
DIA-NN 2.2.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on May 29 2025 15:05:00
Current date and time: Tue Jun 23 20:09:15 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.2.0/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_v2.2.0/report.tsv --temp /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0 --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] [0:25] [10:29] [11:36] [11:39] [11:42] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report-lib.predicted.speclib
[11:45] Initialising library
[11:55] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report-lib.predicted.speclib
[11:57] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[11:58] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5697771 precursors in 2602499 elution groups.
[11:58] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[11:58] Annotating library proteins with information from the FASTA database
[11:58] Protein names missing for some isoforms
[11:58] Gene names missing for some isoforms
[11:58] Library contains 31685 proteins, and 0 genes
[12:02] Initialising library

First pass: generating a spectral library from DIA data

[12:11] File #1/12
[12:11] 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 15 ppm
[12:18] Pre-processing...
[12:19] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[12:20] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[17:53] RT window set to 2.26952
[17:53] IM window set to 0.0405775
[17:53] Peak width: 3.292
[17:53] Scan window radius set to 7
[17:53] Recommended MS1 mass accuracy setting: 9 ppm
[21:09] Searching decoys
[25:27] Main search
[33:10] Removing low confidence identifications
[33:16] Removing interfering precursors
[33:20] Training neural networks on 20535 target and 10285 decoy PSMs
[33:31] Training neural networks on 20535 target and 9471 decoy PSMs
[33:39] Number of IDs at 0.01 FDR: 11892
[33:40] Precursors at 1% peptidoform FDR: 11247
[33:40] Calculating protein q-values
[33:41] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[33:41] Quantification
[33:42] Precursors with scored PTMs at 1% FDR: 241 out of 265 considered
[33:42] Precursors with all scored PTM sites unoccupied at 1% FDR: 11006
[33:42] Precursors with PTMs localised (when required) with > 90% confidence: 236 out of 241
[33:42] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R1_d.quant

[33:42] File #2/12
[33:42] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[33:50] Pre-processing...
[33:51] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[33:52] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[39:33] RT window set to 2.48107
[39:33] IM window set to 0.0434209
[39:33] Recommended MS1 mass accuracy setting: 10 ppm
[43:38] Searching decoys
[48:17] Main search
[57:25] Removing low confidence identifications
[57:32] Removing interfering precursors
[57:37] Training neural networks on 26088 target and 13759 decoy PSMs
[57:51] Training neural networks on 26088 target and 12922 decoy PSMs
[58:01] Number of IDs at 0.01 FDR: 13785
[58:01] Precursors at 1% peptidoform FDR: 12607
[58:02] Calculating protein q-values
[58:02] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[58:03] Quantification
[58:03] Precursors with scored PTMs at 1% FDR: 257 out of 311 considered
[58:03] Precursors with all scored PTM sites unoccupied at 1% FDR: 12350
[58:03] Precursors with PTMs localised (when required) with > 90% confidence: 252 out of 257
[58:04] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R2_d.quant

[58:04] File #3/12
[58:04] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[58:12] Pre-processing...
[58:14] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[58:14] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[63:58] RT window set to 2.53042
[63:58] IM window set to 0.0423806
[63:58] Recommended MS1 mass accuracy setting: 9 ppm
[67:36] Searching decoys
[72:21] Main search
[81:34] Removing low confidence identifications
[81:41] Removing interfering precursors
[81:45] Training neural networks on 24101 target and 12572 decoy PSMs
[81:58] Training neural networks on 24101 target and 11777 decoy PSMs
[82:08] Number of IDs at 0.01 FDR: 12946
[82:08] Precursors at 1% peptidoform FDR: 12177
[82:09] Calculating protein q-values
[82:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[82:09] Quantification
[82:10] Precursors with scored PTMs at 1% FDR: 279 out of 310 considered
[82:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 11898
[82:10] Precursors with PTMs localised (when required) with > 90% confidence: 275 out of 279
[82:10] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R3_d.quant

[82:10] File #4/12
[82:10] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[82:20] Pre-processing...
[82:22] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[82:22] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[88:06] RT window set to 2.61421
[88:06] IM window set to 0.0427333
[88:06] Recommended MS1 mass accuracy setting: 9 ppm
[91:58] Searching decoys
[97:02] Main search
[107:02] Removing low confidence identifications
[107:10] Removing interfering precursors
[107:14] Training neural networks on 26592 target and 14139 decoy PSMs
[107:28] Training neural networks on 26592 target and 13329 decoy PSMs
[107:38] Number of IDs at 0.01 FDR: 13958
[107:39] Precursors at 1% peptidoform FDR: 13107
[107:39] Calculating protein q-values
[107:40] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[107:40] Quantification
[107:41] Precursors with scored PTMs at 1% FDR: 300 out of 344 considered
[107:41] Precursors with all scored PTM sites unoccupied at 1% FDR: 12807
[107:41] Precursors with PTMs localised (when required) with > 90% confidence: 290 out of 300
[107:41] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R4_d.quant

[107:41] File #5/12
[107:41] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[107:50] Pre-processing...
[107:51] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[107:52] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[113:38] RT window set to 2.55445
[113:38] IM window set to 0.0432809
[113:39] Recommended MS1 mass accuracy setting: 9 ppm
[117:32] Searching decoys
[122:29] Main search
[132:18] Removing low confidence identifications
[132:25] Removing interfering precursors
[132:28] Training neural networks on 24126 target and 12705 decoy PSMs
[132:43] Training neural networks on 24126 target and 11725 decoy PSMs
[132:52] Number of IDs at 0.01 FDR: 13167
[132:53] Precursors at 1% peptidoform FDR: 12522
[132:53] Calculating protein q-values
[132:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[132:54] Quantification
[132:55] Precursors with scored PTMs at 1% FDR: 290 out of 313 considered
[132:55] Precursors with all scored PTM sites unoccupied at 1% FDR: 12232
[132:55] Precursors with PTMs localised (when required) with > 90% confidence: 283 out of 290
[132:55] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R5_d.quant

[132:55] File #6/12
[132:55] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[133:03] Pre-processing...
[133:05] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[133:05] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[138:31] RT window set to 2.5895
[138:31] IM window set to 0.0411529
[138:31] Recommended MS1 mass accuracy setting: 9 ppm
[142:18] Searching decoys
[147:13] Main search
[157:05] Removing low confidence identifications
[157:12] Removing interfering precursors
[157:16] Training neural networks on 24991 target and 13257 decoy PSMs
[157:30] Training neural networks on 24991 target and 12538 decoy PSMs
[157:40] Number of IDs at 0.01 FDR: 13362
[157:40] Precursors at 1% peptidoform FDR: 12674
[157:41] Calculating protein q-values
[157:41] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[157:41] Quantification
[157:42] Precursors with scored PTMs at 1% FDR: 278 out of 305 considered
[157:42] Precursors with all scored PTM sites unoccupied at 1% FDR: 12396
[157:42] Precursors with PTMs localised (when required) with > 90% confidence: 273 out of 278
[157:42] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R6_d.quant

[157:42] File #7/12
[157:42] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[157:50] Pre-processing...
[157:51] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[157:51] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[163:33] RT window set to 2.6067
[163:33] IM window set to 0.0416294
[163:33] Recommended MS1 mass accuracy setting: 8 ppm
[167:23] Searching decoys
[172:09] Main search
[181:36] Removing low confidence identifications
[181:44] Removing interfering precursors
[181:48] Training neural networks on 24130 target and 12096 decoy PSMs
[182:03] Training neural networks on 24130 target and 11580 decoy PSMs
[182:13] Number of IDs at 0.01 FDR: 13433
[182:14] Precursors at 1% peptidoform FDR: 12855
[182:14] Calculating protein q-values
[182:15] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[182:15] Quantification
[182:15] Precursors with scored PTMs at 1% FDR: 284 out of 302 considered
[182:15] Precursors with all scored PTM sites unoccupied at 1% FDR: 12571
[182:15] Precursors with PTMs localised (when required) with > 90% confidence: 277 out of 284
[182:16] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R1_d.quant

[182:16] File #8/12
[182:16] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[182:24] Pre-processing...
[182:25] 1886 MS1 and 49019 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[182:26] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[187:40] RT window set to 2.50793
[187:40] IM window set to 0.0405478
[187:41] Recommended MS1 mass accuracy setting: 8 ppm
[190:53] Searching decoys
[194:47] Main search
[202:15] Removing low confidence identifications
[202:21] Removing interfering precursors
[202:25] Training neural networks on 25251 target and 12692 decoy PSMs
[202:37] Training neural networks on 25251 target and 12031 decoy PSMs
[202:46] Number of IDs at 0.01 FDR: 13930
[202:46] Precursors at 1% peptidoform FDR: 13215
[202:47] Calculating protein q-values
[202:47] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[202:47] Quantification
[202:48] Precursors with scored PTMs at 1% FDR: 295 out of 335 considered
[202:48] Precursors with all scored PTM sites unoccupied at 1% FDR: 12920
[202:48] Precursors with PTMs localised (when required) with > 90% confidence: 289 out of 295
[202:48] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R2_d.quant

[202:48] File #9/12
[202:48] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[202:55] Pre-processing...
[202:56] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[202:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[208:02] RT window set to 2.60019
[208:02] IM window set to 0.0421263
[208:03] Recommended MS1 mass accuracy setting: 9 ppm
[211:30] Searching decoys
[215:57] Main search
[224:22] Removing low confidence identifications
[224:29] Removing interfering precursors
[224:33] Training neural networks on 25767 target and 12949 decoy PSMs
[224:45] Training neural networks on 25767 target and 12322 decoy PSMs
[224:53] Number of IDs at 0.01 FDR: 14647
[224:54] Precursors at 1% peptidoform FDR: 13782
[224:54] Calculating protein q-values
[224:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[224:55] Quantification
[224:55] Precursors with scored PTMs at 1% FDR: 321 out of 358 considered
[224:55] Precursors with all scored PTM sites unoccupied at 1% FDR: 13461
[224:55] Precursors with PTMs localised (when required) with > 90% confidence: 311 out of 321
[224:56] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R3_d.quant

[224:56] File #10/12
[224:56] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[225:03] Pre-processing...
[225:05] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[225:05] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[230:10] RT window set to 2.6919
[230:10] IM window set to 0.0417288
[230:10] Recommended MS1 mass accuracy setting: 9 ppm
[233:26] Searching decoys
[237:44] Main search
[246:06] Removing low confidence identifications
[246:13] Removing interfering precursors
[246:17] Training neural networks on 28034 target and 14583 decoy PSMs
[246:29] Training neural networks on 28034 target and 13783 decoy PSMs
[246:38] Number of IDs at 0.01 FDR: 14566
[246:38] Precursors at 1% peptidoform FDR: 13866
[246:39] Calculating protein q-values
[246:39] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[246:39] Quantification
[246:40] Precursors with scored PTMs at 1% FDR: 339 out of 363 considered
[246:40] Precursors with all scored PTM sites unoccupied at 1% FDR: 13527
[246:40] Precursors with PTMs localised (when required) with > 90% confidence: 331 out of 339
[246:40] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R4_d.quant

[246:40] File #11/12
[246:40] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[246:47] Pre-processing...
[246:48] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[246:49] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[251:40] RT window set to 2.3431
[251:40] IM window set to 0.0419174
[251:40] Recommended MS1 mass accuracy setting: 9 ppm
[254:43] Searching decoys
[258:38] Main search
[266:14] Removing low confidence identifications
[266:21] Removing interfering precursors
[266:24] Training neural networks on 25588 target and 12730 decoy PSMs
[266:36] Training neural networks on 25588 target and 12177 decoy PSMs
[266:44] Number of IDs at 0.01 FDR: 14144
[266:44] Precursors at 1% peptidoform FDR: 13603
[266:44] Calculating protein q-values
[266:45] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[266:45] Quantification
[266:45] Precursors with scored PTMs at 1% FDR: 332 out of 358 considered
[266:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 13271
[266:45] Precursors with PTMs localised (when required) with > 90% confidence: 322 out of 332
[266:46] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R5_d.quant

[266:46] File #12/12
[266:46] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[266:53] Pre-processing...
[266:54] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[266:55] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[271:47] RT window set to 2.56467
[271:47] IM window set to 0.0419728
[271:47] Recommended MS1 mass accuracy setting: 9 ppm
[275:02] Searching decoys
[279:24] Main search
[287:56] Removing low confidence identifications
[288:04] Removing interfering precursors
[288:09] Training neural networks on 27506 target and 14193 decoy PSMs
[288:22] Training neural networks on 27506 target and 13505 decoy PSMs
[288:31] Number of IDs at 0.01 FDR: 14580
[288:31] Precursors at 1% peptidoform FDR: 13818
[288:32] Calculating protein q-values
[288:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[288:32] Quantification
[288:33] Precursors with scored PTMs at 1% FDR: 348 out of 370 considered
[288:33] Precursors with all scored PTM sites unoccupied at 1% FDR: 13470
[288:33] Precursors with PTMs localised (when required) with > 90% confidence: 340 out of 348
[288:33] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R6_d.quant

[288:34] Cross-run analysis
[288:34] Reading quantification information: 12 files
[288:44] Quantifying peptides
[289:10] Assembling protein groups
[289:12] Quantifying proteins
[289:12] Calculating q-values for protein and gene groups
[289:14] Calculating global q-values for protein and gene groups
[289:14] Protein groups with global q-value <= 0.01: 2885
[289:15] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[289:15] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report-first-pass.stats.tsv
[289:15] Generating spectral library:
[289:15] 20948 target and 205 decoy precursors saved
WARNING: 266 precursors without any fragments annotated were skipped
[289:15] Spectral library saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report-lib.parquet

[289:19] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report-lib.parquet
[289:20] Spectral library loaded: 3707 protein isoforms, 3512 protein groups and 21153 precursors in 19856 elution groups.
[289:20] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[289:20] Annotating library proteins with information from the FASTA database
[289:20] Gene names missing for some isoforms
[289:20] Library contains 3675 proteins, and 0 genes
[289:20] Initialising library
[289:20] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report-lib.parquet.skyline.speclib


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

[289:20] File #1/12
[289:20] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d
[289:26] Pre-processing...
[289:27] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[289:27] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[289:28] RT window set to 0.716558
[289:28] IM window set to 0.0107143
[289:28] Recommended MS1 mass accuracy setting: 10 ppm
[289:29] Searching decoys
[289:29] Main search
[289:30] Removing low confidence identifications
[289:31] Removing interfering precursors
[289:31] Training neural networks on 18517 target and 11713 decoy PSMs
[289:37] Training neural networks on 18513 target and 10862 decoy PSMs
[289:42] Number of IDs at 0.01 FDR: 15928
[289:42] Precursors at 1% peptidoform FDR: 14556
[289:42] Calculating protein q-values
[289:42] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[289:42] Quantification
[289:43] Precursors with scored PTMs at 1% FDR: 300 out of 324 considered
[289:43] Precursors with all scored PTM sites unoccupied at 1% FDR: 14256
[289:43] Precursors with PTMs localised (when required) with > 90% confidence: 295 out of 300

[289:43] File #2/12
[289:43] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[289:49] Pre-processing...
[289:50] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[289:50] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[289:51] RT window set to 0.713144
[289:51] IM window set to 0.0108339
[289:52] Recommended MS1 mass accuracy setting: 10 ppm
[289:52] Searching decoys
[289:52] Main search
[289:53] Removing low confidence identifications
[289:54] Removing interfering precursors
[289:55] Training neural networks on 18814 target and 12008 decoy PSMs
[290:00] Training neural networks on 18807 target and 11048 decoy PSMs
[290:06] Number of IDs at 0.01 FDR: 16408
[290:06] Precursors at 1% peptidoform FDR: 15321
[290:06] Calculating protein q-values
[290:06] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[290:06] Quantification
[290:06] Precursors with scored PTMs at 1% FDR: 309 out of 348 considered
[290:06] Precursors with all scored PTM sites unoccupied at 1% FDR: 15012
[290:06] Precursors with PTMs localised (when required) with > 90% confidence: 301 out of 309

[290:06] File #3/12
[290:06] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[290:13] Pre-processing...
[290:14] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[290:14] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[290:15] RT window set to 0.70417
[290:15] IM window set to 0.0103429
[290:15] Recommended MS1 mass accuracy setting: 10 ppm
[290:16] Searching decoys
[290:16] Main search
[290:17] Removing low confidence identifications
[290:18] Removing interfering precursors
[290:18] Training neural networks on 18772 target and 11890 decoy PSMs
[290:24] Training neural networks on 18762 target and 10999 decoy PSMs
[290:30] Number of IDs at 0.01 FDR: 16405
[290:30] Precursors at 1% peptidoform FDR: 15275
[290:30] Calculating protein q-values
[290:30] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[290:30] Quantification
[290:30] Precursors with scored PTMs at 1% FDR: 331 out of 355 considered
[290:30] Precursors with all scored PTM sites unoccupied at 1% FDR: 14944
[290:30] Precursors with PTMs localised (when required) with > 90% confidence: 324 out of 331

[290:30] File #4/12
[290:30] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[290:37] Pre-processing...
[290:38] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[290:38] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[290:40] RT window set to 0.705232
[290:40] IM window set to 0.0108441
[290:40] Recommended MS1 mass accuracy setting: 10 ppm
[290:40] Searching decoys
[290:41] Main search
[290:41] Removing low confidence identifications
[290:43] Removing interfering precursors
[290:43] Training neural networks on 18908 target and 12170 decoy PSMs
[290:49] Training neural networks on 18902 target and 11172 decoy PSMs
[290:54] Number of IDs at 0.01 FDR: 16925
[290:54] Precursors at 1% peptidoform FDR: 15915
[290:54] Calculating protein q-values
[290:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[290:54] Quantification
[290:55] Precursors with scored PTMs at 1% FDR: 353 out of 373 considered
[290:55] Precursors with all scored PTM sites unoccupied at 1% FDR: 15562
[290:55] Precursors with PTMs localised (when required) with > 90% confidence: 344 out of 353

[290:55] File #5/12
[290:55] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[291:02] Pre-processing...
[291:03] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[291:03] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[291:04] RT window set to 0.70065
[291:04] IM window set to 0.0100502
[291:04] Recommended MS1 mass accuracy setting: 11 ppm
[291:05] Searching decoys
[291:05] Main search
[291:06] Removing low confidence identifications
[291:07] Removing interfering precursors
[291:07] Training neural networks on 18845 target and 11940 decoy PSMs
[291:13] Training neural networks on 18839 target and 11070 decoy PSMs
[291:18] Number of IDs at 0.01 FDR: 16831
[291:18] Precursors at 1% peptidoform FDR: 15834
[291:18] Calculating protein q-values
[291:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[291:18] Quantification
[291:19] Precursors with scored PTMs at 1% FDR: 341 out of 357 considered
[291:19] Precursors with all scored PTM sites unoccupied at 1% FDR: 15493
[291:19] Precursors with PTMs localised (when required) with > 90% confidence: 334 out of 341

[291:19] File #6/12
[291:19] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[291:26] Pre-processing...
[291:27] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[291:27] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[291:28] RT window set to 0.70122
[291:28] IM window set to 0.0100274
[291:28] Recommended MS1 mass accuracy setting: 10 ppm
[291:29] Searching decoys
[291:29] Main search
[291:30] Removing low confidence identifications
[291:31] Removing interfering precursors
[291:31] Training neural networks on 18789 target and 11840 decoy PSMs
[291:37] Training neural networks on 18783 target and 10941 decoy PSMs
[291:42] Number of IDs at 0.01 FDR: 16527
[291:42] Precursors at 1% peptidoform FDR: 15323
[291:42] Calculating protein q-values
[291:42] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[291:42] Quantification
[291:43] Precursors with scored PTMs at 1% FDR: 336 out of 358 considered
[291:43] Precursors with all scored PTM sites unoccupied at 1% FDR: 14987
[291:43] Precursors with PTMs localised (when required) with > 90% confidence: 329 out of 336

[291:43] File #7/12
[291:43] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[291:49] Pre-processing...
[291:50] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[291:50] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[291:51] RT window set to 0.720648
[291:51] IM window set to 0.0110732
[291:51] Recommended MS1 mass accuracy setting: 10 ppm
[291:52] Searching decoys
[291:52] Main search
[291:53] Removing low confidence identifications
[291:54] Removing interfering precursors
[291:54] Training neural networks on 18822 target and 11857 decoy PSMs
[292:00] Training neural networks on 18816 target and 10939 decoy PSMs
[292:05] Number of IDs at 0.01 FDR: 16719
[292:05] Precursors at 1% peptidoform FDR: 15855
[292:05] Calculating protein q-values
[292:05] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[292:05] Quantification
[292:06] Precursors with scored PTMs at 1% FDR: 337 out of 357 considered
[292:06] Precursors with all scored PTM sites unoccupied at 1% FDR: 15518
[292:06] Precursors with PTMs localised (when required) with > 90% confidence: 331 out of 337

[292:06] File #8/12
[292:06] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[292:12] Pre-processing...
[292:13] 1886 MS1 and 49019 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[292:13] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[292:14] RT window set to 0.714307
[292:14] IM window set to 0.0113869
[292:14] Recommended MS1 mass accuracy setting: 10 ppm
[292:14] Searching decoys
[292:15] Main search
[292:16] Removing low confidence identifications
[292:17] Removing interfering precursors
[292:17] Training neural networks on 18899 target and 12150 decoy PSMs
[292:23] Training neural networks on 18891 target and 11184 decoy PSMs
[292:28] Number of IDs at 0.01 FDR: 17137
[292:28] Precursors at 1% peptidoform FDR: 16153
[292:28] Calculating protein q-values
[292:28] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[292:28] Quantification
[292:28] Precursors with scored PTMs at 1% FDR: 355 out of 371 considered
[292:28] Precursors with all scored PTM sites unoccupied at 1% FDR: 15798
[292:28] Precursors with PTMs localised (when required) with > 90% confidence: 347 out of 355

[292:29] File #9/12
[292:29] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[292:35] Pre-processing...
[292:36] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[292:36] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[292:37] RT window set to 0.689659
[292:37] IM window set to 0.01
[292:37] Recommended MS1 mass accuracy setting: 10 ppm
[292:38] Searching decoys
[292:38] Main search
[292:39] Removing low confidence identifications
[292:40] Removing interfering precursors
[292:40] Training neural networks on 19026 target and 12198 decoy PSMs
[292:46] Training neural networks on 19023 target and 11056 decoy PSMs
[292:52] Number of IDs at 0.01 FDR: 17486
[292:52] Precursors at 1% peptidoform FDR: 16613
[292:52] Calculating protein q-values
[292:52] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[292:52] Quantification
[292:52] Precursors with scored PTMs at 1% FDR: 377 out of 391 considered
[292:52] Precursors with all scored PTM sites unoccupied at 1% FDR: 16236
[292:52] Precursors with PTMs localised (when required) with > 90% confidence: 368 out of 377

[292:52] File #10/12
[292:52] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[292:59] Pre-processing...
[293:00] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[293:00] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[293:01] RT window set to 0.69116
[293:01] IM window set to 0.0100853
[293:01] Recommended MS1 mass accuracy setting: 10 ppm
[293:02] Searching decoys
[293:02] Main search
[293:03] Removing low confidence identifications
[293:04] Removing interfering precursors
[293:05] Training neural networks on 19023 target and 12132 decoy PSMs
[293:10] Training neural networks on 19017 target and 11206 decoy PSMs
[293:16] Number of IDs at 0.01 FDR: 17262
[293:16] Precursors at 1% peptidoform FDR: 16382
[293:16] Calculating protein q-values
[293:16] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[293:16] Quantification
[293:16] Precursors with scored PTMs at 1% FDR: 364 out of 383 considered
[293:16] Precursors with all scored PTM sites unoccupied at 1% FDR: 16018
[293:16] Precursors with PTMs localised (when required) with > 90% confidence: 356 out of 364

[293:17] File #11/12
[293:17] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[293:24] Pre-processing...
[293:25] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[293:25] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[293:26] RT window set to 0.693378
[293:26] IM window set to 0.0101195
[293:26] Recommended MS1 mass accuracy setting: 11 ppm
[293:26] Searching decoys
[293:27] Main search
[293:28] Removing low confidence identifications
[293:29] Removing interfering precursors
[293:29] Training neural networks on 18952 target and 11865 decoy PSMs
[293:35] Training neural networks on 18943 target and 11037 decoy PSMs
[293:40] Number of IDs at 0.01 FDR: 17411
[293:40] Precursors at 1% peptidoform FDR: 16444
[293:40] Calculating protein q-values
[293:40] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[293:40] Quantification
[293:41] Precursors with scored PTMs at 1% FDR: 371 out of 384 considered
[293:41] Precursors with all scored PTM sites unoccupied at 1% FDR: 16073
[293:41] Precursors with PTMs localised (when required) with > 90% confidence: 359 out of 371

[293:41] File #12/12
[293:41] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[293:48] Pre-processing...
[293:49] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20948 precursors in range
[293:49] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[293:50] RT window set to 0.689486
[293:50] IM window set to 0.01
[293:50] Recommended MS1 mass accuracy setting: 10 ppm
[293:51] Searching decoys
[293:51] Main search
[293:52] Removing low confidence identifications
[293:53] Removing interfering precursors
[293:53] Training neural networks on 18900 target and 12057 decoy PSMs
[293:59] Training neural networks on 18890 target and 11006 decoy PSMs
[294:05] Number of IDs at 0.01 FDR: 17515
[294:05] Precursors at 1% peptidoform FDR: 16345
[294:05] Calculating protein q-values
[294:05] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[294:05] Quantification
[294:05] Precursors with scored PTMs at 1% FDR: 373 out of 389 considered
[294:05] Precursors with all scored PTM sites unoccupied at 1% FDR: 15972
[294:05] Precursors with PTMs localised (when required) with > 90% confidence: 365 out of 373

[294:05] Cross-run analysis
[294:05] Reading quantification information: 12 files
[294:06] Quantifying peptides
[294:39] Quantification parameters: 0.319864, 0.00239348, 0.0109332, 0.0264398, 0.148011, 0.0745616, 0.346277, 0.175705, 0.254208, 0.0150963, 0.144531, 0.0605959, 0.329766, 0.250238, 0.216754, 0.0140363
[294:55] Quantifying proteins
[294:55] Calculating q-values for protein and gene groups
[294:55] Calculating global q-values for protein and gene groups
[294:55] Protein groups with global q-value <= 0.01: 2626
[294:56] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[294:56] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.2.0/report.stats.tsv

