5:06] Reading quantification information: 2 files [5:06] Quantifying peptides WARNING: not enough peptides for normalisation [5:07] Assembling protein groups [5:08] Quantifying proteins [5:08] Calculating q-values for protein and gene groups [5:08] Calculating global q-values for protein and gene groups [5:08] Writing report [5:08] Report saved to test_output-first-pass.tsv. [5:08] Stats report saved to test_output-first-pass.stats.tsv [5:08] Generating spectral library: [5:09] 0 precursors passing the FDR threshold are to be extracted [5:09] Saving spectral library to lib.tsv [5:09] 0 precursors saved [5:09] Loading the generated library and saving it in the .speclib format [5:09] Loading spectral library lib.tsv [5:09] Spectral library loaded: 0 protein isoforms, 0 protein groups and 0 precursors in 1 elution groups. [5:09] Loading protein annotations from FASTA /u/onse/data/UP000000589_10090.fasta [5:09] Library contains 0 proteins, and 0 genes [5:09] Saving the library to lib.tsv.speclib [5:12] Second pass: using the newly created spectral library to reanalyse the data [5:12] File #1/2 [5:12] Loading run ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML No MS2 spectra: aborting ERROR: cannot load the file, skipping [5:12] 0 library precursors are potentially detectable [5:12] Processing [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Recalibrating with mass accuracy 0.0001, 3e-05 (MS2, MS1) [5:12] Processing [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Using MS1 mass accuracy: 20 ppm [5:12] Using mass accuracy: 20 ppm [5:12] Processing [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Restoring classifier and weights to 1 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Removing low confidence identifications [5:12] Removing interfering precursors [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Too few confident identifications, neural networks will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Calculating protein q-values [5:12] Number of proteins identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [5:12] Quantification [5:12] File #2/2 [5:12] Loading run ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML ERROR: Failure reading input file ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML No MS2 spectra: aborting ERROR: cannot load the file, skipping [5:12] 0 library precursors are potentially detectable [5:12] Processing [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Recalibrating with mass accuracy 0.0001, 3e-05 (MS2, MS1) [5:12] Processing [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Using MS1 mass accuracy: 20 ppm [5:12] Using mass accuracy: 20 ppm [5:12] Processing [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Restoring classifier and weights to 1 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 0 0 0 0 |***| 0 0 0 0 0 0 [5:12] Precursor search [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Removing low confidence identifications [5:12] Removing interfering precursors [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Optimising weights Ids at 10% FDR using TC scoring: 0 Ids at 10% FDR using TC selection: 0 WARNING: too few training precursors, classifier will not be used [5:12] Too few confident identifications, neural networks will not be used [5:12] Calculating q-values [5:12] Number of IDs at 50%, 5%, 1%, 0.1% FDR: 0, 0, 0, 0 [5:12] Calibrating retention times [5:12] Calculating protein q-values [5:12] Number of proteins identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [5:12] Quantification ERROR: DIA-NN tried but failed to load the following files: ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_1000_shape_0.mzML, ~/data/test_data/20240504_OA4_33min_EdRo_SA_ER586_Onur_Input_Experiment_slideB_50_shape_0.mzML [5:12] Cross-run analysis [5:12] Reading quantification information: 2 files [5:12] Quantifying peptides WARNING: not enough peptides for normalisation [5:12] Quantifying proteins [5:12] Calculating q-values for protein and gene groups [5:12] Calculating global q-values for protein and gene groups [5:12] Writing report [5:13] Report saved to test_output. [5:13] Stats report saved to test_output.stats.tsv [5:13] Log saved to test_output.log.txt Finished ```

As the output suggests, DiaNN fails to read the .mzML files. Unfortunately, I am not able to install Wine on the HPC, as it comes with a bunch of dependencies and I lack sudo permissions. I am also not sure if that would solve the problem, since the Thermo Raw File Reader supposedly won't work on linux?

Any input/leads for solving the issue is greatly appreciated. I will also happily share any file you may need for debugging purposes.

Best regards, Onur

onurserce commented 5 months ago

Update: It looks like these .mzML files cannot be read by DiaNN on a Windows computer as well (MS File Reader 3.0 SP3 installed).

Any leads towards a solution is highly appreciated.

Capture_diann

vdemichev commented 5 months ago

Hi Onur,

.mzML reading does not depend on Thermo .raw, and should work on both Windows and Linux. Since it does not work on Windows too here seems to indicate that there's some incompatibility between those mzMLs and DIA-NN. In general, DIA-NN should work fine with mzMLs produced by MSConvert, with peak picking and index, without compression. Does msconvert work on Linux, maybe under Wine? With ThermoRawFileParser, try to disable compression using -z?

Best, Vadim

onurserce commented 5 months ago

Hi Vadim,

Thanks for the input.

I have not used the compression option with the ThermoRawFileParser (hence the -z flag missing). The exact command is above.

Also, as I said, I am unfortunately not allowed to install Wine on the HPC I am using. Perhaps this is for a good reason, as my antivirus software detected malware during brew installation of Wine on my MacBook while I was testing it.

I didn't know about MSConvert. If MSConvert works under mono in Linux, that'd be great. I will give it a try when I find some time. Another solution would be to reshape the .mzML file to meet the expectations of DiaNN but I don't know what exact structure is expected to perform this conversion.

I will write under this thread about my results when I find some time to try MSConvert. In the meanwhile, feel free to close this issue if you want to.

Best, Onur

lyons89 commented 5 months ago

I came to ask for help with the same problem Onur has. I tested out both MSconvert and ThermoRawFileParser on the desktop and only had success with MSconvert. I wasn't sure if there was a specific combination of options for ThermoRawFileParser to get it to work with DIANN. I'll try to find an MSconvert option that I can integrate into my HPC pipeline.

Let me know @onurserce if you find something that works! I too don't have sudo privileges.

onurserce commented 5 months ago

Hi @lyons89,

Thanks for the contribution. Good to know that MSConvert outputs the right format. Did you try the MSConvert on a Linux machine or Windows? And what options are you looking for?

Best, Onur

lyons89 commented 5 months ago

Hey @onurserce,

I did MSConvert on windows using the GUI. I did the same options that Vadim posted on the readme page, Binary encoding precision: 32 bit, and only checked Write Index. Then for filters added Peak Picking and didn't mess with the defaults. I have thermorawfileparser installaed on the HPC but also found the output wasn't compatible with DIANN. So right now I'm converting to mzML using windows MSConvert, then uploading the HPC to do the search. It would be faster to be able to upload the raw file, and then convert to mzML and pipe to DIANN on the HPC. Still, if i can't find thermorawfileparser options that work with DIANN I'll have to find an MSConvert option for the HPC, and then get someone with admin rights to install it for me.

best, Scott

vdemichev commented 4 months ago

I have not used the compression option with the ThermoRawFileParser (hence the -z flag missing).

Then this is likely the reason for the problem. No -z flag means compression used, -z flag turns it off. So I would suggest to add -z

onurserce commented 4 months ago

Oh wow, can't believe I have missed that... Thank you @vdemichev, this actually solved the problem!

I am closing this issue.

punching-samuel commented 4 months ago

Oh wow, I can't believe I missed this... Thanks @vdemichev, that actually solved the problem! > > Closing this issue.

Hi～ Have you solved this problem? What if the '--noZlibCompression' option of ThermoRawFileParser is selected?

punching-samuel commented 4 months ago

I choose the '--noZlibCompression' option and get new .mzMl files. However the same result after running these new files. 截屏2024-06-20 14 42 59

Best wishes! Yang

Oh wow, can't believe I have missed that... Thank you @vdemichev, this actually solved the problem!

I am closing this issue.

onurserce commented 4 months ago

Hi @punching-samuel,

I have used ThermoRawFileParser v1.4.3 with the following command and the resulting files did work well with DiaNN. mono ThermoRawFileParser/ThermoRawFileParser.exe -d=$HOME/data/test_data -f=2 -m=1 -z

I am assuming that the results may depend on the acquisition device as well (which in my case was Orbitrap Astral).

Hope this helps!