
DIA-NN 2.1.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Mar 23 2025 15:49:03
Current date and time: Wed Apr 22 08:52:17 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.1.0/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_v2.1.0/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
[0:23] [0:38] [6:05] [6:48] [6:51] [6:54] Saving the library to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.1.0/report-lib.predicted.speclib
[6:59] Initialising library
[7:25] Loading spectral library /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.1.0/report-lib.predicted.speclib
[7:28] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[7:30] Spectral library loaded: 31832 protein isoforms, 43199 protein groups and 8103720 precursors in 3825450 elution groups.
[7:30] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[7:30] Annotating library proteins with information from the FASTA database
[7:30] Protein names missing for some isoforms
[7:30] Gene names missing for some isoforms
[7:30] Library contains 31680 proteins, and 0 genes
[7:36] 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 15 ppm
[8:30] Pre-processing...
[9:59] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[10:00] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[12:07] RT window set to 2.42966
[12:07] IM window set to 0.0438291
[12:07] Peak width: 4.088
[12:07] Scan window radius set to 8
[12:07] Recommended MS1 mass accuracy setting: 11 ppm
[13:16] Searching decoys
[21:10] Main search
[36:42] Removing low confidence identifications
[37:07] Removing interfering precursors
[37:16] Training neural networks on 161048 target and 103133 decoy PSMs
[37:50] Training neural networks on 161048 target and 96790 decoy PSMs
[38:18] Number of IDs at 0.01 FDR: 94410
[38:19] Precursors at 1% peptidoform FDR: 88684
[38:20] Calculating protein q-values
[38:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[38:21] Quantification
[38:23] Precursors with scored PTMs at 1% FDR: 624 out of 1394 considered
[38:23] Precursors with all scored PTM sites unoccupied at 1% FDR: 88060
[38:23] Precursors with PTMs localised (when required) with > 90% confidence: 605 out of 624
[38:25] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d.quant

[38:25] File #2/6
[38:25] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d
[38:51] Pre-processing...
[40:22] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[40:23] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[42:09] RT window set to 2.76055
[42:09] IM window set to 0.045193
[42:10] Recommended MS1 mass accuracy setting: 11 ppm
[43:22] Searching decoys
[52:06] Main search
[69:08] Removing low confidence identifications
[69:33] Removing interfering precursors
[69:42] Training neural networks on 163313 target and 105477 decoy PSMs
[70:18] Training neural networks on 163313 target and 99042 decoy PSMs
[70:49] Number of IDs at 0.01 FDR: 97349
[70:50] Precursors at 1% peptidoform FDR: 91169
[70:51] Calculating protein q-values
[70:51] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[70:51] Quantification
[70:54] Precursors with scored PTMs at 1% FDR: 677 out of 1505 considered
[70:54] Precursors with all scored PTM sites unoccupied at 1% FDR: 90492
[70:54] Precursors with PTMs localised (when required) with > 90% confidence: 649 out of 677
[70:55] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d.quant

[70:55] File #3/6
[70:55] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d
[71:21] Pre-processing...
[72:54] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[72:55] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[74:41] RT window set to 2.5845
[74:41] IM window set to 0.0449089
[74:41] Recommended MS1 mass accuracy setting: 12 ppm
[75:54] Searching decoys
[84:12] Main search
[100:32] Removing low confidence identifications
[100:57] Removing interfering precursors
[101:07] Training neural networks on 166101 target and 107760 decoy PSMs
[101:47] Training neural networks on 166101 target and 100310 decoy PSMs
[102:18] Number of IDs at 0.01 FDR: 98304
[102:19] Precursors at 1% peptidoform FDR: 91880
[102:20] Calculating protein q-values
[102:21] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[102:21] Quantification
[102:23] Precursors with scored PTMs at 1% FDR: 576 out of 1409 considered
[102:23] Precursors with all scored PTM sites unoccupied at 1% FDR: 91304
[102:23] Precursors with PTMs localised (when required) with > 90% confidence: 560 out of 576
[102:25] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d.quant

[102:25] File #4/6
[102:25] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d
[103:17] Pre-processing...
[104:47] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[104:48] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[106:30] RT window set to 2.43305
[106:30] IM window set to 0.0436028
[106:30] Recommended MS1 mass accuracy setting: 11 ppm
[107:37] Searching decoys
[115:28] Main search
[130:56] Removing low confidence identifications
[131:20] Removing interfering precursors
[131:29] Training neural networks on 159615 target and 102888 decoy PSMs
[132:03] Training neural networks on 159615 target and 96855 decoy PSMs
[132:29] Number of IDs at 0.01 FDR: 95175
[132:30] Precursors at 1% peptidoform FDR: 89097
[132:30] Calculating protein q-values
[132:31] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[132:31] Quantification
[132:33] Precursors with scored PTMs at 1% FDR: 602 out of 1363 considered
[132:33] Precursors with all scored PTM sites unoccupied at 1% FDR: 88495
[132:33] Precursors with PTMs localised (when required) with > 90% confidence: 577 out of 602
[132:35] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d.quant

[132:35] File #5/6
[132:35] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d
[133:28] Pre-processing...
[134:58] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[134:59] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[136:42] RT window set to 2.60041
[136:42] IM window set to 0.044824
[136:42] Recommended MS1 mass accuracy setting: 11 ppm
[137:51] Searching decoys
[146:04] Main search
[162:11] Removing low confidence identifications
[162:36] Removing interfering precursors
[162:45] Training neural networks on 157539 target and 101954 decoy PSMs
[163:20] Training neural networks on 157539 target and 95272 decoy PSMs
[163:49] Number of IDs at 0.01 FDR: 96290
[163:49] Precursors at 1% peptidoform FDR: 90556
[163:50] Calculating protein q-values
[163:51] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[163:51] Quantification
[163:53] Precursors with scored PTMs at 1% FDR: 603 out of 1376 considered
[163:53] Precursors with all scored PTM sites unoccupied at 1% FDR: 89953
[163:53] Precursors with PTMs localised (when required) with > 90% confidence: 590 out of 603
[163:55] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d.quant

[163:55] File #6/6
[163:55] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d
[164:48] Pre-processing...
[166:19] 4348 MS1 and 104343 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[166:20] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[168:07] RT window set to 2.64937
[168:07] IM window set to 0.0432892
[168:07] Recommended MS1 mass accuracy setting: 12 ppm
[169:16] Searching decoys
[177:19] Main search
[193:07] Removing low confidence identifications
[193:32] Removing interfering precursors
[193:41] Training neural networks on 162040 target and 104646 decoy PSMs
[194:15] Training neural networks on 162040 target and 98931 decoy PSMs
[194:42] Number of IDs at 0.01 FDR: 97509
[194:43] Precursors at 1% peptidoform FDR: 91075
[194:44] Calculating protein q-values
[194:45] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[194:45] Quantification
[194:47] Precursors with scored PTMs at 1% FDR: 646 out of 1369 considered
[194:47] Precursors with all scored PTM sites unoccupied at 1% FDR: 90429
[194:47] Precursors with PTMs localised (when required) with > 90% confidence: 628 out of 646
[194:49] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d.quant

[194:49] Cross-run analysis
[194:49] Reading quantification information: 6 files
[195:09] Quantifying peptides
[196:12] Quantification parameters: 0.350531, 0.00138931, 0.00342072, 0.100419, 0.129451, 0.118507, 0.220925, 0.0145735, 0.0410705, 0.138543, 0.0895651, 0.104916, 0.213936, 0.0798466, 0.0991007, 0.0120911
[196:28] Assembling protein groups
[196:30] Quantifying proteins
[196:31] Calculating q-values for protein and gene groups
[196:32] Calculating global q-values for protein and gene groups
[196:32] Protein groups with global q-value <= 0.01: 11475
[196:35] Compressed report saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.1.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[196:35] Stats report saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.1.0/report.stats.tsv
[196:35] Generating spectral library:
[196:37] 118667 target and 1171 decoy precursors saved
WARNING: 820 precursors without any fragments annotated were skipped
[196:37] Spectral library saved to /home/robbe/PB_output/results/test_run/HYE_diaPASEF/diann_v2.1.0/report-lib.parquet

