
DIA-NN 2.3.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Sep 26 2025 02:56:25
Current date and time: Tue Jun 23 20:09:15 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.3.0/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_v2.3.0/report.tsv --temp /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0 --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
[0:04] Processing FASTA
[0:06] Assembling elution groups
[0:11] 5697771 precursors generated
[0:11] Protein names missing for some isoforms
[0:11] Gene names missing for some isoforms
[0:11] Library contains 31685 proteins, and 0 genes
[0:15] [0:24] [8:59] [10:04] [10:08] [10:12] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report-lib.predicted.speclib
[10:16] Initialising library
[10:30] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report-lib.predicted.speclib
[10:31] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[10:33] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5697771 precursors in 2602499 elution groups.
[10:33] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[10:33] Annotating library proteins with information from the FASTA database
[10:33] Protein names missing for some isoforms
[10:33] Gene names missing for some isoforms
[10:33] Library contains 31685 proteins, and 0 genes
[10:37] Initialising library

First pass: generating a spectral library from DIA data

[10:46] File #1/12
[10:46] 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
[10:53] Pre-processing...
[10:54] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[10:55] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[16:31] RT window set to 2.2366
[16:31] IM window set to 0.0395007
[16:31] Peak width: 3.228
[16:31] Scan window radius set to 7
[16:32] Recommended MS1 mass accuracy setting: 9 ppm
[19:55] Searching decoys
[23:51] Main search
[31:36] Removing low confidence identifications
[31:43] Removing interfering precursors
[31:46] Training neural networks on 21967 target and 11410 decoy PSMs
[31:59] Training neural networks on 21967 target and 10766 decoy PSMs
[32:08] IDs at 0.01 FDR: 11910
[32:08] Precursors at 1% peptidoform FDR: 11407
[32:09] Number of IDs at 0.01 FDR: 13028
[32:09] Calculating protein q-values
[32:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[32:09] Quantification
[32:10] Precursors with scored PTMs at 1% FDR: 247 out of 331 considered
[32:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 11403
[32:10] Precursors with PTMs localised (when required) with > 90% confidence: 241 out of 247
[32:10] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R1_d.quant

[32:10] File #2/12
[32:10] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[32:18] Pre-processing...
[32:19] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[32:20] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[37:31] RT window set to 2.39976
[37:31] IM window set to 0.0420427
[37:31] Recommended MS1 mass accuracy setting: 9 ppm
[40:56] Searching decoys
[45:20] Main search
[54:02] Removing low confidence identifications
[54:09] Removing interfering precursors
[54:13] Training neural networks on 24661 target and 12836 decoy PSMs
[54:27] Training neural networks on 24661 target and 12213 decoy PSMs
[54:37] IDs at 0.01 FDR: 13078
[54:37] Precursors at 1% peptidoform FDR: 12643
[54:38] Number of IDs at 0.01 FDR: 14465
[54:38] Calculating protein q-values
[54:39] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[54:39] Quantification
[54:39] Precursors with scored PTMs at 1% FDR: 275 out of 368 considered
[54:39] Precursors with all scored PTM sites unoccupied at 1% FDR: 12656
[54:39] Precursors with PTMs localised (when required) with > 90% confidence: 269 out of 275
[54:40] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R2_d.quant

[54:40] File #3/12
[54:40] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[54:48] Pre-processing...
[54:49] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[54:50] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[60:10] RT window set to 2.53214
[60:10] IM window set to 0.0432846
[60:11] Recommended MS1 mass accuracy setting: 9 ppm
[63:53] Searching decoys
[68:36] Main search
[77:57] Removing low confidence identifications
[78:05] Removing interfering precursors
[78:09] Training neural networks on 25869 target and 13642 decoy PSMs
[78:24] Training neural networks on 25869 target and 13060 decoy PSMs
[78:34] IDs at 0.01 FDR: 13023
[78:34] Precursors at 1% peptidoform FDR: 12431
[78:35] Number of IDs at 0.01 FDR: 14437
[78:35] Calculating protein q-values
[78:35] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[78:35] Quantification
[78:36] Precursors with scored PTMs at 1% FDR: 274 out of 367 considered
[78:36] Precursors with all scored PTM sites unoccupied at 1% FDR: 12429
[78:36] Precursors with PTMs localised (when required) with > 90% confidence: 271 out of 274
[78:36] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R3_d.quant

[78:36] File #4/12
[78:36] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[78:45] Pre-processing...
[78:46] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[78:47] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[84:17] RT window set to 2.56215
[84:17] IM window set to 0.041074
[84:17] Recommended MS1 mass accuracy setting: 9 ppm
[88:09] Searching decoys
[93:00] Main search
[102:15] Removing low confidence identifications
[102:22] Removing interfering precursors
[102:26] Training neural networks on 25991 target and 13654 decoy PSMs
[102:39] Training neural networks on 25991 target and 12947 decoy PSMs
[102:50] IDs at 0.01 FDR: 13918
[102:50] Precursors at 1% peptidoform FDR: 13317
[102:51] Number of IDs at 0.01 FDR: 15157
[102:51] Calculating protein q-values
[102:51] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[102:52] Quantification
[102:52] Precursors with scored PTMs at 1% FDR: 317 out of 424 considered
[102:52] Precursors with all scored PTM sites unoccupied at 1% FDR: 13230
[102:52] Precursors with PTMs localised (when required) with > 90% confidence: 305 out of 317
[102:53] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R4_d.quant

[102:53] File #5/12
[102:53] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[103:00] Pre-processing...
[103:02] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[103:02] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[108:34] RT window set to 2.35541
[108:34] IM window set to 0.0424555
[108:35] Recommended MS1 mass accuracy setting: 9 ppm
[112:08] Searching decoys
[116:50] Main search
[126:08] Removing low confidence identifications
[126:15] Removing interfering precursors
[126:19] Training neural networks on 25976 target and 13452 decoy PSMs
[126:33] Training neural networks on 25976 target and 12906 decoy PSMs
[126:44] IDs at 0.01 FDR: 13623
[126:44] Precursors at 1% peptidoform FDR: 12920
[126:45] Number of IDs at 0.01 FDR: 14989
[126:45] Calculating protein q-values
[126:46] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[126:46] Quantification
[126:47] Precursors with scored PTMs at 1% FDR: 304 out of 418 considered
[126:47] Precursors with all scored PTM sites unoccupied at 1% FDR: 12875
[126:47] Precursors with PTMs localised (when required) with > 90% confidence: 297 out of 304
[126:47] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R5_d.quant

[126:47] File #6/12
[126:47] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[126:55] Pre-processing...
[126:56] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[126:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[132:13] RT window set to 2.29996
[132:13] IM window set to 0.0407313
[132:13] Recommended MS1 mass accuracy setting: 9 ppm
[135:39] Searching decoys
[140:16] Main search
[149:07] Removing low confidence identifications
[149:14] Removing interfering precursors
[149:18] Training neural networks on 24387 target and 12693 decoy PSMs
[149:31] Training neural networks on 24387 target and 12005 decoy PSMs
[149:40] IDs at 0.01 FDR: 13122
[149:40] Precursors at 1% peptidoform FDR: 12606
[149:41] Number of IDs at 0.01 FDR: 14253
[149:41] Calculating protein q-values
[149:42] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[149:42] Quantification
[149:42] Precursors with scored PTMs at 1% FDR: 314 out of 397 considered
[149:42] Precursors with all scored PTM sites unoccupied at 1% FDR: 12504
[149:42] Precursors with PTMs localised (when required) with > 90% confidence: 308 out of 314
[149:43] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R6_d.quant

[149:43] File #7/12
[149:43] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[149:50] Pre-processing...
[149:51] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[149:51] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[155:00] RT window set to 2.41341
[155:00] IM window set to 0.0419516
[155:00] Recommended MS1 mass accuracy setting: 9 ppm
[158:25] Searching decoys
[162:46] Main search
[171:18] Removing low confidence identifications
[171:25] Removing interfering precursors
[171:29] Training neural networks on 22968 target and 11418 decoy PSMs
[171:42] Training neural networks on 22968 target and 11159 decoy PSMs
[171:51] IDs at 0.01 FDR: 12957
[171:52] Precursors at 1% peptidoform FDR: 12378
[171:53] Number of IDs at 0.01 FDR: 14277
[171:53] Calculating protein q-values
[171:53] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[171:53] Quantification
[171:54] Precursors with scored PTMs at 1% FDR: 304 out of 389 considered
[171:54] Precursors with all scored PTM sites unoccupied at 1% FDR: 12376
[171:54] Precursors with PTMs localised (when required) with > 90% confidence: 298 out of 304
[171:54] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R1_d.quant

[171:54] File #8/12
[171:54] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[172:01] Pre-processing...
[172:02] 1886 MS1 and 49019 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[172:03] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[177:07] RT window set to 2.5107
[177:07] IM window set to 0.0409393
[177:08] Recommended MS1 mass accuracy setting: 8 ppm
[180:31] Searching decoys
[184:41] Main search
[192:57] Removing low confidence identifications
[193:04] Removing interfering precursors
[193:08] Training neural networks on 24159 target and 12059 decoy PSMs
[193:21] Training neural networks on 24159 target and 11558 decoy PSMs
[193:30] IDs at 0.01 FDR: 13504
[193:31] Precursors at 1% peptidoform FDR: 12844
[193:31] Number of IDs at 0.01 FDR: 14576
[193:31] Calculating protein q-values
[193:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[193:32] Quantification
[193:32] Precursors with scored PTMs at 1% FDR: 307 out of 413 considered
[193:32] Precursors with all scored PTM sites unoccupied at 1% FDR: 12717
[193:32] Precursors with PTMs localised (when required) with > 90% confidence: 300 out of 307
[193:33] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R2_d.quant

[193:33] File #9/12
[193:33] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[193:40] Pre-processing...
[193:41] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[193:42] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[198:39] RT window set to 2.31464
[198:39] IM window set to 0.0419398
[198:39] Recommended MS1 mass accuracy setting: 9 ppm
[201:18] Searching decoys
[205:14] Main search
[213:05] Removing low confidence identifications
[213:11] Removing interfering precursors
[213:15] Training neural networks on 25278 target and 12653 decoy PSMs
[213:27] Training neural networks on 25278 target and 12120 decoy PSMs
[213:36] IDs at 0.01 FDR: 14210
[213:36] Precursors at 1% peptidoform FDR: 13540
[213:37] Number of IDs at 0.01 FDR: 15344
[213:37] Calculating protein q-values
[213:37] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[213:37] Quantification
[213:38] Precursors with scored PTMs at 1% FDR: 352 out of 441 considered
[213:38] Precursors with all scored PTM sites unoccupied at 1% FDR: 13360
[213:38] Precursors with PTMs localised (when required) with > 90% confidence: 343 out of 352
[213:38] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R3_d.quant

[213:38] File #10/12
[213:38] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[213:46] Pre-processing...
[213:47] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[213:48] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[218:45] RT window set to 2.85488
[218:45] IM window set to 0.0426567
[218:46] Recommended MS1 mass accuracy setting: 9 ppm
[222:18] Searching decoys
[226:59] Main search
[236:13] Removing low confidence identifications
[236:19] Removing interfering precursors
[236:23] Training neural networks on 26464 target and 13541 decoy PSMs
[236:35] Training neural networks on 26464 target and 12902 decoy PSMs
[236:43] IDs at 0.01 FDR: 14456
[236:43] Precursors at 1% peptidoform FDR: 13419
[236:44] Number of IDs at 0.01 FDR: 15661
[236:44] Calculating protein q-values
[236:44] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[236:44] Quantification
[236:45] Precursors with scored PTMs at 1% FDR: 338 out of 468 considered
[236:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 13202
[236:45] Precursors with PTMs localised (when required) with > 90% confidence: 330 out of 338
[236:45] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R4_d.quant

[236:45] File #11/12
[236:45] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[236:52] Pre-processing...
[236:54] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[236:54] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[241:31] RT window set to 2.35678
[241:31] IM window set to 0.0411235
[241:31] Recommended MS1 mass accuracy setting: 9 ppm
[244:01] Searching decoys
[247:55] Main search
[255:33] Removing low confidence identifications
[255:40] Removing interfering precursors
[255:43] Training neural networks on 25922 target and 13061 decoy PSMs
[255:55] Training neural networks on 25922 target and 12529 decoy PSMs
[256:02] IDs at 0.01 FDR: 14003
[256:03] Precursors at 1% peptidoform FDR: 13514
[256:03] Number of IDs at 0.01 FDR: 15483
[256:03] Calculating protein q-values
[256:04] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[256:04] Quantification
[256:04] Precursors with scored PTMs at 1% FDR: 346 out of 446 considered
[256:04] Precursors with all scored PTM sites unoccupied at 1% FDR: 13516
[256:04] Precursors with PTMs localised (when required) with > 90% confidence: 335 out of 346
[256:05] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R5_d.quant

[256:05] File #12/12
[256:05] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[256:12] Pre-processing...
[256:14] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[256:14] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[260:51] RT window set to 2.34808
[260:51] IM window set to 0.042774
[260:51] Recommended MS1 mass accuracy setting: 9 ppm
[263:22] Searching decoys
[267:22] Main search
[275:10] Removing low confidence identifications
[275:16] Removing interfering precursors
[275:20] Training neural networks on 27156 target and 13967 decoy PSMs
[275:31] Training neural networks on 27156 target and 13419 decoy PSMs
[275:40] IDs at 0.01 FDR: 14337
[275:40] Precursors at 1% peptidoform FDR: 13599
[275:41] Number of IDs at 0.01 FDR: 15640
[275:41] Calculating protein q-values
[275:41] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[275:41] Quantification
[275:42] Precursors with scored PTMs at 1% FDR: 342 out of 468 considered
[275:42] Precursors with all scored PTM sites unoccupied at 1% FDR: 13450
[275:42] Precursors with PTMs localised (when required) with > 90% confidence: 335 out of 342
[275:42] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R6_d.quant

[275:42] Cross-run analysis
[275:42] Reading quantification information: 12 files
[275:52] Quantifying peptides
[275:56] Assembling protein groups
[275:57] Quantifying proteins
[275:57] Calculating q-values for protein and gene groups
[275:59] Calculating global q-values for protein and gene groups
[275:59] Protein groups with global q-value <= 0.01: 2869
[275:59] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[275:59] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report-first-pass.stats.tsv
[275:59] Generating spectral library:
[276:00] 21342 target and 193 decoy precursors saved
WARNING: 899 precursors without any fragments annotated were skipped
[276:00] Spectral library saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report-lib.parquet

[276:00] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report-lib.parquet
[276:00] Spectral library loaded: 3328 protein isoforms, 3178 protein groups and 21535 precursors in 20206 elution groups.
[276:00] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[276:00] Annotating library proteins with information from the FASTA database
[276:00] Gene names missing for some isoforms
[276:00] Library contains 3295 proteins, and 0 genes
[276:00] Initialising library
[276:01] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report-lib.parquet.skyline.speclib


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

[276:01] File #1/12
[276:01] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d
[276:07] Pre-processing...
[276:08] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[276:08] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[276:09] RT window set to 0.727207
[276:09] IM window set to 0.01
[276:09] Recommended MS1 mass accuracy setting: 9 ppm
[276:10] Searching decoys
[276:10] Main search
[276:11] Removing low confidence identifications
[276:12] Removing interfering precursors
[276:12] Training neural networks on 18572 target and 11699 decoy PSMs
[276:18] Training neural networks on 18566 target and 11013 decoy PSMs
[276:23] IDs at 0.01 FDR: 15659
[276:23] Precursors at 1% peptidoform FDR: 14612
[276:23] Number of IDs at 0.01 FDR: 16448
[276:23] Calculating protein q-values
[276:23] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[276:23] Quantification
[276:24] Precursors with scored PTMs at 1% FDR: 312 out of 339 considered
[276:24] Precursors with all scored PTM sites unoccupied at 1% FDR: 14745
[276:24] Precursors with PTMs localised (when required) with > 90% confidence: 308 out of 312

[276:24] File #2/12
[276:24] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[276:30] Pre-processing...
[276:31] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[276:31] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[276:32] RT window set to 0.712128
[276:32] IM window set to 0.01
[276:32] Recommended MS1 mass accuracy setting: 10 ppm
[276:33] Searching decoys
[276:33] Main search
[276:34] Removing low confidence identifications
[276:35] Removing interfering precursors
[276:35] Training neural networks on 18827 target and 12140 decoy PSMs
[276:41] Training neural networks on 18825 target and 11065 decoy PSMs
[276:46] IDs at 0.01 FDR: 16684
[276:46] Precursors at 1% peptidoform FDR: 15727
[276:46] Number of IDs at 0.01 FDR: 17349
[276:46] Calculating protein q-values
[276:46] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[276:46] Quantification
[276:47] Precursors with scored PTMs at 1% FDR: 342 out of 365 considered
[276:47] Precursors with all scored PTM sites unoccupied at 1% FDR: 15775
[276:47] Precursors with PTMs localised (when required) with > 90% confidence: 332 out of 342

[276:47] File #3/12
[276:47] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[276:54] Pre-processing...
[276:55] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[276:55] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[276:56] RT window set to 0.693163
[276:56] IM window set to 0.01
[276:56] Recommended MS1 mass accuracy setting: 10 ppm
[276:56] Searching decoys
[276:57] Main search
[276:57] Removing low confidence identifications
[276:58] Removing interfering precursors
[276:59] Training neural networks on 18857 target and 12131 decoy PSMs
[277:04] Training neural networks on 18854 target and 11106 decoy PSMs
[277:10] IDs at 0.01 FDR: 16472
[277:10] Precursors at 1% peptidoform FDR: 14994
[277:10] Number of IDs at 0.01 FDR: 17324
[277:10] Calculating protein q-values
[277:10] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[277:10] Quantification
[277:10] Precursors with scored PTMs at 1% FDR: 333 out of 374 considered
[277:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 14990
[277:10] Precursors with PTMs localised (when required) with > 90% confidence: 329 out of 333

[277:11] File #4/12
[277:11] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[277:18] Pre-processing...
[277:19] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[277:19] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[277:20] RT window set to 0.718752
[277:20] IM window set to 0.01
[277:20] Recommended MS1 mass accuracy setting: 10 ppm
[277:20] Searching decoys
[277:21] Main search
[277:21] Removing low confidence identifications
[277:22] Removing interfering precursors
[277:23] Training neural networks on 18974 target and 12300 decoy PSMs
[277:28] Training neural networks on 18971 target and 11238 decoy PSMs
[277:34] IDs at 0.01 FDR: 16776
[277:34] Precursors at 1% peptidoform FDR: 15597
[277:34] Number of IDs at 0.01 FDR: 17553
[277:34] Calculating protein q-values
[277:34] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[277:34] Quantification
[277:34] Precursors with scored PTMs at 1% FDR: 347 out of 378 considered
[277:34] Precursors with all scored PTM sites unoccupied at 1% FDR: 15680
[277:34] Precursors with PTMs localised (when required) with > 90% confidence: 344 out of 347

[277:35] File #5/12
[277:35] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[277:42] Pre-processing...
[277:43] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[277:43] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[277:44] RT window set to 0.698971
[277:44] IM window set to 0.01
[277:44] Recommended MS1 mass accuracy setting: 10 ppm
[277:44] Searching decoys
[277:45] Main search
[277:45] Removing low confidence identifications
[277:46] Removing interfering precursors
[277:47] Training neural networks on 18898 target and 12150 decoy PSMs
[277:52] Training neural networks on 18888 target and 11150 decoy PSMs
[277:58] IDs at 0.01 FDR: 16804
[277:58] Precursors at 1% peptidoform FDR: 15645
[277:58] Number of IDs at 0.01 FDR: 17486
[277:58] Calculating protein q-values
[277:58] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[277:58] Quantification
[277:58] Precursors with scored PTMs at 1% FDR: 347 out of 378 considered
[277:58] Precursors with all scored PTM sites unoccupied at 1% FDR: 15640
[277:58] Precursors with PTMs localised (when required) with > 90% confidence: 340 out of 347

[277:58] File #6/12
[277:58] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[278:06] Pre-processing...
[278:07] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[278:07] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[278:08] RT window set to 0.704004
[278:08] IM window set to 0.01
[278:08] Recommended MS1 mass accuracy setting: 10 ppm
[278:08] Searching decoys
[278:08] Main search
[278:09] Removing low confidence identifications
[278:10] Removing interfering precursors
[278:10] Training neural networks on 18895 target and 12200 decoy PSMs
[278:16] Training neural networks on 18892 target and 11107 decoy PSMs
[278:22] IDs at 0.01 FDR: 16245
[278:22] Precursors at 1% peptidoform FDR: 15308
[278:22] Number of IDs at 0.01 FDR: 17309
[278:22] Calculating protein q-values
[278:22] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[278:22] Quantification
[278:22] Precursors with scored PTMs at 1% FDR: 344 out of 372 considered
[278:22] Precursors with all scored PTM sites unoccupied at 1% FDR: 15586
[278:22] Precursors with PTMs localised (when required) with > 90% confidence: 336 out of 344

[278:23] File #7/12
[278:23] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[278:29] Pre-processing...
[278:30] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[278:30] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[278:31] RT window set to 0.715123
[278:31] IM window set to 0.0101561
[278:31] Recommended MS1 mass accuracy setting: 10 ppm
[278:31] Searching decoys
[278:32] Main search
[278:32] Removing low confidence identifications
[278:33] Removing interfering precursors
[278:33] Training neural networks on 18853 target and 11905 decoy PSMs
[278:39] Training neural networks on 18850 target and 11052 decoy PSMs
[278:45] IDs at 0.01 FDR: 16562
[278:45] Precursors at 1% peptidoform FDR: 15735
[278:45] Number of IDs at 0.01 FDR: 17299
[278:45] Calculating protein q-values
[278:45] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[278:45] Quantification
[278:45] Precursors with scored PTMs at 1% FDR: 355 out of 381 considered
[278:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 15862
[278:45] Precursors with PTMs localised (when required) with > 90% confidence: 349 out of 355

[278:45] File #8/12
[278:45] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[278:52] Pre-processing...
[278:52] 1886 MS1 and 49019 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[278:52] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[278:53] RT window set to 0.709402
[278:53] IM window set to 0.0111054
[278:53] Recommended MS1 mass accuracy setting: 10 ppm
[278:54] Searching decoys
[278:54] Main search
[278:55] Removing low confidence identifications
[278:56] Removing interfering precursors
[278:56] Training neural networks on 18903 target and 12024 decoy PSMs
[279:02] Training neural networks on 18897 target and 11150 decoy PSMs
[279:07] IDs at 0.01 FDR: 17156
[279:07] Precursors at 1% peptidoform FDR: 16084
[279:07] Number of IDs at 0.01 FDR: 17867
[279:07] Calculating protein q-values
[279:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[279:07] Quantification
[279:08] Precursors with scored PTMs at 1% FDR: 370 out of 400 considered
[279:08] Precursors with all scored PTM sites unoccupied at 1% FDR: 16120
[279:08] Precursors with PTMs localised (when required) with > 90% confidence: 363 out of 370

[279:08] File #9/12
[279:08] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[279:15] Pre-processing...
[279:16] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[279:16] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[279:17] RT window set to 0.697833
[279:17] IM window set to 0.0100215
[279:17] Recommended MS1 mass accuracy setting: 10 ppm
[279:17] Searching decoys
[279:18] Main search
[279:18] Removing low confidence identifications
[279:19] Removing interfering precursors
[279:20] Training neural networks on 19052 target and 12325 decoy PSMs
[279:25] Training neural networks on 19048 target and 11394 decoy PSMs
[279:31] IDs at 0.01 FDR: 17993
[279:31] Precursors at 1% peptidoform FDR: 16723
[279:31] Number of IDs at 0.01 FDR: 18443
[279:31] Calculating protein q-values
[279:31] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[279:31] Quantification
[279:31] Precursors with scored PTMs at 1% FDR: 374 out of 396 considered
[279:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 16558
[279:31] Precursors with PTMs localised (when required) with > 90% confidence: 367 out of 374

[279:32] File #10/12
[279:32] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[279:39] Pre-processing...
[279:40] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[279:40] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[279:41] RT window set to 0.700396
[279:41] IM window set to 0.0104672
[279:41] Recommended MS1 mass accuracy setting: 10 ppm
[279:41] Searching decoys
[279:42] Main search
[279:42] Removing low confidence identifications
[279:43] Removing interfering precursors
[279:44] Training neural networks on 19052 target and 12488 decoy PSMs
[279:49] Training neural networks on 19048 target and 11286 decoy PSMs
[279:55] IDs at 0.01 FDR: 17568
[279:55] Precursors at 1% peptidoform FDR: 16475
[279:55] Number of IDs at 0.01 FDR: 18135
[279:55] Calculating protein q-values
[279:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[279:55] Quantification
[279:56] Precursors with scored PTMs at 1% FDR: 373 out of 399 considered
[279:56] Precursors with all scored PTM sites unoccupied at 1% FDR: 16403
[279:56] Precursors with PTMs localised (when required) with > 90% confidence: 367 out of 373

[279:56] File #11/12
[279:56] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[280:03] Pre-processing...
[280:04] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[280:04] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[280:05] RT window set to 0.684982
[280:05] IM window set to 0.0101338
[280:05] Recommended MS1 mass accuracy setting: 11 ppm
[280:05] Searching decoys
[280:06] Main search
[280:07] Removing low confidence identifications
[280:08] Removing interfering precursors
[280:08] Training neural networks on 19030 target and 12299 decoy PSMs
[280:14] Training neural networks on 19024 target and 11240 decoy PSMs
[280:19] IDs at 0.01 FDR: 17482
[280:19] Precursors at 1% peptidoform FDR: 16397
[280:19] Number of IDs at 0.01 FDR: 18111
[280:19] Calculating protein q-values
[280:19] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[280:19] Quantification
[280:20] Precursors with scored PTMs at 1% FDR: 384 out of 409 considered
[280:20] Precursors with all scored PTM sites unoccupied at 1% FDR: 16356
[280:20] Precursors with PTMs localised (when required) with > 90% confidence: 375 out of 384

[280:20] File #12/12
[280:20] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[280:27] Pre-processing...
[280:28] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 21342 precursors in range
[280:28] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[280:29] RT window set to 0.695142
[280:29] IM window set to 0.0104908
[280:29] Recommended MS1 mass accuracy setting: 10 ppm
[280:30] Searching decoys
[280:30] Main search
[280:31] Removing low confidence identifications
[280:32] Removing interfering precursors
[280:32] Training neural networks on 18931 target and 12143 decoy PSMs
[280:38] Training neural networks on 18924 target and 11037 decoy PSMs
[280:44] IDs at 0.01 FDR: 17484
[280:44] Precursors at 1% peptidoform FDR: 16397
[280:44] Number of IDs at 0.01 FDR: 18105
[280:44] Calculating protein q-values
[280:44] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[280:44] Quantification
[280:44] Precursors with scored PTMs at 1% FDR: 377 out of 401 considered
[280:44] Precursors with all scored PTM sites unoccupied at 1% FDR: 16336
[280:44] Precursors with PTMs localised (when required) with > 90% confidence: 367 out of 377

[280:44] Cross-run analysis
[280:44] Reading quantification information: 12 files
[280:45] Quantifying peptides
[281:00] Quantification parameters: 0.31867, 0.00237364, 0.0110395, 0.0209978, 0.168206, 0.0977823, 0.317296, 0.192475, 0.258211, 0.0139865, 0.148787, 0.0469613, 0.367691, 0.272255, 0.230473, 0.0141308
[281:02] Quantifying proteins
[281:02] Calculating q-values for protein and gene groups
[281:02] Calculating global q-values for protein and gene groups
[281:02] Protein groups with global q-value <= 0.01: 2666
[281:03] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[281:03] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.3.0/report.stats.tsv

