
DIA-NN 2.2.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on May 29 2025 15:05:00
Current date and time: Wed Apr 22 04:59:56 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.2.0/diann-linux --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d --fasta /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta --out /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.2.0/report.tsv --threads 32 --missed-cleavages 2 --min-pep-len 7 --max-pep-len 30 --mass-acc 20 --mass-acc-ms1 20 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 2 --max-pr-charge 4 --min-pr-mz 400 --max-pr-mz 1200 --min-fr-mz 200 --max-fr-mz 2000 --unimod4 --var-mod UniMod:35,15.994915,M --gen-spec-lib --fasta-search 

Thread number set to 32
Maximum number of missed cleavages set to 2
Min peptide length set to 7
Max peptide length set to 30
Output will be filtered at 0.01 FDR
Output will be filtered at 0.01 protein-level FDR
Min precursor charge set to 2
Max precursor charge set to 4
Min precursor m/z set to 400
Max precursor m/z set to 1200
Min fragment m/z set to 200
Max fragment m/z set to 2000
Cysteine carbamidomethylation enabled as a fixed modification
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
A spectral library will be generated
DIA-NN will carry out FASTA digest for in silico lib generation
Mass accuracy will be fixed to 2e-05 (MS2) and 2e-05 (MS1)
WARNING: FASTA digest mode enabled and raw data are provided, turning on deep learning spectra/RT/IM prediction
WARNING: incorrect settings, the in silico-predicted library must be generated in a separate pipeline step and then used to process the raw data, now without activating FASTA digest
WARNING: peptidoform scoring enabled because variable modifications have been declared; to disable, use --no-peptidoforms
The following variable modifications will be localised: UniMod:35 

6 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:06] Processing FASTA
[0:09] Assembling elution groups
[0:17] 8103720 precursors generated
[0:17] Protein names missing for some isoforms
[0:17] Gene names missing for some isoforms
[0:17] Library contains 31680 proteins, and 0 genes
[0:24] [0:38] [6:02] [6:44] [6:48] [6:53] Saving the library to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.2.0/report-lib.predicted.speclib
[7:00] Initialising library
[7:18] Loading spectral library /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.2.0/report-lib.predicted.speclib
[7:21] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[7:23] Spectral library loaded: 31832 protein isoforms, 43199 protein groups and 8103720 precursors in 3825450 elution groups.
[7:23] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[7:23] Annotating library proteins with information from the FASTA database
[7:23] Protein names missing for some isoforms
[7:23] Gene names missing for some isoforms
[7:23] Library contains 31680 proteins, and 0 genes
[7:31] Initialising library
WARNING: it is strongly recommended to enable MBR when analysing with a large library, if this is a quantitative analysis

[7:48] File #1/6
[7:48] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d
WARNING: for the vast majority of timsTOF datasets it is better to manually fix both the MS1 and MS2 mass accuracies to 15 ppm
[8:31] Pre-processing...
[8:36] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[8:37] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[10:08] RT window set to 2.57746
[10:08] IM window set to 0.0429506
[10:08] Peak width: 4.04
[10:08] Scan window radius set to 8
[10:08] Recommended MS1 mass accuracy setting: 11 ppm
[10:48] Searching decoys
[19:06] Main search
[35:17] Removing low confidence identifications
[35:42] Removing interfering precursors
[35:50] Training neural networks on 154101 target and 97200 decoy PSMs
[36:23] Training neural networks on 154101 target and 91933 decoy PSMs
[36:52] Number of IDs at 0.01 FDR: 94353
[36:52] Precursors at 1% peptidoform FDR: 89732
[36:53] Calculating protein q-values
[36:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[36:54] Quantification
[36:58] Precursors with scored PTMs at 1% FDR: 758 out of 970 considered
[36:58] Precursors with all scored PTM sites unoccupied at 1% FDR: 88974
[36:58] Precursors with PTMs localised (when required) with > 90% confidence: 736 out of 758
[36:59] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d.quant

[36:59] File #2/6
[36:59] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d
[37:41] Pre-processing...
[37:45] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[37:46] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[39:31] RT window set to 2.66171
[39:31] IM window set to 0.0437581
[39:31] Recommended MS1 mass accuracy setting: 11 ppm
[40:11] Searching decoys
[48:25] Main search
[64:32] Removing low confidence identifications
[64:55] Removing interfering precursors
[65:02] Training neural networks on 158953 target and 100626 decoy PSMs
[65:33] Training neural networks on 158953 target and 95243 decoy PSMs
[65:56] Number of IDs at 0.01 FDR: 97381
[65:57] Precursors at 1% peptidoform FDR: 92397
[65:58] Calculating protein q-values
[65:59] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[65:59] Quantification
[66:01] Precursors with scored PTMs at 1% FDR: 693 out of 900 considered
[66:01] Precursors with all scored PTM sites unoccupied at 1% FDR: 91704
[66:01] Precursors with PTMs localised (when required) with > 90% confidence: 667 out of 693
[66:03] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d.quant

[66:03] File #3/6
[66:03] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d
[66:43] Pre-processing...
[66:47] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[66:48] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[68:29] RT window set to 2.65095
[68:29] IM window set to 0.042687
[68:30] Recommended MS1 mass accuracy setting: 12 ppm
[69:08] Searching decoys
[77:13] Main search
[93:12] Removing low confidence identifications
[93:36] Removing interfering precursors
[93:43] Training neural networks on 159240 target and 101519 decoy PSMs
[94:11] Training neural networks on 159240 target and 94910 decoy PSMs
[94:35] Number of IDs at 0.01 FDR: 98449
[94:36] Precursors at 1% peptidoform FDR: 93386
[94:37] Calculating protein q-values
[94:37] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[94:37] Quantification
[94:40] Precursors with scored PTMs at 1% FDR: 661 out of 865 considered
[94:40] Precursors with all scored PTM sites unoccupied at 1% FDR: 92725
[94:40] Precursors with PTMs localised (when required) with > 90% confidence: 635 out of 661
[94:41] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d.quant

[94:41] File #4/6
[94:41] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d
[95:20] Pre-processing...
[95:24] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[95:25] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[97:02] RT window set to 2.66
[97:02] IM window set to 0.0430655
[97:03] Recommended MS1 mass accuracy setting: 11 ppm
[97:40] Searching decoys
[105:35] Main search
[121:14] Removing low confidence identifications
[121:37] Removing interfering precursors
[121:44] Training neural networks on 154658 target and 98845 decoy PSMs
[122:15] Training neural networks on 154658 target and 93403 decoy PSMs
[122:41] Number of IDs at 0.01 FDR: 95333
[122:41] Precursors at 1% peptidoform FDR: 90503
[122:42] Calculating protein q-values
[122:43] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[122:43] Quantification
[122:45] Precursors with scored PTMs at 1% FDR: 649 out of 879 considered
[122:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 89854
[122:45] Precursors with PTMs localised (when required) with > 90% confidence: 628 out of 649
[122:47] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d.quant

[122:47] File #5/6
[122:47] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d
[123:26] Pre-processing...
[123:31] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[123:32] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[125:08] RT window set to 2.78001
[125:08] IM window set to 0.0428329
[125:09] Recommended MS1 mass accuracy setting: 11 ppm
[125:47] Searching decoys
[133:52] Main search
[149:49] Removing low confidence identifications
[150:13] Removing interfering precursors
[150:21] Training neural networks on 156217 target and 100615 decoy PSMs
[150:53] Training neural networks on 156217 target and 94741 decoy PSMs
[151:18] Number of IDs at 0.01 FDR: 96428
[151:19] Precursors at 1% peptidoform FDR: 91815
[151:20] Calculating protein q-values
[151:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[151:20] Quantification
[151:22] Precursors with scored PTMs at 1% FDR: 667 out of 897 considered
[151:22] Precursors with all scored PTM sites unoccupied at 1% FDR: 91148
[151:22] Precursors with PTMs localised (when required) with > 90% confidence: 649 out of 667
[151:24] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d.quant

[151:24] File #6/6
[151:24] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d
[152:03] Pre-processing...
[152:07] 4348 MS1 and 104343 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[152:08] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[153:46] RT window set to 2.66806
[153:46] IM window set to 0.0422791
[153:47] Recommended MS1 mass accuracy setting: 11 ppm
[154:23] Searching decoys
[162:17] Main search
[177:48] Removing low confidence identifications
[178:11] Removing interfering precursors
[178:20] Training neural networks on 157850 target and 101895 decoy PSMs
[178:53] Training neural networks on 157850 target and 95704 decoy PSMs
[179:17] Number of IDs at 0.01 FDR: 97435
[179:17] Precursors at 1% peptidoform FDR: 92344
[179:18] Calculating protein q-values
[179:19] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[179:19] Quantification
[179:21] Precursors with scored PTMs at 1% FDR: 698 out of 875 considered
[179:21] Precursors with all scored PTM sites unoccupied at 1% FDR: 91646
[179:21] Precursors with PTMs localised (when required) with > 90% confidence: 675 out of 698
[179:23] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d.quant

[179:23] Cross-run analysis
[179:23] Reading quantification information: 6 files
[179:42] Quantifying peptides
[180:46] Quantification parameters: 0.353021, 0.00137579, 0.00335456, 0.116176, 0.146675, 0.133185, 0.207151, 0.014773, 0.02098, 0.132705, 0.0916366, 0.105297, 0.16739, 0.0775397, 0.0815663, 0.0128892
[181:04] Assembling protein groups
[181:06] Quantifying proteins
[181:06] Calculating q-values for protein and gene groups
[181:08] Calculating global q-values for protein and gene groups
[181:08] Protein groups with global q-value <= 0.01: 11540
[181:11] Compressed report saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.2.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[181:11] Stats report saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.2.0/report.stats.tsv
[181:11] Generating spectral library:
[181:13] 119075 target and 1140 decoy precursors saved
WARNING: 948 precursors without any fragments annotated were skipped
[181:13] Spectral library saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.2.0/report-lib.parquet

