
DIA-NN 2.5.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Apr 12 2026 10:45:33
Current date and time: Tue Jun 23 20:44:52 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.5.0/diann-linux --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d --fasta /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta --out /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report.tsv --temp /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0 --threads 15 --missed-cleavages 1 --min-pep-len 6 --max-pep-len 30 --mass-acc 20 --mass-acc-ms1 20 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 1 --max-pr-charge 5 --min-pr-mz 400 --max-pr-mz 1200 --min-fr-mz 200 --max-fr-mz 2000 --cut K*,R* --unimod4 --var-mod UniMod:35,15.994915,M --var-mods 1 --gen-spec-lib --fasta-search --reanalyse 

Thread number set to 15
Maximum number of missed cleavages set to 1
Min peptide length set to 6
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 1
Max precursor charge set to 5
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
In silico digest will involve cuts at K*,R*
Cysteine carbamidomethylation enabled as a fixed modification
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
Maximum number of variable modifications set to 1
A spectral library will be generated
DIA-NN will carry out FASTA digest for in silico lib generation
MBR enabled; .quant files will only be saved to disk during the first pass
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 

12 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:05] Processing FASTA
[0:07] Assembling elution groups
[0:13] 5697771 precursors generated
[0:13] Protein names missing for some isoforms
[0:13] Gene names missing for some isoforms
[0:13] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:17] [0:27] [8:11] [9:09] [9:13] [9:16] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report-lib.predicted.speclib
[9:19] Initialising library
[9:29] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report-lib.predicted.speclib
[9:31] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[9:32] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5697771 precursors in 2602499 elution groups (targets and decoys).
[9:32] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[9:33] Annotating library proteins with information from the FASTA database
[9:33] Protein names missing for some isoforms
[9:33] Gene names missing for some isoforms
[9:33] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[9:36] Initialising library

First pass: generating a spectral library from DIA data

[9:46] File #1/12
[9:46] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.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
[9:53] Pre-processing...
[9:54] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[9:55] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[15:56] RT window set to 2.16471
[15:56] IM window set to 0.0398389
[15:56] Peak width: 3.324
[15:56] Scan window radius set to 7
[15:57] Recommended MS1 mass accuracy setting: 8 ppm
[19:23] Searching decoys
[22:55] Main search
[29:38] Removing low confidence identifications
[29:47] Removing interfering precursors
[29:51] Training neural networks on 25537 target and 15147 decoy PSMs
[30:04] Training neural networks on 25537 target and 14702 decoy PSMs
[30:16] Precursors at 1% peptidoform FDR: 11516
[30:17] Number of IDs at 0.01 FDR: 12619
[30:17] Calculating protein q-values
[30:17] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[30:17] Quantification
[30:18] Precursors with scored PTMs at 1% FDR: 235 out of 292 considered
[30:18] Precursors with all scored PTM sites unoccupied at 1% FDR: 11434
[30:18] Precursors with PTMs localised (when required) with > 90% confidence: 228 out of 235
[30:18] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R1_d.quant

[30:18] File #2/12
[30:18] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[30:26] Pre-processing...
[30:27] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[30:28] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[36:29] RT window set to 2.36152
[36:29] IM window set to 0.0422986
[36:29] Recommended MS1 mass accuracy setting: 9 ppm
[40:18] Searching decoys
[44:20] Main search
[52:08] Removing low confidence identifications
[52:16] Removing interfering precursors
[52:21] Training neural networks on 27992 target and 16594 decoy PSMs
[52:35] Training neural networks on 27992 target and 15914 decoy PSMs
[52:48] Precursors at 1% peptidoform FDR: 12590
[52:48] Number of IDs at 0.01 FDR: 13702
[52:48] Calculating protein q-values
[52:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[52:49] Quantification
[52:49] Precursors with scored PTMs at 1% FDR: 295 out of 354 considered
[52:49] Precursors with all scored PTM sites unoccupied at 1% FDR: 12486
[52:49] Precursors with PTMs localised (when required) with > 90% confidence: 289 out of 295
[52:50] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R2_d.quant

[52:50] File #3/12
[52:50] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[52:57] Pre-processing...
[52:59] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[52:59] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[58:59] RT window set to 2.63063
[58:59] IM window set to 0.0425411
[59:00] Recommended MS1 mass accuracy setting: 9 ppm
[63:00] Searching decoys
[67:24] Main search
[75:55] Removing low confidence identifications
[76:04] Removing interfering precursors
[76:09] Training neural networks on 28646 target and 17146 decoy PSMs
[76:24] Training neural networks on 28646 target and 16588 decoy PSMs
[76:37] Precursors at 1% peptidoform FDR: 12461
[76:38] Number of IDs at 0.01 FDR: 13820
[76:38] Calculating protein q-values
[76:38] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[76:38] Quantification
[76:39] Precursors with scored PTMs at 1% FDR: 278 out of 349 considered
[76:39] Precursors with all scored PTM sites unoccupied at 1% FDR: 12354
[76:39] Precursors with PTMs localised (when required) with > 90% confidence: 275 out of 278
[76:39] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R3_d.quant

[76:39] File #4/12
[76:39] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[76:48] Pre-processing...
[76:49] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[76:50] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[82:46] RT window set to 2.6394
[82:46] IM window set to 0.0420806
[82:47] Recommended MS1 mass accuracy setting: 9 ppm
[86:47] Searching decoys
[91:27] Main search
[100:28] Removing low confidence identifications
[100:37] Removing interfering precursors
[100:42] Training neural networks on 29548 target and 18148 decoy PSMs
[100:59] Training neural networks on 29548 target and 17551 decoy PSMs
[101:12] Precursors at 1% peptidoform FDR: 13195
[101:13] Number of IDs at 0.01 FDR: 14350
[101:13] Calculating protein q-values
[101:13] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[101:13] Quantification
[101:14] Precursors with scored PTMs at 1% FDR: 329 out of 395 considered
[101:14] Precursors with all scored PTM sites unoccupied at 1% FDR: 13013
[101:14] Precursors with PTMs localised (when required) with > 90% confidence: 318 out of 329
[101:15] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R4_d.quant

[101:15] File #5/12
[101:15] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[101:24] Pre-processing...
[101:26] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[101:26] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[107:29] RT window set to 2.35148
[107:29] IM window set to 0.041132
[107:29] Recommended MS1 mass accuracy setting: 9 ppm
[111:18] Searching decoys
[115:32] Main search
[123:45] Removing low confidence identifications
[123:54] Removing interfering precursors
[124:00] Training neural networks on 31391 target and 19426 decoy PSMs
[124:16] Training neural networks on 31391 target and 18989 decoy PSMs
[124:30] Precursors at 1% peptidoform FDR: 13094
[124:31] Number of IDs at 0.01 FDR: 14472
[124:31] Calculating protein q-values
[124:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[124:32] Quantification
[124:33] Precursors with scored PTMs at 1% FDR: 330 out of 399 considered
[124:33] Precursors with all scored PTM sites unoccupied at 1% FDR: 13020
[124:33] Precursors with PTMs localised (when required) with > 90% confidence: 324 out of 330
[124:33] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R5_d.quant

[124:33] File #6/12
[124:33] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[124:41] Pre-processing...
[124:42] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[124:43] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[130:47] RT window set to 2.32824
[130:47] IM window set to 0.0410968
[130:48] Recommended MS1 mass accuracy setting: 9 ppm
[134:31] Searching decoys
[138:42] Main search
[146:56] Removing low confidence identifications
[147:06] Removing interfering precursors
[147:11] Training neural networks on 28930 target and 17779 decoy PSMs
[147:27] Training neural networks on 28930 target and 17178 decoy PSMs
[147:42] Precursors at 1% peptidoform FDR: 12591
[147:42] Number of IDs at 0.01 FDR: 13798
[147:42] Calculating protein q-values
[147:43] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[147:43] Quantification
[147:43] Precursors with scored PTMs at 1% FDR: 326 out of 382 considered
[147:43] Precursors with all scored PTM sites unoccupied at 1% FDR: 12424
[147:43] Precursors with PTMs localised (when required) with > 90% confidence: 317 out of 326
[147:44] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R6_d.quant

[147:44] File #7/12
[147:44] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[147:51] Pre-processing...
[147:52] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[147:52] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[153:30] RT window set to 2.41123
[153:30] IM window set to 0.0411372
[153:31] Recommended MS1 mass accuracy setting: 9 ppm
[156:50] Searching decoys
[160:23] Main search
[167:10] Removing low confidence identifications
[167:19] Removing interfering precursors
[167:23] Training neural networks on 29332 target and 17647 decoy PSMs
[167:37] Training neural networks on 29332 target and 17517 decoy PSMs
[167:47] Precursors at 1% peptidoform FDR: 12917
[167:48] Number of IDs at 0.01 FDR: 14423
[167:48] Calculating protein q-values
[167:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[167:49] Quantification
[167:49] Precursors with scored PTMs at 1% FDR: 322 out of 390 considered
[167:49] Precursors with all scored PTM sites unoccupied at 1% FDR: 12842
[167:49] Precursors with PTMs localised (when required) with > 90% confidence: 314 out of 322
[167:50] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R1_d.quant

[167:50] File #8/12
[167:50] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[167:56] Pre-processing...
[167:57] 1886 MS1 and 49019 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[167:58] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[173:12] RT window set to 2.5422
[173:12] IM window set to 0.0420461
[173:12] Recommended MS1 mass accuracy setting: 9 ppm
[176:37] Searching decoys
[180:12] Main search
[187:13] Removing low confidence identifications
[187:22] Removing interfering precursors
[187:26] Training neural networks on 30051 target and 18027 decoy PSMs
[187:40] Training neural networks on 30051 target and 17469 decoy PSMs
[187:52] Precursors at 1% peptidoform FDR: 13226
[187:52] Number of IDs at 0.01 FDR: 14604
[187:52] Calculating protein q-values
[187:53] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[187:53] Quantification
[187:53] Precursors with scored PTMs at 1% FDR: 332 out of 407 considered
[187:53] Precursors with all scored PTM sites unoccupied at 1% FDR: 13047
[187:53] Precursors with PTMs localised (when required) with > 90% confidence: 322 out of 332
[187:54] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R2_d.quant

[187:54] File #9/12
[187:54] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[188:01] Pre-processing...
[188:02] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[188:03] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[193:30] RT window set to 2.31209
[193:30] IM window set to 0.0418463
[193:30] Recommended MS1 mass accuracy setting: 9 ppm
[196:39] Searching decoys
[200:01] Main search
[206:35] Removing low confidence identifications
[206:44] Removing interfering precursors
[206:48] Training neural networks on 32082 target and 19374 decoy PSMs
[207:01] Training neural networks on 32082 target and 18728 decoy PSMs
[207:12] Precursors at 1% peptidoform FDR: 14253
[207:13] Number of IDs at 0.01 FDR: 15639
[207:13] Calculating protein q-values
[207:13] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[207:13] Quantification
[207:14] Precursors with scored PTMs at 1% FDR: 366 out of 435 considered
[207:14] Precursors with all scored PTM sites unoccupied at 1% FDR: 14134
[207:14] Precursors with PTMs localised (when required) with > 90% confidence: 353 out of 366
[207:14] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R3_d.quant

[207:14] File #10/12
[207:14] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[207:21] Pre-processing...
[207:23] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[207:23] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[212:38] RT window set to 2.83336
[212:38] IM window set to 0.0421429
[212:38] Recommended MS1 mass accuracy setting: 9 ppm
[216:11] Searching decoys
[220:19] Main search
[228:22] Removing low confidence identifications
[228:30] Removing interfering precursors
[228:35] Training neural networks on 30510 target and 18208 decoy PSMs
[228:48] Training neural networks on 30510 target and 17768 decoy PSMs
[228:59] Precursors at 1% peptidoform FDR: 13761
[229:00] Number of IDs at 0.01 FDR: 15007
[229:00] Calculating protein q-values
[229:00] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[229:00] Quantification
[229:01] Precursors with scored PTMs at 1% FDR: 375 out of 442 considered
[229:01] Precursors with all scored PTM sites unoccupied at 1% FDR: 13543
[229:01] Precursors with PTMs localised (when required) with > 90% confidence: 361 out of 375
[229:01] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R4_d.quant

[229:01] File #11/12
[229:01] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[229:08] Pre-processing...
[229:10] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[229:10] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[234:17] RT window set to 2.29746
[234:17] IM window set to 0.041183
[234:17] Recommended MS1 mass accuracy setting: 9 ppm
[237:20] Searching decoys
[240:44] Main search
[247:21] Removing low confidence identifications
[247:29] Removing interfering precursors
[247:34] Training neural networks on 34341 target and 21176 decoy PSMs
[247:48] Training neural networks on 34341 target and 20554 decoy PSMs
[247:59] Precursors at 1% peptidoform FDR: 14183
[248:00] Number of IDs at 0.01 FDR: 15672
[248:00] Calculating protein q-values
[248:00] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[248:00] Quantification
[248:01] Precursors with scored PTMs at 1% FDR: 360 out of 444 considered
[248:01] Precursors with all scored PTM sites unoccupied at 1% FDR: 14034
[248:01] Precursors with PTMs localised (when required) with > 90% confidence: 351 out of 360
[248:01] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R5_d.quant

[248:01] File #12/12
[248:01] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[248:08] Pre-processing...
[248:10] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[248:10] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[253:17] RT window set to 2.34887
[253:17] IM window set to 0.0422373
[253:18] Recommended MS1 mass accuracy setting: 9 ppm
[255:51] Searching decoys
[259:20] Main search
[266:07] Removing low confidence identifications
[266:16] Removing interfering precursors
[266:20] Training neural networks on 33861 target and 21063 decoy PSMs
[266:34] Training neural networks on 33861 target and 20340 decoy PSMs
[266:45] Precursors at 1% peptidoform FDR: 14277
[266:46] Number of IDs at 0.01 FDR: 15887
[266:46] Calculating protein q-values
[266:46] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[266:46] Quantification
[266:47] Precursors with scored PTMs at 1% FDR: 363 out of 449 considered
[266:47] Precursors with all scored PTM sites unoccupied at 1% FDR: 14124
[266:47] Precursors with PTMs localised (when required) with > 90% confidence: 355 out of 363
[266:47] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R6_d.quant

[266:47] Cross-run analysis
[266:47] Reading quantification information: 12 files
[266:57] Target precursors at 1% global q-value: 23148
[266:57] Quantifying peptides
[267:01] Assembling protein groups
[267:01] Quantifying proteins
[267:01] Calculating q-values for protein and gene groups
[267:03] Calculating global q-values for protein and gene groups
[267:03] Protein groups with global q-value <= 0.01: 2883
[267:04] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[267:04] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report-first-pass.stats.tsv
[267:04] Generating spectral library:
[267:05] 24577 target and 1409 decoy precursors saved
WARNING: 1610 precursors without any fragments annotated were skipped
[267:05] Spectral library saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report-lib.parquet

[267:05] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report-lib.parquet
[267:05] Spectral library loaded: 4863 protein isoforms, 4747 protein groups and 25986 precursors in 24435 elution groups (targets and decoys).
[267:05] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[267:05] Annotating library proteins with information from the FASTA database
[267:05] Gene names missing for some isoforms
[267:05] Library contains 4848 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[267:05] Initialising library
[267:06] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report-lib.parquet.skyline.speclib


Second pass: using the newly created spectral library to reanalyse the data

[267:06] File #1/12
[267:06] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d
[267:12] Pre-processing...
[267:13] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[267:13] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[267:15] RT window set to 0.715453
[267:15] IM window set to 0.01
[267:15] Recommended MS1 mass accuracy setting: 10 ppm
[267:16] Searching decoys
[267:16] Main search
[267:18] Removing low confidence identifications
[267:19] Removing interfering precursors
[267:19] Training neural networks on 22069 target and 13042 decoy PSMs
[267:25] Training neural networks on 22036 target and 11564 decoy PSMs
[267:30] Precursors at 1% peptidoform FDR: 16020
[267:30] Number of IDs at 0.01 FDR: 16638
[267:30] Calculating protein q-values
[267:30] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[267:30] Quantification
[267:31] Precursors with scored PTMs at 1% FDR: 270 out of 299 considered
[267:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 15798
[267:31] Precursors with PTMs localised (when required) with > 90% confidence: 266 out of 270

[267:31] File #2/12
[267:31] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[267:37] Pre-processing...
[267:38] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[267:38] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[267:40] RT window set to 0.716149
[267:40] IM window set to 0.01
[267:40] Recommended MS1 mass accuracy setting: 10 ppm
[267:41] Searching decoys
[267:41] Main search
[267:42] Removing low confidence identifications
[267:44] Removing interfering precursors
[267:44] Training neural networks on 21833 target and 12205 decoy PSMs
[267:49] Training neural networks on 21807 target and 11644 decoy PSMs
[267:55] Precursors at 1% peptidoform FDR: 16185
[267:55] Number of IDs at 0.01 FDR: 17060
[267:55] Calculating protein q-values
[267:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[267:55] Quantification
[267:55] Precursors with scored PTMs at 1% FDR: 307 out of 337 considered
[267:55] Precursors with all scored PTM sites unoccupied at 1% FDR: 15993
[267:55] Precursors with PTMs localised (when required) with > 90% confidence: 300 out of 307

[267:55] File #3/12
[267:55] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[268:02] Pre-processing...
[268:03] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[268:03] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[268:05] RT window set to 0.708147
[268:05] IM window set to 0.01
[268:05] Recommended MS1 mass accuracy setting: 10 ppm
[268:06] Searching decoys
[268:06] Main search
[268:07] Removing low confidence identifications
[268:08] Removing interfering precursors
[268:09] Training neural networks on 22017 target and 12058 decoy PSMs
[268:14] Training neural networks on 21994 target and 11712 decoy PSMs
[268:20] Precursors at 1% peptidoform FDR: 16246
[268:20] Number of IDs at 0.01 FDR: 17048
[268:20] Calculating protein q-values
[268:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[268:20] Quantification
[268:20] Precursors with scored PTMs at 1% FDR: 320 out of 353 considered
[268:20] Precursors with all scored PTM sites unoccupied at 1% FDR: 16216
[268:20] Precursors with PTMs localised (when required) with > 90% confidence: 313 out of 320

[268:20] File #4/12
[268:20] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[268:27] Pre-processing...
[268:28] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[268:28] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[268:30] RT window set to 0.706558
[268:30] IM window set to 0.01
[268:30] Recommended MS1 mass accuracy setting: 10 ppm
[268:31] Searching decoys
[268:31] Main search
[268:33] Removing low confidence identifications
[268:34] Removing interfering precursors
[268:34] Training neural networks on 22480 target and 13483 decoy PSMs
[268:40] Training neural networks on 22444 target and 11709 decoy PSMs
[268:46] Precursors at 1% peptidoform FDR: 17296
[268:46] Number of IDs at 0.01 FDR: 17812
[268:46] Calculating protein q-values
[268:46] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[268:46] Quantification
[268:46] Precursors with scored PTMs at 1% FDR: 333 out of 355 considered
[268:46] Precursors with all scored PTM sites unoccupied at 1% FDR: 17054
[268:46] Precursors with PTMs localised (when required) with > 90% confidence: 329 out of 333

[268:46] File #5/12
[268:46] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[268:53] Pre-processing...
[268:54] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[268:54] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[268:56] RT window set to 0.701798
[268:56] IM window set to 0.01
[268:57] Recommended MS1 mass accuracy setting: 10 ppm
[268:57] Searching decoys
[268:58] Main search
[268:59] Removing low confidence identifications
[269:00] Removing interfering precursors
[269:00] Training neural networks on 22453 target and 13458 decoy PSMs
[269:06] Training neural networks on 22421 target and 11729 decoy PSMs
[269:12] Precursors at 1% peptidoform FDR: 17124
[269:12] Number of IDs at 0.01 FDR: 17813
[269:12] Calculating protein q-values
[269:12] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[269:12] Quantification
[269:12] Precursors with scored PTMs at 1% FDR: 329 out of 355 considered
[269:12] Precursors with all scored PTM sites unoccupied at 1% FDR: 16917
[269:12] Precursors with PTMs localised (when required) with > 90% confidence: 323 out of 329

[269:12] File #6/12
[269:12] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[269:19] Pre-processing...
[269:20] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[269:20] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[269:22] RT window set to 0.698436
[269:22] IM window set to 0.01
[269:22] Recommended MS1 mass accuracy setting: 10 ppm
[269:23] Searching decoys
[269:23] Main search
[269:25] Removing low confidence identifications
[269:26] Removing interfering precursors
[269:26] Training neural networks on 22455 target and 13502 decoy PSMs
[269:32] Training neural networks on 22425 target and 11602 decoy PSMs
[269:37] Precursors at 1% peptidoform FDR: 16828
[269:38] Number of IDs at 0.01 FDR: 17614
[269:38] Calculating protein q-values
[269:38] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[269:38] Quantification
[269:38] Precursors with scored PTMs at 1% FDR: 314 out of 348 considered
[269:38] Precursors with all scored PTM sites unoccupied at 1% FDR: 16604
[269:38] Precursors with PTMs localised (when required) with > 90% confidence: 308 out of 314

[269:38] File #7/12
[269:38] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[269:44] Pre-processing...
[269:45] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[269:45] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[269:47] RT window set to 0.719323
[269:47] IM window set to 0.01
[269:47] Recommended MS1 mass accuracy setting: 10 ppm
[269:48] Searching decoys
[269:48] Main search
[269:49] Removing low confidence identifications
[269:51] Removing interfering precursors
[269:51] Training neural networks on 22114 target and 12247 decoy PSMs
[269:56] Training neural networks on 22095 target and 11821 decoy PSMs
[270:02] Precursors at 1% peptidoform FDR: 16324
[270:02] Number of IDs at 0.01 FDR: 17189
[270:02] Calculating protein q-values
[270:02] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[270:02] Quantification
[270:02] Precursors with scored PTMs at 1% FDR: 320 out of 341 considered
[270:02] Precursors with all scored PTM sites unoccupied at 1% FDR: 16406
[270:02] Precursors with PTMs localised (when required) with > 90% confidence: 316 out of 320

[270:02] File #8/12
[270:02] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[270:09] Pre-processing...
[270:09] 1886 MS1 and 49019 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[270:09] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[270:11] RT window set to 0.718107
[270:11] IM window set to 0.01
[270:11] Recommended MS1 mass accuracy setting: 10 ppm
[270:12] Searching decoys
[270:12] Main search
[270:13] Removing low confidence identifications
[270:15] Removing interfering precursors
[270:15] Training neural networks on 22209 target and 12144 decoy PSMs
[270:20] Training neural networks on 22185 target and 11699 decoy PSMs
[270:26] Precursors at 1% peptidoform FDR: 17196
[270:26] Number of IDs at 0.01 FDR: 17705
[270:26] Calculating protein q-values
[270:26] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[270:26] Quantification
[270:26] Precursors with scored PTMs at 1% FDR: 341 out of 358 considered
[270:26] Precursors with all scored PTM sites unoccupied at 1% FDR: 17010
[270:26] Precursors with PTMs localised (when required) with > 90% confidence: 335 out of 341

[270:26] File #9/12
[270:26] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[270:33] Pre-processing...
[270:34] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[270:34] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[270:36] RT window set to 0.690631
[270:36] IM window set to 0.01
[270:36] Recommended MS1 mass accuracy setting: 10 ppm
[270:37] Searching decoys
[270:37] Main search
[270:38] Removing low confidence identifications
[270:40] Removing interfering precursors
[270:40] Training neural networks on 22367 target and 12340 decoy PSMs
[270:46] Training neural networks on 22346 target and 12004 decoy PSMs
[270:51] Precursors at 1% peptidoform FDR: 17511
[270:51] Number of IDs at 0.01 FDR: 18224
[270:51] Calculating protein q-values
[270:51] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[270:51] Quantification
[270:52] Precursors with scored PTMs at 1% FDR: 355 out of 386 considered
[270:52] Precursors with all scored PTM sites unoccupied at 1% FDR: 17376
[270:52] Precursors with PTMs localised (when required) with > 90% confidence: 346 out of 355

[270:52] File #10/12
[270:52] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[270:59] Pre-processing...
[271:00] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[271:00] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[271:02] RT window set to 0.707643
[271:02] IM window set to 0.01
[271:02] Recommended MS1 mass accuracy setting: 10 ppm
[271:02] Searching decoys
[271:03] Main search
[271:04] Removing low confidence identifications
[271:05] Removing interfering precursors
[271:06] Training neural networks on 22396 target and 12485 decoy PSMs
[271:11] Training neural networks on 22370 target and 12063 decoy PSMs
[271:17] Precursors at 1% peptidoform FDR: 17492
[271:17] Number of IDs at 0.01 FDR: 18322
[271:17] Calculating protein q-values
[271:17] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[271:17] Quantification
[271:17] Precursors with scored PTMs at 1% FDR: 360 out of 413 considered
[271:17] Precursors with all scored PTM sites unoccupied at 1% FDR: 17203
[271:17] Precursors with PTMs localised (when required) with > 90% confidence: 351 out of 360

[271:18] File #11/12
[271:18] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[271:25] Pre-processing...
[271:26] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[271:26] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[271:28] RT window set to 0.688783
[271:28] IM window set to 0.01
[271:28] Recommended MS1 mass accuracy setting: 10 ppm
[271:28] Searching decoys
[271:29] Main search
[271:30] Removing low confidence identifications
[271:31] Removing interfering precursors
[271:31] Training neural networks on 22366 target and 12495 decoy PSMs
[271:37] Training neural networks on 22344 target and 11955 decoy PSMs
[271:43] Precursors at 1% peptidoform FDR: 17651
[271:43] Number of IDs at 0.01 FDR: 18064
[271:43] Calculating protein q-values
[271:43] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[271:43] Quantification
[271:43] Precursors with scored PTMs at 1% FDR: 359 out of 377 considered
[271:43] Precursors with all scored PTM sites unoccupied at 1% FDR: 17297
[271:43] Precursors with PTMs localised (when required) with > 90% confidence: 352 out of 359

[271:43] File #12/12
[271:43] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[271:50] Pre-processing...
[271:51] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 24577 precursors in range
[271:51] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[271:54] RT window set to 0.686836
[271:54] IM window set to 0.01
[271:54] Recommended MS1 mass accuracy setting: 10 ppm
[271:54] Searching decoys
[271:55] Main search
[271:56] Removing low confidence identifications
[271:57] Removing interfering precursors
[271:57] Training neural networks on 22325 target and 12376 decoy PSMs
[272:03] Training neural networks on 22305 target and 11792 decoy PSMs
[272:09] Precursors at 1% peptidoform FDR: 17202
[272:09] Number of IDs at 0.01 FDR: 18014
[272:09] Calculating protein q-values
[272:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[272:09] Quantification
[272:09] Precursors with scored PTMs at 1% FDR: 363 out of 385 considered
[272:09] Precursors with all scored PTM sites unoccupied at 1% FDR: 17142
[272:09] Precursors with PTMs localised (when required) with > 90% confidence: 355 out of 363

[272:09] Cross-run analysis
[272:09] Reading quantification information: 12 files
[272:10] Target precursors at 1% global q-value: 21482
[272:10] Quantifying peptides
[272:27] Quantification parameters: 0.329222, 0.00236752, 0.0113301, 0.0144208, 0.136115, 0.090556, 0.310888, 0.198903, 0.251349, 0.0153635, 0.12975, 0.022543, 0.357907, 0.278472, 0.233458, 0.0277423
[272:29] Quantifying proteins
[272:29] Calculating q-values for protein and gene groups
[272:29] Calculating global q-values for protein and gene groups
[272:29] Protein groups with global q-value <= 0.01: 2814
[272:30] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[272:30] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.5.0/report.stats.tsv

