
DIA-NN 2.5.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Apr 12 2026 10:45:33
Current date and time: Thu Jul 16 16:37:26 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.5.0/diann-linux --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d --f /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d --fasta /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta --out /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report.tsv --temp /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0 --threads 100 --missed-cleavages 1 --min-pep-len 6 --max-pep-len 30 --mass-acc 15 --mass-acc-ms1 15 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 1 --max-pr-charge 5 --min-pr-mz 400 --max-pr-mz 1000 --min-fr-mz 100 --max-fr-mz 1700 --cut K*,R* --unimod4 --var-mod UniMod:35,15.994915,M --var-mods 1 --gen-spec-lib --fasta-search --reanalyse 

Thread number set to 100
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 1000
Min fragment m/z set to 100
Max fragment m/z set to 1700
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 1.5e-05 (MS2) and 1.5e-05 (MS1)
WARNING: FASTA digest mode enabled and raw data are provided, turning on deep learning spectra/RT/IM prediction
WARNING: incorrect settings, the in silico-predicted library must be generated in a separate pipeline step and then used to process the raw data, now without activating FASTA digest
WARNING: peptidoform scoring enabled because variable modifications have been declared; to disable, use --no-peptidoforms
The following variable modifications will be localised: UniMod:35 

6 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:15] Processing FASTA
[0:18] Assembling elution groups
[0:32] 4902976 precursors generated
[0:32] Protein names missing for some isoforms
[0:32] Gene names missing for some isoforms
[0:32] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:49] [1:24] [5:28] [6:02] [6:05] [6:08] Saving the library to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report-lib.predicted.speclib
[6:12] Initialising library
[8:05] Loading spectral library /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report-lib.predicted.speclib
[8:34] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[8:49] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 4902976 precursors in 2602499 elution groups (targets and decoys).
[8:49] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[8:52] Annotating library proteins with information from the FASTA database
[8:53] Protein names missing for some isoforms
[8:53] Gene names missing for some isoforms
[8:53] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[9:47] Initialising library

First pass: generating a spectral library from DIA data

[12:05] File #1/6
[12:05] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d
[19:39] Pre-processing...
[19:45] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 4902976 precursors in range
[19:46] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[22:39] RT window set to 3.72467
[22:39] IM window set to 0.0439005
[22:39] Peak width: 3.892
[22:39] Scan window radius set to 8
[22:40] Recommended MS1 mass accuracy setting: 11 ppm
[24:25] Searching decoys
[36:46] Main search
[51:26] Removing low confidence identifications
[52:13] Removing interfering precursors
[52:26] Training neural networks on 223071 target and 168051 decoy PSMs
[53:38] Training neural networks on 223071 target and 165375 decoy PSMs
[54:36] Precursors at 1% peptidoform FDR: 94678
[54:38] Number of IDs at 0.01 FDR: 98457
[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
[54:45] Precursors with scored PTMs at 1% FDR: 1084 out of 1248 considered
[54:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 93594
[54:45] Precursors with PTMs localised (when required) with > 90% confidence: 1048 out of 1084
[54:46] Quantification information saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_HYE_diaPASEF_ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494_d.quant

[54:46] File #2/6
[54:46] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d
[55:52] Pre-processing...
[55:55] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 4902976 precursors in range
[55:56] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[56:49] RT window set to 2.76132
[56:49] IM window set to 0.0430446
[56:49] Recommended MS1 mass accuracy setting: 12 ppm
[57:11] Searching decoys
[61:13] Main search
[79:34] Removing low confidence identifications
[80:56] Removing interfering precursors
[81:37] Training neural networks on 235939 target and 183713 decoy PSMs
[83:56] Training neural networks on 235939 target and 181661 decoy PSMs
[86:01] Precursors at 1% peptidoform FDR: 99378
[86:07] Number of IDs at 0.01 FDR: 102978
[86:07] Calculating protein q-values
[86:10] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[86:11] Quantification
[86:23] Precursors with scored PTMs at 1% FDR: 845 out of 1000 considered
[86:23] Precursors with all scored PTM sites unoccupied at 1% FDR: 98533
[86:23] Precursors with PTMs localised (when required) with > 90% confidence: 815 out of 845
[86:30] Quantification information saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_HYE_diaPASEF_ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500_d.quant

[86:30] File #3/6
[86:30] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d
[88:04] Pre-processing...
[88:08] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 4902976 precursors in range
[88:10] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[89:45] RT window set to 3.55346
[89:45] IM window set to 0.0430748
[89:45] Recommended MS1 mass accuracy setting: 11 ppm
[90:37] Searching decoys
[94:13] Main search
[101:09] Removing low confidence identifications
[101:55] Removing interfering precursors
[102:16] Training neural networks on 240603 target and 187719 decoy PSMs
[103:16] Training neural networks on 240603 target and 185410 decoy PSMs
[103:43] Precursors at 1% peptidoform FDR: 99722
[103:44] Number of IDs at 0.01 FDR: 102961
[103:44] Calculating protein q-values
[103:45] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[103:45] Quantification
[103:47] Precursors with scored PTMs at 1% FDR: 1050 out of 1186 considered
[103:47] Precursors with all scored PTM sites unoccupied at 1% FDR: 98672
[103:47] Precursors with PTMs localised (when required) with > 90% confidence: 1013 out of 1050
[103:49] Quantification information saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_HYE_diaPASEF_ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506_d.quant

[103:49] File #4/6
[103:49] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d
[104:27] Pre-processing...
[104:28] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 4902976 precursors in range
[104:29] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[105:00] RT window set to 2.76893
[105:00] IM window set to 0.0430662
[105:00] Recommended MS1 mass accuracy setting: 11 ppm
[105:12] Searching decoys
[107:07] Main search
[121:21] Removing low confidence identifications
[122:27] Removing interfering precursors
[122:55] Training neural networks on 216218 target and 163688 decoy PSMs
[124:43] Training neural networks on 216218 target and 159775 decoy PSMs
[126:09] Precursors at 1% peptidoform FDR: 94798
[126:14] Number of IDs at 0.01 FDR: 98206
[126:14] Calculating protein q-values
[126:17] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[126:17] Quantification
[126:26] Precursors with scored PTMs at 1% FDR: 737 out of 941 considered
[126:26] Precursors with all scored PTM sites unoccupied at 1% FDR: 94061
[126:26] Precursors with PTMs localised (when required) with > 90% confidence: 712 out of 737
[126:30] Quantification information saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_HYE_diaPASEF_ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496_d.quant

[126:31] File #5/6
[126:31] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d
[128:32] Pre-processing...
[128:37] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 4902976 precursors in range
[128:39] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[130:23] RT window set to 2.85521
[130:23] IM window set to 0.0435777
[130:23] Recommended MS1 mass accuracy setting: 11 ppm
[131:18] Searching decoys
[138:04] Main search
[150:29] Removing low confidence identifications
[151:17] Removing interfering precursors
[151:34] Training neural networks on 235243 target and 179358 decoy PSMs
[152:54] Training neural networks on 235243 target and 177852 decoy PSMs
[154:06] Precursors at 1% peptidoform FDR: 97258
[154:08] Number of IDs at 0.01 FDR: 100864
[154:09] Calculating protein q-values
[154:10] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[154:10] Quantification
[154:14] Precursors with scored PTMs at 1% FDR: 724 out of 929 considered
[154:14] Precursors with all scored PTM sites unoccupied at 1% FDR: 96534
[154:14] Precursors with PTMs localised (when required) with > 90% confidence: 706 out of 724
[154:16] Quantification information saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_HYE_diaPASEF_ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502_d.quant

[154:16] File #6/6
[154:16] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d
[155:27] Pre-processing...
[155:30] 4348 MS1 and 104343 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 4902976 precursors in range
[155:31] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[156:36] RT window set to 2.70358
[156:36] IM window set to 0.0426421
[156:37] Recommended MS1 mass accuracy setting: 11 ppm
[157:04] Searching decoys
[162:41] Main search
[173:50] Removing low confidence identifications
[174:36] Removing interfering precursors
[174:53] Training neural networks on 232986 target and 178004 decoy PSMs
[175:52] Training neural networks on 232986 target and 176254 decoy PSMs
[176:54] Precursors at 1% peptidoform FDR: 98273
[176:57] Number of IDs at 0.01 FDR: 102047
[176:57] Calculating protein q-values
[176:58] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[176:58] Quantification
[177:02] Precursors with scored PTMs at 1% FDR: 751 out of 918 considered
[177:02] Precursors with all scored PTM sites unoccupied at 1% FDR: 97522
[177:02] Precursors with PTMs localised (when required) with > 90% confidence: 726 out of 751
[177:05] Quantification information saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/_public_local_ProteoBench_HYE_diaPASEF_ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508_d.quant

[177:05] Cross-run analysis
[177:05] Reading quantification information: 6 files
[177:28] Target precursors at 1% global q-value: 127441
[177:29] Quantifying peptides
[177:46] Assembling protein groups
[177:49] Quantifying proteins
[177:49] Calculating q-values for protein and gene groups
[177:55] Calculating global q-values for protein and gene groups
[177:55] Protein groups with global q-value <= 0.01: 11938
[178:00] Compressed report saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[178:00] Stats report saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report-first-pass.stats.tsv
[178:00] Generating spectral library:
[178:04] 139589 target and 7860 decoy precursors saved
WARNING: 7452 precursors without any fragments annotated were skipped
[178:05] Spectral library saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report-lib.parquet

[178:07] Loading spectral library /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report-lib.parquet
[178:09] Spectral library loaded: 18025 protein isoforms, 17894 protein groups and 147449 precursors in 135199 elution groups (targets and decoys).
[178:10] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[178:10] Annotating library proteins with information from the FASTA database
[178:10] Protein names missing for some isoforms
[178:10] Gene names missing for some isoforms
[178:10] Library contains 18015 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[178:10] Initialising library
[178:13] Saving the library to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report-lib.parquet.skyline.speclib


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

[178:13] File #1/6
[178:13] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d
[179:35] Pre-processing...
[179:38] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 139589 precursors in range
[179:38] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[179:43] RT window set to 0.940742
[179:43] IM window set to 0.01
[179:43] Recommended MS1 mass accuracy setting: 12 ppm
[179:44] Searching decoys
[179:49] Main search
[179:58] Removing low confidence identifications
[180:07] Removing interfering precursors
[180:09] Training neural networks on 123497 target and 73174 decoy PSMs
[180:45] Training neural networks on 123422 target and 66182 decoy PSMs
[181:21] Precursors at 1% peptidoform FDR: 103097
[181:23] Number of IDs at 0.01 FDR: 106227
[181:23] Calculating protein q-values
[181:23] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[181:23] Quantification
[181:30] Precursors with scored PTMs at 1% FDR: 909 out of 1021 considered
[181:30] Precursors with all scored PTM sites unoccupied at 1% FDR: 102508
[181:30] Precursors with PTMs localised (when required) with > 90% confidence: 891 out of 909

[181:32] File #2/6
[181:32] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d
[184:26] Pre-processing...
[184:32] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 139589 precursors in range
[184:32] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[184:45] RT window set to 0.940183
[184:45] IM window set to 0.01
[184:45] Recommended MS1 mass accuracy setting: 12 ppm
[184:49] Searching decoys
[184:57] Main search
[185:14] Removing low confidence identifications
[185:34] Removing interfering precursors
[185:42] Training neural networks on 124358 target and 73242 decoy PSMs
[186:41] Training neural networks on 124278 target and 66605 decoy PSMs
[187:36] Precursors at 1% peptidoform FDR: 104716
[187:38] Number of IDs at 0.01 FDR: 108399
[187:38] Calculating protein q-values
[187:38] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[187:38] Quantification
[187:45] Precursors with scored PTMs at 1% FDR: 890 out of 1005 considered
[187:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 104483
[187:45] Precursors with PTMs localised (when required) with > 90% confidence: 872 out of 890

[187:48] File #3/6
[187:48] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d
[189:33] Pre-processing...
[189:38] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 139589 precursors in range
[189:38] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[189:42] RT window set to 0.939863
[189:42] IM window set to 0.01
[189:42] Recommended MS1 mass accuracy setting: 12 ppm
[189:45] Searching decoys
[189:51] Main search
[190:02] Removing low confidence identifications
[190:14] Removing interfering precursors
[190:17] Training neural networks on 123839 target and 72784 decoy PSMs
[191:06] Training neural networks on 123800 target and 66218 decoy PSMs
[191:55] Precursors at 1% peptidoform FDR: 104229
[191:57] Number of IDs at 0.01 FDR: 107141
[191:57] Calculating protein q-values
[191:57] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[191:57] Quantification
[192:03] Precursors with scored PTMs at 1% FDR: 906 out of 1001 considered
[192:03] Precursors with all scored PTM sites unoccupied at 1% FDR: 103477
[192:03] Precursors with PTMs localised (when required) with > 90% confidence: 887 out of 906

[192:05] File #4/6
[192:05] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d
[193:49] Pre-processing...
[193:53] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 139589 precursors in range
[193:53] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[194:01] RT window set to 0.938542
[194:01] IM window set to 0.01
[194:01] Recommended MS1 mass accuracy setting: 11 ppm
[194:04] Searching decoys
[194:10] Main search
[194:21] Removing low confidence identifications
[194:32] Removing interfering precursors
[194:36] Training neural networks on 123261 target and 72256 decoy PSMs
[195:24] Training neural networks on 123185 target and 65274 decoy PSMs
[196:06] Precursors at 1% peptidoform FDR: 104219
[196:06] Number of IDs at 0.01 FDR: 107311
[196:06] Calculating protein q-values
[196:06] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[196:06] Quantification
[196:11] Precursors with scored PTMs at 1% FDR: 896 out of 1013 considered
[196:11] Precursors with all scored PTM sites unoccupied at 1% FDR: 103781
[196:11] Precursors with PTMs localised (when required) with > 90% confidence: 883 out of 896

[196:13] File #5/6
[196:13] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d
[198:07] Pre-processing...
[198:12] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 139589 precursors in range
[198:12] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[198:21] RT window set to 0.936051
[198:21] IM window set to 0.01
[198:21] Recommended MS1 mass accuracy setting: 11 ppm
[198:23] Searching decoys
[198:30] Main search
[198:42] Removing low confidence identifications
[198:55] Removing interfering precursors
[199:00] Training neural networks on 123227 target and 72730 decoy PSMs
[199:47] Training neural networks on 123176 target and 65448 decoy PSMs
[200:36] Precursors at 1% peptidoform FDR: 103822
[200:37] Number of IDs at 0.01 FDR: 106840
[200:37] Calculating protein q-values
[200:37] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[200:37] Quantification
[200:44] Precursors with scored PTMs at 1% FDR: 878 out of 977 considered
[200:44] Precursors with all scored PTM sites unoccupied at 1% FDR: 103418
[200:44] Precursors with PTMs localised (when required) with > 90% confidence: 862 out of 878

[200:48] File #6/6
[200:48] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d
[202:31] Pre-processing...
[202:35] 4348 MS1 and 104343 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 139589 precursors in range
[202:35] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[202:43] RT window set to 0.939773
[202:43] IM window set to 0.01
[202:43] Recommended MS1 mass accuracy setting: 11 ppm
[202:45] Searching decoys
[202:52] Main search
[203:03] Removing low confidence identifications
[203:13] Removing interfering precursors
[203:17] Training neural networks on 122363 target and 74369 decoy PSMs
[204:03] Training neural networks on 122321 target and 69712 decoy PSMs
[204:46] Precursors at 1% peptidoform FDR: 102826
[204:47] Number of IDs at 0.01 FDR: 105836
[204:47] Calculating protein q-values
[204:47] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[204:47] Quantification
[204:52] Precursors with scored PTMs at 1% FDR: 853 out of 954 considered
[204:52] Precursors with all scored PTM sites unoccupied at 1% FDR: 102295
[204:52] Precursors with PTMs localised (when required) with > 90% confidence: 836 out of 853

[204:54] Cross-run analysis
[204:54] Reading quantification information: 6 files
[205:03] Target precursors at 1% global q-value: 119701
[205:04] Quantifying peptides
[209:22] Quantification parameters: 0.306416, 0.00131457, 0.00311687, 0.0934802, 0.126904, 0.114477, 0.175899, 0.0140795, 0.0143617, 0.0862917, 0.0807833, 0.0835295, 0.179665, 0.0879471, 0.0954498, 0.0120413
[209:35] Quantifying proteins
[209:36] Calculating q-values for protein and gene groups
[209:37] Calculating global q-values for protein and gene groups
[209:37] Protein groups with global q-value <= 0.01: 11465
[209:45] Compressed report saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[209:45] Stats report saved to /home/robbe/PB_output/results/diaPASEFManuscriptMBR/HYE_diaPASEF/diann_v2.5.0/report.stats.tsv

