DIA-NN 1.9.2 (Data-Independent Acquisition by Neural Networks)
Compiled on Oct 31 2024 04:27:44
Current date and time: Tue Jun 23 20:09:15 2026
Logical CPU cores: 128
/home/robbe/bin/diann-1.9.2/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_v1.9.2/report.tsv --temp /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2 --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
A spectral library will be created from the DIA runs and used to reanalyse them; .quant files will only be saved to disk during the first step
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
[0:04] Processing FASTA
[0:09] Assembling elution groups
[0:15] 5697771 precursors generated
[0:15] Protein names missing for some isoforms
[0:15] Gene names missing for some isoforms
[0:15] Library contains 31685 proteins, and 0 genes
[0:19] [0:30] [10:29] [11:37] [11:40] [11:43] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report-lib.predicted.speclib
[11:49] Initialising library
[12:00] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report-lib.predicted.speclib
[12:03] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[12:04] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5697771 precursors in 2602499 elution groups.
[12:04] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[12:04] Annotating library proteins with information from the FASTA database
[12:04] Protein names missing for some isoforms
[12:04] Gene names missing for some isoforms
[12:04] Library contains 31685 proteins, and 0 genes
[12:08] Initialising library

First pass: generating a spectral library from DIA data

[12:20] File #1/12
[12:20] 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
[12:25] 5543758 library precursors are potentially detectable
[12:26] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[16:47] RT window set to 1.80363
[16:47] Ion mobility window set to 0.0371633
[16:47] Peak width: 3.224
[16:47] Scan window radius set to 7
[16:47] Recommended MS1 mass accuracy setting: 12.5395 ppm
[23:42] Removing low confidence identifications
[26:33] Precursors at 1% peptidoform FDR: 6675
[26:33] Removing interfering precursors
[26:36] Training neural networks on 35841 PSMs
[26:38] Number of IDs at 0.01 FDR: 11802
[26:39] Precursors at 1% peptidoform FDR: 9853
[26:40] Calculating protein q-values
[26:40] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[26:40] Quantification
[26:40] Precursors with monitored PTMs at 1% FDR: 79 out of 2226 considered
[26:40] Unmodified precursors with monitored PTM sites at 1% FDR: 1796
[26:40] Precursors with PTMs localised (when required) with > 90% confidence: 79 out of 79
[26:40] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R1_d.quant

[26:40] File #2/12
[26:40] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[26:45] 5543758 library precursors are potentially detectable
[26:46] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[30:56] RT window set to 1.65735
[30:56] Ion mobility window set to 0.0405048
[30:57] Recommended MS1 mass accuracy setting: 12.8887 ppm
[37:33] Removing low confidence identifications
[40:19] Precursors at 1% peptidoform FDR: 7956
[40:19] Removing interfering precursors
[40:23] Training neural networks on 40762 PSMs
[40:26] Number of IDs at 0.01 FDR: 13193
[40:27] Precursors at 1% peptidoform FDR: 10900
[40:28] Calculating protein q-values
[40:28] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[40:28] Quantification
[40:28] Precursors with monitored PTMs at 1% FDR: 117 out of 2597 considered
[40:28] Unmodified precursors with monitored PTM sites at 1% FDR: 1917
[40:28] Precursors with PTMs localised (when required) with > 90% confidence: 115 out of 117
[40:29] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R2_d.quant

[40:29] File #3/12
[40:29] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[40:34] 5543758 library precursors are potentially detectable
[40:35] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[45:30] RT window set to 2.05131
[45:30] Ion mobility window set to 0.0394521
[45:30] Recommended MS1 mass accuracy setting: 13.7338 ppm
[53:29] Removing low confidence identifications
[56:38] Precursors at 1% peptidoform FDR: 7520
[56:38] Removing interfering precursors
[56:41] Training neural networks on 38588 PSMs
[56:44] Number of IDs at 0.01 FDR: 12342
[56:44] Precursors at 1% peptidoform FDR: 10435
[56:45] Calculating protein q-values
[56:45] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[56:45] Quantification
[56:46] Precursors with monitored PTMs at 1% FDR: 46 out of 2355 considered
[56:46] Unmodified precursors with monitored PTM sites at 1% FDR: 1890
[56:46] Precursors with PTMs localised (when required) with > 90% confidence: 44 out of 46
[56:46] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R3_d.quant

[56:46] File #4/12
[56:46] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[56:52] 5543758 library precursors are potentially detectable
[56:53] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[61:24] RT window set to 1.67108
[61:24] Ion mobility window set to 0.0413063
[61:25] Recommended MS1 mass accuracy setting: 12.9676 ppm
[68:32] Removing low confidence identifications
[71:20] Precursors at 1% peptidoform FDR: 7846
[71:20] Removing interfering precursors
[71:24] Training neural networks on 42344 PSMs
[71:26] Number of IDs at 0.01 FDR: 13247
[71:27] Precursors at 1% peptidoform FDR: 11338
[71:27] Calculating protein q-values
[71:28] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[71:28] Quantification
[71:28] Precursors with monitored PTMs at 1% FDR: 69 out of 2528 considered
[71:28] Unmodified precursors with monitored PTM sites at 1% FDR: 2095
[71:28] Precursors with PTMs localised (when required) with > 90% confidence: 63 out of 69
[71:28] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R4_d.quant

[71:28] File #5/12
[71:28] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[71:34] 5543758 library precursors are potentially detectable
[71:35] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[76:06] RT window set to 1.61919
[76:06] Ion mobility window set to 0.040385
[76:06] Recommended MS1 mass accuracy setting: 12.6636 ppm
[83:08] Removing low confidence identifications
[85:48] Precursors at 1% peptidoform FDR: 8181
[85:48] Removing interfering precursors
[85:52] Training neural networks on 41288 PSMs
[85:54] Number of IDs at 0.01 FDR: 13147
[85:55] Precursors at 1% peptidoform FDR: 11067
[85:55] Calculating protein q-values
[85:56] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[85:56] Quantification
[85:56] Precursors with monitored PTMs at 1% FDR: 105 out of 2400 considered
[85:56] Unmodified precursors with monitored PTM sites at 1% FDR: 2058
[85:56] Precursors with PTMs localised (when required) with > 90% confidence: 102 out of 105
[85:56] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R5_d.quant

[85:56] File #6/12
[85:56] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[86:02] 5543758 library precursors are potentially detectable
[86:03] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[90:26] RT window set to 1.57855
[90:26] Ion mobility window set to 0.037551
[90:26] Recommended MS1 mass accuracy setting: 12.6749 ppm
[96:54] Removing low confidence identifications
[99:23] Precursors at 1% peptidoform FDR: 7816
[99:23] Removing interfering precursors
[99:27] Training neural networks on 39727 PSMs
[99:29] Number of IDs at 0.01 FDR: 12786
[99:30] Precursors at 1% peptidoform FDR: 10640
[99:31] Calculating protein q-values
[99:31] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[99:31] Quantification
[99:31] Precursors with monitored PTMs at 1% FDR: 80 out of 2463 considered
[99:31] Unmodified precursors with monitored PTM sites at 1% FDR: 1939
[99:31] Precursors with PTMs localised (when required) with > 90% confidence: 78 out of 80
[99:32] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R6_d.quant

[99:32] File #7/12
[99:32] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[99:37] 5543758 library precursors are potentially detectable
[99:37] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[104:11] RT window set to 1.57104
[104:11] Ion mobility window set to 0.0392727
[104:11] Recommended MS1 mass accuracy setting: 12.4022 ppm
[110:23] Removing low confidence identifications
[112:40] Precursors at 1% peptidoform FDR: 7505
[112:40] Removing interfering precursors
[112:44] Training neural networks on 39487 PSMs
[112:46] Number of IDs at 0.01 FDR: 13024
[112:47] Precursors at 1% peptidoform FDR: 10882
[112:47] Calculating protein q-values
[112:47] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[112:47] Quantification
[112:48] Precursors with monitored PTMs at 1% FDR: 28 out of 2240 considered
[112:48] Unmodified precursors with monitored PTM sites at 1% FDR: 1750
[112:48] Precursors with PTMs localised (when required) with > 90% confidence: 27 out of 28
[112:48] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R1_d.quant

[112:48] File #8/12
[112:48] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[112:53] 5543758 library precursors are potentially detectable
[112:54] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[117:02] RT window set to 1.90287
[117:02] Ion mobility window set to 0.0387823
[117:03] Recommended MS1 mass accuracy setting: 13.1516 ppm
[124:07] Removing low confidence identifications
[126:56] Precursors at 1% peptidoform FDR: 7778
[126:56] Removing interfering precursors
[127:00] Training neural networks on 41850 PSMs
[127:02] Number of IDs at 0.01 FDR: 13564
[127:03] Precursors at 1% peptidoform FDR: 10817
[127:04] Calculating protein q-values
[127:04] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[127:04] Quantification
[127:05] Precursors with monitored PTMs at 1% FDR: 86 out of 2392 considered
[127:05] Unmodified precursors with monitored PTM sites at 1% FDR: 1745
[127:05] Precursors with PTMs localised (when required) with > 90% confidence: 83 out of 86
[127:05] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R2_d.quant

[127:05] File #9/12
[127:05] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[127:10] 5543758 library precursors are potentially detectable
[127:11] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[131:54] RT window set to 1.60486
[131:54] Ion mobility window set to 0.038491
[131:54] Recommended MS1 mass accuracy setting: 12.8865 ppm
[138:24] Removing low confidence identifications
[140:52] Precursors at 1% peptidoform FDR: 8164
[140:53] Removing interfering precursors
[140:56] Training neural networks on 44473 PSMs
[140:59] Number of IDs at 0.01 FDR: 14087
[141:00] Precursors at 1% peptidoform FDR: 11090
[141:01] Calculating protein q-values
[141:01] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[141:01] Quantification
[141:01] Precursors with monitored PTMs at 1% FDR: 71 out of 2428 considered
[141:01] Unmodified precursors with monitored PTM sites at 1% FDR: 1857
[141:01] Precursors with PTMs localised (when required) with > 90% confidence: 67 out of 71
[141:02] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R3_d.quant

[141:02] File #10/12
[141:02] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[141:07] 5543758 library precursors are potentially detectable
[141:08] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[145:36] RT window set to 2.16162
[145:36] Ion mobility window set to 0.0414892
[145:36] Recommended MS1 mass accuracy setting: 12.4991 ppm
[154:29] Removing low confidence identifications
[157:50] Precursors at 1% peptidoform FDR: 8358
[157:50] Removing interfering precursors
[157:53] Training neural networks on 43383 PSMs
[157:56] Number of IDs at 0.01 FDR: 14058
[157:57] Precursors at 1% peptidoform FDR: 11480
[157:57] Calculating protein q-values
[157:57] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[157:57] Quantification
[157:58] Precursors with monitored PTMs at 1% FDR: 48 out of 2472 considered
[157:58] Unmodified precursors with monitored PTM sites at 1% FDR: 1897
[157:58] Precursors with PTMs localised (when required) with > 90% confidence: 47 out of 48
[157:58] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R4_d.quant

[157:58] File #11/12
[157:58] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[158:04] 5543758 library precursors are potentially detectable
[158:05] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[162:28] RT window set to 1.59207
[162:28] Ion mobility window set to 0.0402865
[162:28] Recommended MS1 mass accuracy setting: 13.1287 ppm
[168:50] Removing low confidence identifications
[171:18] Precursors at 1% peptidoform FDR: 7653
[171:18] Removing interfering precursors
[171:22] Training neural networks on 42898 PSMs
[171:24] Number of IDs at 0.01 FDR: 13977
[171:25] Precursors at 1% peptidoform FDR: 11680
[171:25] Calculating protein q-values
[171:25] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[171:25] Quantification
[171:26] Precursors with monitored PTMs at 1% FDR: 62 out of 2420 considered
[171:26] Unmodified precursors with monitored PTM sites at 1% FDR: 1916
[171:26] Precursors with PTMs localised (when required) with > 90% confidence: 56 out of 62
[171:26] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R5_d.quant

[171:26] File #12/12
[171:26] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[171:32] 5543758 library precursors are potentially detectable
[171:32] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[175:52] RT window set to 1.68238
[175:52] Ion mobility window set to 0.0406793
[175:52] Recommended MS1 mass accuracy setting: 13.2169 ppm
[182:36] Removing low confidence identifications
[185:05] Precursors at 1% peptidoform FDR: 8229
[185:05] Removing interfering precursors
[185:09] Training neural networks on 44474 PSMs
[185:11] Number of IDs at 0.01 FDR: 14184
[185:12] Precursors at 1% peptidoform FDR: 11720
[185:13] Calculating protein q-values
[185:13] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[185:13] Quantification
[185:14] Precursors with monitored PTMs at 1% FDR: 127 out of 2469 considered
[185:14] Unmodified precursors with monitored PTM sites at 1% FDR: 1936
[185:14] Precursors with PTMs localised (when required) with > 90% confidence: 124 out of 127
[185:14] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R6_d.quant

[185:14] Cross-run analysis
[185:14] Reading quantification information: 12 files
[185:16] Quantifying peptides
[185:23] Assembling protein groups
[185:24] Quantifying proteins
[185:24] Calculating q-values for protein and gene groups
[185:27] Calculating global q-values for protein and gene groups
[185:27] Protein groups with global q-value <= 0.01: 3346
[185:27] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[185:27] Writing report
[185:29] Report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report-first-pass.tsv.
[185:29] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report-first-pass.stats.tsv
[185:29] Generating spectral library:
[185:29] 20221 target and 193 decoy precursors saved
WARNING: 316 precursors without any fragments annotated were skipped
[185:29] Spectral library saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report-lib.parquet

[185:30] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report-lib.parquet
[185:30] Spectral library loaded: 3972 protein isoforms, 4008 protein groups and 20414 precursors in 19156 elution groups.
[185:30] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[185:30] Annotating library proteins with information from the FASTA database
[185:30] Gene names missing for some isoforms
[185:30] Library contains 3941 proteins, and 0 genes
[185:30] Initialising library
[185:30] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report-lib.parquet.skyline.speclib


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

[185:30] File #1/12
[185:30] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d
[185:34] 20221 library precursors are potentially detectable
[185:34] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[185:36] RT window set to 0.726765
[185:36] Ion mobility window set to 0.01
[185:36] Recommended MS1 mass accuracy setting: 12.7328 ppm
[185:37] Removing low confidence identifications
[185:38] Precursors at 1% peptidoform FDR: 11108
[185:38] Removing interfering precursors
[185:38] Training neural networks on 26948 PSMs
[185:39] Number of IDs at 0.01 FDR: 16692
[185:39] Precursors at 1% peptidoform FDR: 13568
[185:39] Calculating protein q-values
[185:39] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[185:39] Quantification
[185:39] Precursors with monitored PTMs at 1% FDR: 98 out of 3027 considered
[185:39] Unmodified precursors with monitored PTM sites at 1% FDR: 2419
[185:39] Precursors with PTMs localised (when required) with > 90% confidence: 96 out of 98

[185:39] File #2/12
[185:39] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[185:44] 20221 library precursors are potentially detectable
[185:44] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[185:46] RT window set to 0.719772
[185:46] Ion mobility window set to 0.0121178
[185:46] Recommended MS1 mass accuracy setting: 13.3273 ppm
[185:47] Removing low confidence identifications
[185:48] Precursors at 1% peptidoform FDR: 11869
[185:48] Removing interfering precursors
[185:48] Training neural networks on 27455 PSMs
[185:49] Number of IDs at 0.01 FDR: 17150
[185:50] Precursors at 1% peptidoform FDR: 13790
[185:50] Calculating protein q-values
[185:50] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[185:50] Quantification
[185:50] Precursors with monitored PTMs at 1% FDR: 106 out of 3105 considered
[185:50] Unmodified precursors with monitored PTM sites at 1% FDR: 2441
[185:50] Precursors with PTMs localised (when required) with > 90% confidence: 103 out of 106

[185:50] File #3/12
[185:50] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[185:54] 20221 library precursors are potentially detectable
[185:54] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[185:56] RT window set to 0.720828
[185:56] Ion mobility window set to 0.0107722
[185:56] Recommended MS1 mass accuracy setting: 12.872 ppm
[185:57] Removing low confidence identifications
[185:58] Precursors at 1% peptidoform FDR: 11841
[185:58] Removing interfering precursors
[185:58] Training neural networks on 27530 PSMs
[185:59] Number of IDs at 0.01 FDR: 16955
[185:59] Precursors at 1% peptidoform FDR: 13681
[185:59] Calculating protein q-values
[185:59] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[185:59] Quantification
[185:59] Precursors with monitored PTMs at 1% FDR: 112 out of 3075 considered
[185:59] Unmodified precursors with monitored PTM sites at 1% FDR: 2449
[185:59] Precursors with PTMs localised (when required) with > 90% confidence: 108 out of 112

[185:59] File #4/12
[185:59] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[186:05] 20221 library precursors are potentially detectable
[186:05] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[186:06] RT window set to 0.72348
[186:06] Ion mobility window set to 0.0108709
[186:06] Recommended MS1 mass accuracy setting: 12.8557 ppm
[186:08] Removing low confidence identifications
[186:08] Precursors at 1% peptidoform FDR: 12116
[186:09] Removing interfering precursors
[186:09] Training neural networks on 27626 PSMs
[186:09] Number of IDs at 0.01 FDR: 17477
[186:10] Precursors at 1% peptidoform FDR: 13879
[186:10] Calculating protein q-values
[186:10] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[186:10] Quantification
[186:10] Precursors with monitored PTMs at 1% FDR: 116 out of 3122 considered
[186:10] Unmodified precursors with monitored PTM sites at 1% FDR: 2483
[186:10] Precursors with PTMs localised (when required) with > 90% confidence: 112 out of 116

[186:10] File #5/12
[186:10] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[186:16] 20221 library precursors are potentially detectable
[186:16] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[186:17] RT window set to 0.708647
[186:17] Ion mobility window set to 0.0112461
[186:17] Recommended MS1 mass accuracy setting: 13.4644 ppm
[186:19] Removing low confidence identifications
[186:20] Precursors at 1% peptidoform FDR: 12273
[186:20] Removing interfering precursors
[186:20] Training neural networks on 27553 PSMs
[186:21] Number of IDs at 0.01 FDR: 17433
[186:21] Precursors at 1% peptidoform FDR: 13849
[186:21] Calculating protein q-values
[186:21] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[186:21] Quantification
[186:21] Precursors with monitored PTMs at 1% FDR: 109 out of 3109 considered
[186:21] Unmodified precursors with monitored PTM sites at 1% FDR: 2464
[186:21] Precursors with PTMs localised (when required) with > 90% confidence: 105 out of 109

[186:21] File #6/12
[186:21] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[186:26] 20221 library precursors are potentially detectable
[186:26] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[186:28] RT window set to 0.708291
[186:28] Ion mobility window set to 0.0108028
[186:28] Recommended MS1 mass accuracy setting: 13.2376 ppm
[186:30] Removing low confidence identifications
[186:31] Precursors at 1% peptidoform FDR: 11629
[186:31] Removing interfering precursors
[186:31] Training neural networks on 27499 PSMs
[186:31] Number of IDs at 0.01 FDR: 17020
[186:32] Precursors at 1% peptidoform FDR: 13720
[186:32] Calculating protein q-values
[186:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[186:32] Quantification
[186:32] Precursors with monitored PTMs at 1% FDR: 111 out of 3061 considered
[186:32] Unmodified precursors with monitored PTM sites at 1% FDR: 2436
[186:32] Precursors with PTMs localised (when required) with > 90% confidence: 107 out of 111

[186:32] File #7/12
[186:32] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[186:36] 20221 library precursors are potentially detectable
[186:36] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[186:37] RT window set to 0.725289
[186:37] Ion mobility window set to 0.0103263
[186:37] Recommended MS1 mass accuracy setting: 12.7495 ppm
[186:39] Removing low confidence identifications
[186:40] Precursors at 1% peptidoform FDR: 11756
[186:40] Removing interfering precursors
[186:40] Training neural networks on 27455 PSMs
[186:41] Number of IDs at 0.01 FDR: 17380
[186:41] Precursors at 1% peptidoform FDR: 14010
[186:41] Calculating protein q-values
[186:41] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[186:41] Quantification
[186:41] Precursors with monitored PTMs at 1% FDR: 113 out of 3048 considered
[186:41] Unmodified precursors with monitored PTM sites at 1% FDR: 2444
[186:41] Precursors with PTMs localised (when required) with > 90% confidence: 110 out of 113

[186:42] File #8/12
[186:42] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[186:46] 20221 library precursors are potentially detectable
[186:46] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[186:47] RT window set to 0.705733
[186:47] Ion mobility window set to 0.01079
[186:47] Recommended MS1 mass accuracy setting: 13.2278 ppm
[186:48] Removing low confidence identifications
[186:49] Precursors at 1% peptidoform FDR: 12052
[186:49] Removing interfering precursors
[186:49] Training neural networks on 27581 PSMs
[186:50] Number of IDs at 0.01 FDR: 17549
[186:50] Precursors at 1% peptidoform FDR: 14132
[186:50] Calculating protein q-values
[186:50] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[186:50] Quantification
[186:51] Precursors with monitored PTMs at 1% FDR: 109 out of 3185 considered
[186:51] Unmodified precursors with monitored PTM sites at 1% FDR: 2503
[186:51] Precursors with PTMs localised (when required) with > 90% confidence: 103 out of 109

[186:51] File #9/12
[186:51] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[186:55] 20221 library precursors are potentially detectable
[186:55] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[186:57] RT window set to 0.707555
[186:57] Ion mobility window set to 0.0107806
[186:57] Recommended MS1 mass accuracy setting: 13.0022 ppm
[186:58] Removing low confidence identifications
[186:59] Precursors at 1% peptidoform FDR: 12334
[186:59] Removing interfering precursors
[186:59] Training neural networks on 27726 PSMs
[187:00] Number of IDs at 0.01 FDR: 17892
[187:01] Precursors at 1% peptidoform FDR: 14344
[187:01] Calculating protein q-values
[187:01] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[187:01] Quantification
[187:01] Precursors with monitored PTMs at 1% FDR: 115 out of 3210 considered
[187:01] Unmodified precursors with monitored PTM sites at 1% FDR: 2505
[187:01] Precursors with PTMs localised (when required) with > 90% confidence: 111 out of 115

[187:01] File #10/12
[187:01] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[187:06] 20221 library precursors are potentially detectable
[187:06] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[187:08] RT window set to 0.706802
[187:08] Ion mobility window set to 0.0107364
[187:08] Recommended MS1 mass accuracy setting: 13.2838 ppm
[187:09] Removing low confidence identifications
[187:10] Precursors at 1% peptidoform FDR: 12597
[187:10] Removing interfering precursors
[187:10] Training neural networks on 27827 PSMs
[187:11] Number of IDs at 0.01 FDR: 17946
[187:11] Precursors at 1% peptidoform FDR: 14318
[187:11] Calculating protein q-values
[187:11] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[187:11] Quantification
[187:11] Precursors with monitored PTMs at 1% FDR: 117 out of 3152 considered
[187:11] Unmodified precursors with monitored PTM sites at 1% FDR: 2476
[187:11] Precursors with PTMs localised (when required) with > 90% confidence: 112 out of 117

[187:11] File #11/12
[187:11] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[187:16] 20221 library precursors are potentially detectable
[187:16] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[187:18] RT window set to 0.71083
[187:18] Ion mobility window set to 0.0102481
[187:18] Recommended MS1 mass accuracy setting: 12.7294 ppm
[187:19] Removing low confidence identifications
[187:20] Precursors at 1% peptidoform FDR: 12494
[187:20] Removing interfering precursors
[187:20] Training neural networks on 27749 PSMs
[187:21] Number of IDs at 0.01 FDR: 17705
[187:21] Precursors at 1% peptidoform FDR: 14091
[187:21] Calculating protein q-values
[187:21] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[187:21] Quantification
[187:21] Precursors with monitored PTMs at 1% FDR: 115 out of 3167 considered
[187:21] Unmodified precursors with monitored PTM sites at 1% FDR: 2444
[187:21] Precursors with PTMs localised (when required) with > 90% confidence: 109 out of 115

[187:22] File #12/12
[187:22] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[187:26] 20221 library precursors are potentially detectable
[187:26] Calibrating with mass accuracies 20 (MS1), 20 (MS2)
[187:28] RT window set to 0.705172
[187:28] Ion mobility window set to 0.0109787
[187:28] Recommended MS1 mass accuracy setting: 14.0709 ppm
[187:29] Removing low confidence identifications
[187:30] Precursors at 1% peptidoform FDR: 12167
[187:30] Removing interfering precursors
[187:30] Training neural networks on 27601 PSMs
[187:31] Number of IDs at 0.01 FDR: 17728
[187:31] Precursors at 1% peptidoform FDR: 13963
[187:31] Calculating protein q-values
[187:31] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[187:31] Quantification
[187:31] Precursors with monitored PTMs at 1% FDR: 114 out of 3053 considered
[187:31] Unmodified precursors with monitored PTM sites at 1% FDR: 2405
[187:31] Precursors with PTMs localised (when required) with > 90% confidence: 108 out of 114

[187:31] Cross-run analysis
[187:31] Reading quantification information: 12 files
[187:32] Quantifying peptides
[187:50] Quantification parameters: 0.309361, 0.00254986, 0.0106739, 0.0157107, 0.0674071, 0.0476086, 0.379306, 0.173336, 0.242666, 0.0149323, 0.0707482, 0.0165033, 0.395039, 0.355697, 0.274125, 0.0234906
[187:54] Quantifying proteins
[187:54] Calculating q-values for protein and gene groups
[187:54] Calculating global q-values for protein and gene groups
[187:54] Protein groups with global q-value <= 0.01: 3546
[187:55] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[187:55] Writing report
[187:57] Report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report.tsv.
[187:57] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v1.9.2/report.stats.tsv

