
DIA-NN 2.3.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Sep 26 2025 02:56:25
Current date and time: Wed Apr 22 01:21:36 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.3.0/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_v2.3.0/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] [0:37] [6:24] [7:08] [7:11] [7:14] Saving the library to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.3.0/report-lib.predicted.speclib
[7:23] Initialising library
[7:38] Loading spectral library /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.3.0/report-lib.predicted.speclib
[7:40] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[7:42] Spectral library loaded: 31832 protein isoforms, 43199 protein groups and 8103720 precursors in 3825450 elution groups.
[7:42] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[7:42] Annotating library proteins with information from the FASTA database
[7:42] Protein names missing for some isoforms
[7:42] Gene names missing for some isoforms
[7:42] Library contains 31680 proteins, and 0 genes
[7:48] Initialising library
WARNING: it is strongly recommended to enable MBR when analysing with a large library, if this is a quantitative analysis

[8:02] File #1/6
[8:02] 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 10-15 ppm
[9:04] Pre-processing...
[9:08] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[9:09] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[10:29] RT window set to 2.5865
[10:29] IM window set to 0.0424929
[10:29] Peak width: 4.08
[10:29] Scan window radius set to 8
[10:29] Recommended MS1 mass accuracy setting: 11 ppm
[11:04] Searching decoys
[18:56] Main search
[34:27] Removing low confidence identifications
[34:49] Removing interfering precursors
[34:56] Training neural networks on 153872 target and 97020 decoy PSMs
[35:28] Training neural networks on 153872 target and 92038 decoy PSMs
[35:53] IDs at 0.01 FDR: 94462
[35:54] Precursors at 1% peptidoform FDR: 89805
[35:55] Number of IDs at 0.01 FDR: 97566
[35:55] Calculating protein q-values
[35:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[35:56] Quantification
[35:59] Precursors with scored PTMs at 1% FDR: 725 out of 1047 considered
[35:59] Precursors with all scored PTM sites unoccupied at 1% FDR: 89717
[35:59] Precursors with PTMs localised (when required) with > 90% confidence: 701 out of 725
[36:00] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d.quant

[36:00] File #2/6
[36:00] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d
[36:58] Pre-processing...
[37:02] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[37:03] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[38:37] RT window set to 2.62318
[38:37] IM window set to 0.0429588
[38:37] Recommended MS1 mass accuracy setting: 11 ppm
[39:15] Searching decoys
[46:59] Main search
[62:20] Removing low confidence identifications
[62:43] Removing interfering precursors
[62:50] Training neural networks on 157835 target and 98714 decoy PSMs
[63:21] Training neural networks on 157835 target and 93599 decoy PSMs
[63:46] IDs at 0.01 FDR: 97153
[63:46] Precursors at 1% peptidoform FDR: 92318
[63:48] Number of IDs at 0.01 FDR: 100345
[63:48] Calculating protein q-values
[63:48] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[63:48] Quantification
[63:51] Precursors with scored PTMs at 1% FDR: 812 out of 1123 considered
[63:51] Precursors with all scored PTM sites unoccupied at 1% FDR: 92161
[63:51] Precursors with PTMs localised (when required) with > 90% confidence: 789 out of 812
[63:53] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d.quant

[63:53] File #3/6
[63:53] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d
[64:54] Pre-processing...
[64:58] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[64:59] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[66:34] RT window set to 2.6339
[66:34] IM window set to 0.0414515
[66:34] Recommended MS1 mass accuracy setting: 12 ppm
[67:11] Searching decoys
[74:58] Main search
[90:23] Removing low confidence identifications
[90:46] Removing interfering precursors
[90:54] Training neural networks on 160773 target and 101868 decoy PSMs
[91:27] Training neural networks on 160773 target and 96217 decoy PSMs
[91:52] IDs at 0.01 FDR: 97484
[91:52] Precursors at 1% peptidoform FDR: 92945
[91:54] Number of IDs at 0.01 FDR: 100647
[91:54] Calculating protein q-values
[91:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[91:54] Quantification
[91:57] Precursors with scored PTMs at 1% FDR: 673 out of 1012 considered
[91:57] Precursors with all scored PTM sites unoccupied at 1% FDR: 92991
[91:57] Precursors with PTMs localised (when required) with > 90% confidence: 646 out of 673
[91:59] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d.quant

[91:59] File #4/6
[91:59] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d
[92:57] Pre-processing...
[93:02] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[93:03] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[94:35] RT window set to 2.65512
[94:35] IM window set to 0.041519
[94:35] Recommended MS1 mass accuracy setting: 11 ppm
[95:12] Searching decoys
[102:53] Main search
[118:01] Removing low confidence identifications
[118:23] Removing interfering precursors
[118:31] Training neural networks on 154808 target and 97811 decoy PSMs
[119:04] Training neural networks on 154808 target and 92498 decoy PSMs
[119:29] IDs at 0.01 FDR: 94980
[119:30] Precursors at 1% peptidoform FDR: 90360
[119:31] Number of IDs at 0.01 FDR: 98194
[119:31] Calculating protein q-values
[119:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[119:32] Quantification
[119:35] Precursors with scored PTMs at 1% FDR: 721 out of 1034 considered
[119:35] Precursors with all scored PTM sites unoccupied at 1% FDR: 90333
[119:35] Precursors with PTMs localised (when required) with > 90% confidence: 695 out of 721
[119:37] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d.quant

[119:37] File #5/6
[119:37] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d
[120:36] Pre-processing...
[120:41] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[120:41] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[122:14] RT window set to 2.56051
[122:14] IM window set to 0.0429971
[122:14] Recommended MS1 mass accuracy setting: 11 ppm
[122:49] Searching decoys
[130:32] Main search
[145:50] Removing low confidence identifications
[146:12] Removing interfering precursors
[146:19] Training neural networks on 154708 target and 98122 decoy PSMs
[146:52] Training neural networks on 154708 target and 92903 decoy PSMs
[147:16] IDs at 0.01 FDR: 96427
[147:16] Precursors at 1% peptidoform FDR: 92005
[147:18] Number of IDs at 0.01 FDR: 99624
[147:18] Calculating protein q-values
[147:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[147:18] Quantification
[147:21] Precursors with scored PTMs at 1% FDR: 640 out of 1020 considered
[147:21] Precursors with all scored PTM sites unoccupied at 1% FDR: 92067
[147:21] Precursors with PTMs localised (when required) with > 90% confidence: 626 out of 640
[147:23] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d.quant

[147:23] File #6/6
[147:23] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d
[148:23] Pre-processing...
[148:27] 4348 MS1 and 104343 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[148:28] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[150:00] RT window set to 2.73608
[150:00] IM window set to 0.0431467
[150:00] Recommended MS1 mass accuracy setting: 11 ppm
[150:36] Searching decoys
[158:23] Main search
[173:51] Removing low confidence identifications
[174:14] Removing interfering precursors
[174:21] Training neural networks on 159301 target and 101241 decoy PSMs
[174:52] Training neural networks on 159301 target and 95873 decoy PSMs
[175:18] IDs at 0.01 FDR: 97517
[175:19] Precursors at 1% peptidoform FDR: 92415
[175:20] Number of IDs at 0.01 FDR: 100432
[175:20] Calculating protein q-values
[175:21] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[175:21] Quantification
[175:24] Precursors with scored PTMs at 1% FDR: 636 out of 972 considered
[175:24] Precursors with all scored PTM sites unoccupied at 1% FDR: 92208
[175:24] Precursors with PTMs localised (when required) with > 90% confidence: 612 out of 636
[175:26] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d.quant

[175:26] Cross-run analysis
[175:26] Reading quantification information: 6 files
[175:45] Quantifying peptides
[176:48] Quantification parameters: 0.355045, 0.00136467, 0.00338586, 0.104209, 0.14858, 0.132467, 0.218756, 0.0141217, 0.0216494, 0.145459, 0.0994423, 0.115031, 0.177917, 0.0827051, 0.0869967, 0.01131
[176:53] Assembling protein groups
[176:55] Quantifying proteins
[176:56] Calculating q-values for protein and gene groups
[176:57] Calculating global q-values for protein and gene groups
[176:57] Protein groups with global q-value <= 0.01: 11453
[177:00] Compressed report saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.3.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[177:00] Stats report saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.3.0/report.stats.tsv
[177:01] Generating spectral library:
[177:03] 118090 target and 1105 decoy precursors saved
WARNING: 2573 precursors without any fragments annotated were skipped
[177:03] Spectral library saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.3.0/report-lib.parquet

