DIA-NN 1.9.1 (Data-Independent Acquisition by Neural Networks)
Compiled on Jul 15 2024 09:42:01
Current date and time: Wed Apr 22 15:28:40 2026
Logical CPU cores: 128
/home/robbe/bin/diann-1.9.1/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/test_run/PYE_diaPASEF/diann_v1.9.1/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 

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
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: it is strongly recommended to first generate an in silico-predicted library in a separate pipeline step and then use it 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 scored: UniMod:35 

12 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:07] Processing FASTA
[0:15] Assembling elution groups
[0:24] 8103720 precursors generated
[0:25] Protein names missing for some isoforms
[0:25] Gene names missing for some isoforms
[0:25] Library contains 31680 proteins, and 0 genes
[0:32] [0:47] [6:30] [7:14] [7:17] [7:21] Saving the library to report-lib.predicted.speclib
[7:43] Initialising library
[8:00] Loading spectral library report-lib.predicted.speclib
[8:07] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[8:09] Spectral library loaded: 31832 protein isoforms, 43199 protein groups and 8103720 precursors in 3825450 elution groups.
[8:09] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[8:09] Annotating library proteins with information from the FASTA database
[8:10] Protein names missing for some isoforms
[8:10] Gene names missing for some isoforms
[8:10] Library contains 31680 proteins, and 0 genes
[8:19] [8:31] [14:04] [14:44] [14:47] [14:51] Saving the library to report-lib.predicted.speclib
[15:14] Initialising library

[15:27] File #1/12
[15:27] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d
WARNING: for most Slice/DIA-PASEF datasets it is better to manually fix both the MS1 and MS2 mass accuracies to values in the range 10-15 ppm
[15:30] 7931928 library precursors are potentially detectable
[15:31] Processing...
[20:02] RT window set to 1.75632
[20:02] Ion mobility window set to 0.0371972
[20:02] Peak width: 3.324
[20:02] Scan window radius set to 7
[20:02] Recommended MS1 mass accuracy setting: 12.9027 ppm
[26:15] Removing low confidence identifications
[27:49] Precursors at 1% peptidoform FDR: 6458
[27:50] Removing interfering precursors
[27:54] Training neural networks: 19801 targets, 11531 decoys
[27:57] Number of IDs at 0.01 FDR: 13048
[27:58] Precursors at 1% peptidoform FDR: 8553
[27:59] Calculating protein q-values
[27:59] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[27:59] Quantification
[28:00] Precursors with monitored PTMs at 1% FDR: 56 out of 4144 considered
[28:00] Unmodified precursors with monitored PTM sites at 1% FDR: 1296
[28:00] Precursors with PTMs localised (when required) with > 90% confidence: 56 out of 56
[28:00] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d.quant

[28:00] File #2/12
[28:00] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[28:03] 7931928 library precursors are potentially detectable
[28:05] Processing...
[31:52] RT window set to 1.54849
[31:52] Ion mobility window set to 0.0391883
[31:53] Recommended MS1 mass accuracy setting: 11.8074 ppm
[37:25] Removing low confidence identifications
[38:52] Precursors at 1% peptidoform FDR: 8515
[38:52] Removing interfering precursors
[38:57] Training neural networks: 27894 targets, 15599 decoys
[39:00] Number of IDs at 0.01 FDR: 16630
[39:01] Precursors at 1% peptidoform FDR: 10675
[39:02] Calculating protein q-values
[39:02] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[39:03] Quantification
[39:03] Precursors with monitored PTMs at 1% FDR: 74 out of 5832 considered
[39:03] Unmodified precursors with monitored PTM sites at 1% FDR: 1854
[39:03] Precursors with PTMs localised (when required) with > 90% confidence: 73 out of 74
[39:04] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d.quant

[39:04] File #3/12
[39:04] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[39:07] 7931928 library precursors are potentially detectable
[39:08] Processing...
[43:02] RT window set to 1.71393
[43:02] Ion mobility window set to 0.0386884
[43:02] Recommended MS1 mass accuracy setting: 13.6718 ppm
[48:51] Removing low confidence identifications
[50:25] Precursors at 1% peptidoform FDR: 8107
[50:26] Removing interfering precursors
[50:30] Training neural networks: 26370 targets, 14981 decoys
[50:33] Number of IDs at 0.01 FDR: 15827
[50:34] Precursors at 1% peptidoform FDR: 10301
[50:35] Calculating protein q-values
[50:35] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[50:35] Quantification
[50:36] Precursors with monitored PTMs at 1% FDR: 39 out of 5585 considered
[50:36] Unmodified precursors with monitored PTM sites at 1% FDR: 1679
[50:36] Precursors with PTMs localised (when required) with > 90% confidence: 37 out of 39
[50:37] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d.quant

[50:37] File #4/12
[50:37] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[50:40] 7931928 library precursors are potentially detectable
[50:41] Processing...
[54:47] RT window set to 1.64652
[54:47] Ion mobility window set to 0.0396996
[54:48] Recommended MS1 mass accuracy setting: 11.8121 ppm
[60:41] Removing low confidence identifications
[62:16] Precursors at 1% peptidoform FDR: 8456
[62:17] Removing interfering precursors
[62:22] Training neural networks: 27624 targets, 15823 decoys
[62:24] Number of IDs at 0.01 FDR: 16451
[62:26] Precursors at 1% peptidoform FDR: 11007
[62:26] Calculating protein q-values
[62:27] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[62:27] Quantification
[62:27] Precursors with monitored PTMs at 1% FDR: 31 out of 5516 considered
[62:27] Unmodified precursors with monitored PTM sites at 1% FDR: 1821
[62:27] Precursors with PTMs localised (when required) with > 90% confidence: 30 out of 31
[62:28] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d.quant

[62:28] File #5/12
[62:28] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[62:32] 7931928 library precursors are potentially detectable
[62:33] Processing...
[66:40] RT window set to 2.0814
[66:40] Ion mobility window set to 0.039203
[66:40] Recommended MS1 mass accuracy setting: 12.4113 ppm
[73:22] Removing low confidence identifications
[75:12] Precursors at 1% peptidoform FDR: 8614
[75:13] Removing interfering precursors
[75:17] Training neural networks: 26443 targets, 14944 decoys
[75:20] Number of IDs at 0.01 FDR: 16222
[75:21] Precursors at 1% peptidoform FDR: 10608
[75:22] Calculating protein q-values
[75:23] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[75:23] Quantification
[75:23] Precursors with monitored PTMs at 1% FDR: 73 out of 5369 considered
[75:23] Unmodified precursors with monitored PTM sites at 1% FDR: 1716
[75:23] Precursors with PTMs localised (when required) with > 90% confidence: 72 out of 73
[75:24] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d.quant

[75:24] File #6/12
[75:24] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[75:27] 7931928 library precursors are potentially detectable
[75:28] Processing...
[79:34] RT window set to 1.74973
[79:34] Ion mobility window set to 0.0378169
[79:35] Recommended MS1 mass accuracy setting: 13.0354 ppm
[85:24] Removing low confidence identifications
[86:59] Precursors at 1% peptidoform FDR: 8291
[87:00] Removing interfering precursors
[87:04] Training neural networks: 25597 targets, 14586 decoys
[87:07] Number of IDs at 0.01 FDR: 15716
[87:08] Precursors at 1% peptidoform FDR: 10481
[87:09] Calculating protein q-values
[87:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[87:09] Quantification
[87:10] Precursors with monitored PTMs at 1% FDR: 59 out of 5206 considered
[87:10] Unmodified precursors with monitored PTM sites at 1% FDR: 1709
[87:10] Precursors with PTMs localised (when required) with > 90% confidence: 59 out of 59
[87:10] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d.quant

[87:10] File #7/12
[87:10] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[87:13] 7931928 library precursors are potentially detectable
[87:15] Processing...
[91:50] RT window set to 1.46118
[91:50] Ion mobility window set to 0.0369919
[91:51] Recommended MS1 mass accuracy setting: 12.5717 ppm
[97:07] Removing low confidence identifications
[98:23] Precursors at 1% peptidoform FDR: 8006
[98:23] Removing interfering precursors
[98:28] Training neural networks: 25077 targets, 14213 decoys
[98:30] Number of IDs at 0.01 FDR: 15497
[98:32] Precursors at 1% peptidoform FDR: 10473
[98:33] Calculating protein q-values
[98:33] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[98:33] Quantification
[98:33] Precursors with monitored PTMs at 1% FDR: 54 out of 4974 considered
[98:33] Unmodified precursors with monitored PTM sites at 1% FDR: 1474
[98:33] Precursors with PTMs localised (when required) with > 90% confidence: 54 out of 54
[98:34] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d.quant

[98:34] File #8/12
[98:34] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[98:36] 7931928 library precursors are potentially detectable
[98:38] Processing...
[102:19] RT window set to 1.8887
[102:19] Ion mobility window set to 0.0394452
[102:20] Recommended MS1 mass accuracy setting: 13.3115 ppm
[108:03] Removing low confidence identifications
[109:33] Precursors at 1% peptidoform FDR: 8748
[109:34] Removing interfering precursors
[109:39] Training neural networks: 27673 targets, 15929 decoys
[109:41] Number of IDs at 0.01 FDR: 16629
[109:42] Precursors at 1% peptidoform FDR: 11257
[109:43] Calculating protein q-values
[109:44] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[109:44] Quantification
[109:44] Precursors with monitored PTMs at 1% FDR: 74 out of 5479 considered
[109:44] Unmodified precursors with monitored PTM sites at 1% FDR: 1690
[109:44] Precursors with PTMs localised (when required) with > 90% confidence: 74 out of 74
[109:45] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d.quant

[109:45] File #9/12
[109:45] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[109:48] 7931928 library precursors are potentially detectable
[109:49] Processing...
[113:45] RT window set to 1.83658
[113:45] Ion mobility window set to 0.0387109
[113:45] Recommended MS1 mass accuracy setting: 11.979 ppm
[119:39] Removing low confidence identifications
[121:14] Precursors at 1% peptidoform FDR: 8738
[121:15] Removing interfering precursors
[121:19] Training neural networks: 27378 targets, 15299 decoys
[121:22] Number of IDs at 0.01 FDR: 17224
[121:23] Precursors at 1% peptidoform FDR: 10703
[121:24] Calculating protein q-values
[121:24] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[121:24] Quantification
[121:25] Precursors with monitored PTMs at 1% FDR: 79 out of 5509 considered
[121:25] Unmodified precursors with monitored PTM sites at 1% FDR: 1549
[121:25] Precursors with PTMs localised (when required) with > 90% confidence: 79 out of 79
[121:25] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d.quant

[121:25] File #10/12
[121:25] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[121:28] 7931928 library precursors are potentially detectable
[121:30] Processing...
[125:27] RT window set to 1.45463
[125:27] Ion mobility window set to 0.0365843
[125:27] Recommended MS1 mass accuracy setting: 12.2334 ppm
[130:28] Removing low confidence identifications
[131:45] Precursors at 1% peptidoform FDR: 8950
[131:46] Removing interfering precursors
[131:50] Training neural networks: 28643 targets, 15889 decoys
[131:53] Number of IDs at 0.01 FDR: 17202
[131:54] Precursors at 1% peptidoform FDR: 10653
[131:55] Calculating protein q-values
[131:56] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[131:56] Quantification
[131:56] Precursors with monitored PTMs at 1% FDR: 77 out of 5559 considered
[131:56] Unmodified precursors with monitored PTM sites at 1% FDR: 1535
[131:56] Precursors with PTMs localised (when required) with > 90% confidence: 77 out of 77
[131:57] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d.quant

[131:57] File #11/12
[131:57] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[132:00] 7931928 library precursors are potentially detectable
[132:01] Processing...
[135:57] RT window set to 1.68825
[135:57] Ion mobility window set to 0.0378574
[135:58] Recommended MS1 mass accuracy setting: 12.3338 ppm
[141:32] Removing low confidence identifications
[142:58] Precursors at 1% peptidoform FDR: 8565
[142:59] Removing interfering precursors
[143:04] Training neural networks: 27213 targets, 15021 decoys
[143:06] Number of IDs at 0.01 FDR: 16975
[143:08] Precursors at 1% peptidoform FDR: 10818
[143:08] Calculating protein q-values
[143:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[143:09] Quantification
[143:09] Precursors with monitored PTMs at 1% FDR: 84 out of 5539 considered
[143:09] Unmodified precursors with monitored PTM sites at 1% FDR: 1544
[143:09] Precursors with PTMs localised (when required) with > 90% confidence: 84 out of 84
[143:10] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d.quant

[143:10] File #12/12
[143:10] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[143:13] 7931928 library precursors are potentially detectable
[143:14] Processing...
[148:04] RT window set to 1.87244
[148:04] Ion mobility window set to 0.0377153
[148:04] Recommended MS1 mass accuracy setting: 12.5389 ppm
[154:43] Removing low confidence identifications
[156:25] Precursors at 1% peptidoform FDR: 8712
[156:26] Removing interfering precursors
[156:30] Training neural networks: 27891 targets, 15675 decoys
[156:33] Number of IDs at 0.01 FDR: 17386
[156:34] Precursors at 1% peptidoform FDR: 11135
[156:36] Calculating protein q-values
[156:36] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[156:36] Quantification
[156:36] Precursors with monitored PTMs at 1% FDR: 106 out of 5682 considered
[156:36] Unmodified precursors with monitored PTM sites at 1% FDR: 1570
[156:36] Precursors with PTMs localised (when required) with > 90% confidence: 104 out of 106
[156:37] Quantification information saved to /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d.quant

[156:37] Cross-run analysis
[156:37] Reading quantification information: 12 files
[156:40] Quantifying peptides
[157:02] Quantification parameters: 0.316108, 0.00284987, 0.010976, 0.0460065, 0.130579, 0.116206, 0.414238, 0.0966702, 0.221276, 0.0388645, 0.12829, 0.099443, 0.372886, 0.250943, 0.204445, 0.0143182
[157:06] Assembling protein groups
[157:08] Quantifying proteins
[157:08] Calculating q-values for protein and gene groups
[157:11] Calculating global q-values for protein and gene groups
[157:12] Protein groups with global q-value <= 0.01: 15932
[157:13] Compressed report saved to /home/robbe/PB_output/results/test_run/PYE_diaPASEF/diann_v1.9.1/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[157:13] Writing report
[157:15] Report saved to /home/robbe/PB_output/results/test_run/PYE_diaPASEF/diann_v1.9.1/report.tsv.
[157:15] Stats report saved to /home/robbe/PB_output/results/test_run/PYE_diaPASEF/diann_v1.9.1/report.stats.tsv
[157:15] Generating spectral library:
[157:16] 43718 target and 440 decoy precursors saved
WARNING: 1590 precursors without any fragments annotated were skipped
[157:16] Spectral library saved to report-lib.parquet

