
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 Apr 30 11:45:10 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/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report.tsv --threads 32 --missed-cleavages 2 --min-pep-len 7 --max-pep-len 30 --mass-acc 20 --mass-acc-ms1 20 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 2 --max-pr-charge 4 --min-pr-mz 400 --max-pr-mz 1200 --min-fr-mz 200 --max-fr-mz 2000 --unimod4 --var-mod UniMod:35,15.994915,M --gen-spec-lib --fasta-search --reanalyse 

Thread number set to 32
Maximum number of missed cleavages set to 2
Min peptide length set to 7
Max peptide length set to 30
Output will be filtered at 0.01 FDR
Output will be filtered at 0.01 protein-level FDR
Min precursor charge set to 2
Max precursor charge set to 4
Min precursor m/z set to 400
Max precursor m/z set to 1200
Min fragment m/z set to 200
Max fragment m/z set to 2000
Cysteine carbamidomethylation enabled as a fixed modification
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
A spectral library will be generated
DIA-NN will carry out FASTA digest for in silico lib generation
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 

6 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:06] Processing FASTA
[0:09] Assembling elution groups
[0:17] 8103720 precursors generated
[0:17] Protein names missing for some isoforms
[0:17] Gene names missing for some isoforms
[0:17] Library contains 31680 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:23] [0:37] [7:52] [8:42] [8:45] [8:49] Saving the library to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report-lib.predicted.speclib
[8:55] Initialising library
[9:11] Loading spectral library /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report-lib.predicted.speclib
[9:14] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[9:16] Spectral library loaded: 31832 protein isoforms, 43199 protein groups and 8103720 precursors in 3825450 elution groups (targets and decoys).
[9:16] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[9:16] Annotating library proteins with information from the FASTA database
[9:16] Protein names missing for some isoforms
[9:16] Gene names missing for some isoforms
[9:16] Library contains 31680 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[9:23] Initialising library

First pass: generating a spectral library from DIA data

[9:38] File #1/6
[9:38] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d
WARNING: for the vast majority of timsTOF datasets it is better to manually fix both the MS1 and MS2 mass accuracies to 10-15 ppm
[10:44] Pre-processing...
[10:50] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[10:51] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[12:35] RT window set to 2.50808
[12:35] IM window set to 0.0433049
[12:35] Peak width: 4.068
[12:35] Scan window radius set to 8
[12:35] Recommended MS1 mass accuracy setting: 11 ppm
[13:20] Searching decoys
[22:13] Main search
[39:25] Removing low confidence identifications
[40:02] Removing interfering precursors
[40:13] Training neural networks on 192048 target and 145619 decoy PSMs
[40:55] Training neural networks on 192048 target and 142016 decoy PSMs
[41:36] Precursors at 1% peptidoform FDR: 92893
[41:38] Number of IDs at 0.01 FDR: 95857
[41:38] Calculating protein q-values
[41:38] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[41:38] Quantification
[41:43] Precursors with scored PTMs at 1% FDR: 760 out of 935 considered
[41:43] Precursors with all scored PTM sites unoccupied at 1% FDR: 92133
[41:43] Precursors with PTMs localised (when required) with > 90% confidence: 738 out of 760
[41:44] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d.quant

[41:44] File #2/6
[41:44] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d
[42:45] Pre-processing...
[42:50] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[42:51] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[44:24] RT window set to 2.59168
[44:24] IM window set to 0.0432488
[44:24] Recommended MS1 mass accuracy setting: 11 ppm
[45:07] Searching decoys
[53:52] Main search
[71:09] Removing low confidence identifications
[71:49] Removing interfering precursors
[72:00] Training neural networks on 197520 target and 150159 decoy PSMs
[72:44] Training neural networks on 197520 target and 147002 decoy PSMs
[73:25] Precursors at 1% peptidoform FDR: 96525
[73:27] Number of IDs at 0.01 FDR: 99441
[73:27] Calculating protein q-values
[73:27] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[73:27] Quantification
[73:31] Precursors with scored PTMs at 1% FDR: 917 out of 1068 considered
[73:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 95608
[73:31] Precursors with PTMs localised (when required) with > 90% confidence: 887 out of 917
[73:32] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d.quant

[73:32] File #3/6
[73:32] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d
[74:35] Pre-processing...
[74:40] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[74:41] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[76:15] RT window set to 2.67922
[76:15] IM window set to 0.0418055
[76:15] Recommended MS1 mass accuracy setting: 12 ppm
[76:59] Searching decoys
[85:47] Main search
[103:00] Removing low confidence identifications
[103:37] Removing interfering precursors
[103:48] Training neural networks on 201495 target and 153370 decoy PSMs
[104:37] Training neural networks on 201495 target and 149544 decoy PSMs
[105:20] Precursors at 1% peptidoform FDR: 96098
[105:21] Number of IDs at 0.01 FDR: 99150
[105:21] Calculating protein q-values
[105:22] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[105:22] Quantification
[105:25] Precursors with scored PTMs at 1% FDR: 698 out of 888 considered
[105:25] Precursors with all scored PTM sites unoccupied at 1% FDR: 95400
[105:25] Precursors with PTMs localised (when required) with > 90% confidence: 669 out of 698
[105:26] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d.quant

[105:27] File #4/6
[105:27] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d
[106:28] Pre-processing...
[106:33] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[106:34] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[108:04] RT window set to 2.5651
[108:04] IM window set to 0.0411208
[108:04] Recommended MS1 mass accuracy setting: 12 ppm
[108:44] Searching decoys
[117:08] Main search
[133:15] Removing low confidence identifications
[133:51] Removing interfering precursors
[134:01] Training neural networks on 191784 target and 143747 decoy PSMs
[134:43] Training neural networks on 191784 target and 139474 decoy PSMs
[135:20] Precursors at 1% peptidoform FDR: 93304
[135:21] Number of IDs at 0.01 FDR: 96042
[135:21] Calculating protein q-values
[135:22] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[135:22] Quantification
[135:25] Precursors with scored PTMs at 1% FDR: 707 out of 892 considered
[135:25] Precursors with all scored PTM sites unoccupied at 1% FDR: 92597
[135:25] Precursors with PTMs localised (when required) with > 90% confidence: 685 out of 707
[135:26] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d.quant

[135:26] File #5/6
[135:26] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d
[136:27] Pre-processing...
[136:32] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[136:32] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[138:00] RT window set to 2.54092
[138:00] IM window set to 0.0423338
[138:00] Recommended MS1 mass accuracy setting: 12 ppm
[138:41] Searching decoys
[146:52] Main search
[163:01] Removing low confidence identifications
[163:37] Removing interfering precursors
[163:47] Training neural networks on 184946 target and 139374 decoy PSMs
[164:29] Training neural networks on 184946 target and 135236 decoy PSMs
[165:03] Precursors at 1% peptidoform FDR: 93641
[165:04] Number of IDs at 0.01 FDR: 96619
[165:04] Calculating protein q-values
[165:05] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[165:05] Quantification
[165:08] Precursors with scored PTMs at 1% FDR: 710 out of 888 considered
[165:08] Precursors with all scored PTM sites unoccupied at 1% FDR: 92931
[165:08] Precursors with PTMs localised (when required) with > 90% confidence: 691 out of 710
[165:09] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d.quant

[165:10] File #6/6
[165:10] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d
[166:12] Pre-processing...
[166:17] 4348 MS1 and 104343 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 7127359 precursors in range
[166:18] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[167:47] RT window set to 2.74225
[167:47] IM window set to 0.0425039
[167:47] Recommended MS1 mass accuracy setting: 11 ppm
[168:30] Searching decoys
[176:54] Main search
[193:22] Removing low confidence identifications
[193:57] Removing interfering precursors
[194:07] Training neural networks on 193268 target and 146669 decoy PSMs
[194:50] Training neural networks on 193268 target and 143321 decoy PSMs
[195:24] Precursors at 1% peptidoform FDR: 95772
[195:25] Number of IDs at 0.01 FDR: 98856
[195:25] Calculating protein q-values
[195:25] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[195:25] Quantification
[195:29] Precursors with scored PTMs at 1% FDR: 712 out of 876 considered
[195:29] Precursors with all scored PTM sites unoccupied at 1% FDR: 95060
[195:29] Precursors with PTMs localised (when required) with > 90% confidence: 689 out of 712
[195:30] Quantification information saved to /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d.quant

[195:30] Cross-run analysis
[195:30] Reading quantification information: 6 files
[195:52] Target precursors at 1% global q-value: 122410
[195:52] Quantifying peptides
[196:02] Assembling protein groups
[196:03] Quantifying proteins
[196:03] Calculating q-values for protein and gene groups
[196:05] Calculating global q-values for protein and gene groups
[196:05] Protein groups with global q-value <= 0.01: 11728
[196:08] Compressed report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[196:08] Stats report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report-first-pass.stats.tsv
[196:08] Generating spectral library:
[196:11] 134082 target and 7583 decoy precursors saved
WARNING: 5665 precursors without any fragments annotated were skipped
[196:11] Spectral library saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report-lib.parquet

[196:12] Loading spectral library /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report-lib.parquet
[196:14] Spectral library loaded: 17714 protein isoforms, 17562 protein groups and 141665 precursors in 130270 elution groups (targets and decoys).
[196:14] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[196:14] Annotating library proteins with information from the FASTA database
[196:14] Gene names missing for some isoforms
[196:14] Library contains 17704 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[196:14] Initialising library
[196:15] Saving the library to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report-lib.parquet.skyline.speclib


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

[196:15] File #1/6
[196:15] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_01_11494.d
[197:01] Pre-processing...
[197:04] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 134082 precursors in range
[197:04] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[197:08] RT window set to 0.944007
[197:08] IM window set to 0.01
[197:08] Recommended MS1 mass accuracy setting: 12 ppm
[197:09] Searching decoys
[197:14] Main search
[197:23] Removing low confidence identifications
[197:30] Removing interfering precursors
[197:31] Training neural networks on 118459 target and 68500 decoy PSMs
[197:50] Training neural networks on 118382 target and 62159 decoy PSMs
[198:07] Precursors at 1% peptidoform FDR: 98538
[198:08] Number of IDs at 0.01 FDR: 101839
[198:08] Calculating protein q-values
[198:08] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[198:08] Quantification
[198:10] Precursors with scored PTMs at 1% FDR: 743 out of 850 considered
[198:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 98057
[198:10] Precursors with PTMs localised (when required) with > 90% confidence: 727 out of 743

[198:11] File #2/6
[198:11] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_02_11500.d
[198:51] Pre-processing...
[198:54] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 134082 precursors in range
[198:54] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[198:56] RT window set to 0.942016
[198:56] IM window set to 0.01
[198:56] Recommended MS1 mass accuracy setting: 11 ppm
[198:57] Searching decoys
[199:02] Main search
[199:11] Removing low confidence identifications
[199:18] Removing interfering precursors
[199:19] Training neural networks on 119045 target and 69481 decoy PSMs
[199:39] Training neural networks on 118985 target and 62724 decoy PSMs
[199:58] Precursors at 1% peptidoform FDR: 99543
[199:58] Number of IDs at 0.01 FDR: 102435
[199:58] Calculating protein q-values
[199:58] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[199:58] Quantification
[200:01] Precursors with scored PTMs at 1% FDR: 747 out of 851 considered
[200:01] Precursors with all scored PTM sites unoccupied at 1% FDR: 98945
[200:01] Precursors with PTMs localised (when required) with > 90% confidence: 734 out of 747

[200:02] File #3/6
[200:02] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_A_Sample_Alpha_03_11506.d
[200:43] Pre-processing...
[200:46] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 134082 precursors in range
[200:46] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[200:48] RT window set to 0.940176
[200:48] IM window set to 0.01
[200:48] Recommended MS1 mass accuracy setting: 11 ppm
[200:49] Searching decoys
[200:54] Main search
[201:04] Removing low confidence identifications
[201:10] Removing interfering precursors
[201:11] Training neural networks on 119031 target and 69509 decoy PSMs
[201:31] Training neural networks on 118963 target and 62655 decoy PSMs
[201:50] Precursors at 1% peptidoform FDR: 99326
[201:50] Number of IDs at 0.01 FDR: 102900
[201:50] Calculating protein q-values
[201:50] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[201:50] Quantification
[201:52] Precursors with scored PTMs at 1% FDR: 753 out of 848 considered
[201:52] Precursors with all scored PTM sites unoccupied at 1% FDR: 99019
[201:52] Precursors with PTMs localised (when required) with > 90% confidence: 734 out of 753

[201:53] File #4/6
[201:53] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_01_11496.d
[202:33] Pre-processing...
[202:36] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 134082 precursors in range
[202:36] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[202:38] RT window set to 0.940509
[202:38] IM window set to 0.01
[202:38] Recommended MS1 mass accuracy setting: 11 ppm
[202:38] Searching decoys
[202:43] Main search
[202:53] Removing low confidence identifications
[202:59] Removing interfering precursors
[203:00] Training neural networks on 118446 target and 68233 decoy PSMs
[203:17] Training neural networks on 118378 target and 61965 decoy PSMs
[203:32] Precursors at 1% peptidoform FDR: 99419
[203:32] Number of IDs at 0.01 FDR: 102221
[203:32] Calculating protein q-values
[203:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[203:32] Quantification
[203:34] Precursors with scored PTMs at 1% FDR: 745 out of 845 considered
[203:34] Precursors with all scored PTM sites unoccupied at 1% FDR: 98739
[203:34] Precursors with PTMs localised (when required) with > 90% confidence: 734 out of 745

[203:35] File #5/6
[203:35] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_02_11502.d
[204:14] Pre-processing...
[204:17] 4348 MS1 and 104340 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 134082 precursors in range
[204:17] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[204:19] RT window set to 0.937348
[204:19] IM window set to 0.01
[204:19] Recommended MS1 mass accuracy setting: 11 ppm
[204:19] Searching decoys
[204:24] Main search
[204:34] Removing low confidence identifications
[204:40] Removing interfering precursors
[204:41] Training neural networks on 118472 target and 68449 decoy PSMs
[204:58] Training neural networks on 118371 target and 62124 decoy PSMs
[205:14] Precursors at 1% peptidoform FDR: 99337
[205:15] Number of IDs at 0.01 FDR: 102440
[205:15] Calculating protein q-values
[205:15] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[205:15] Quantification
[205:17] Precursors with scored PTMs at 1% FDR: 738 out of 848 considered
[205:17] Precursors with all scored PTM sites unoccupied at 1% FDR: 98860
[205:17] Precursors with PTMs localised (when required) with > 90% confidence: 724 out of 738

[205:17] File #6/6
[205:17] Loading run /public/local/ProteoBench/HYE_diaPASEF/ttSCP_diaPASEF_Condition_B_Sample_Alpha_03_11508.d
[205:57] Pre-processing...
[206:00] 4348 MS1 and 104343 MS2 scans in 4348 (inferred) and 4348 (encoded) cycles, 134082 precursors in range
[206:00] Calibrating with mass accuracies 24 (MS1), 25 (MS2)
[206:04] RT window set to 0.942457
[206:04] IM window set to 0.01
[206:04] Recommended MS1 mass accuracy setting: 11 ppm
[206:05] Searching decoys
[206:10] Main search
[206:19] Removing low confidence identifications
[206:25] Removing interfering precursors
[206:27] Training neural networks on 119034 target and 69175 decoy PSMs
[206:45] Training neural networks on 118977 target and 62644 decoy PSMs
[207:02] Precursors at 1% peptidoform FDR: 100402
[207:03] Number of IDs at 0.01 FDR: 104100
[207:03] Calculating protein q-values
[207:03] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[207:03] Quantification
[207:05] Precursors with scored PTMs at 1% FDR: 758 out of 869 considered
[207:05] Precursors with all scored PTM sites unoccupied at 1% FDR: 100364
[207:05] Precursors with PTMs localised (when required) with > 90% confidence: 744 out of 758

[207:06] Cross-run analysis
[207:06] Reading quantification information: 6 files
[207:08] Target precursors at 1% global q-value: 115262
[207:09] Quantifying peptides
[208:15] Quantification parameters: 0.301875, 0.00133726, 0.00279983, 0.141971, 0.173717, 0.163494, 0.16879, 0.0136205, 0.014316, 0.109956, 0.0875709, 0.0954603, 0.157199, 0.0719241, 0.0763941, 0.012036
[208:19] Quantifying proteins
[208:20] Calculating q-values for protein and gene groups
[208:20] Calculating global q-values for protein and gene groups
[208:20] Protein groups with global q-value <= 0.01: 11362
[208:23] Compressed report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[208:23] Stats report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_diaPASEF/diann_v2.5.0/report.stats.tsv

