
DIA-NN 2.1.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Mar 23 2025 15:49:03
Current date and time: Tue Jun 23 20:09:15 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.1.0/diann-linux --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d --f /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d --f /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d --fasta /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta --out /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report.tsv --temp /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0 --threads 15 --missed-cleavages 1 --min-pep-len 6 --max-pep-len 30 --mass-acc 20 --mass-acc-ms1 20 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 1 --max-pr-charge 5 --min-pr-mz 400 --max-pr-mz 1200 --min-fr-mz 200 --max-fr-mz 2000 --cut K*,R* --unimod4 --var-mod UniMod:35,15.994915,M --var-mods 1 --gen-spec-lib --fasta-search --reanalyse 

Thread number set to 15
Maximum number of missed cleavages set to 1
Min peptide length set to 6
Max peptide length set to 30
Output will be filtered at 0.01 FDR
Output will be filtered at 0.01 protein-level FDR
Min precursor charge set to 1
Max precursor charge set to 5
Min precursor m/z set to 400
Max precursor m/z set to 1200
Min fragment m/z set to 200
Max fragment m/z set to 2000
In silico digest will involve cuts at K*,R*
Cysteine carbamidomethylation enabled as a fixed modification
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
Maximum number of variable modifications set to 1
A spectral library will be generated
DIA-NN will carry out FASTA digest for in silico lib generation
MBR enabled; .quant files will only be saved to disk during the first pass
Mass accuracy will be fixed to 2e-05 (MS2) and 2e-05 (MS1)
WARNING: FASTA digest mode enabled and raw data are provided, turning on deep learning spectra/RT/IM prediction
WARNING: incorrect settings, the in silico-predicted library must be generated in a separate pipeline step and then used to process the raw data, now without activating FASTA digest
WARNING: peptidoform scoring enabled because variable modifications have been declared; to disable, use --no-peptidoforms
The following variable modifications will be localised: UniMod:35 

12 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:04] Processing FASTA
[0:06] Assembling elution groups
[0:11] 5697771 precursors generated
[0:11] Protein names missing for some isoforms
[0:11] Gene names missing for some isoforms
[0:11] Library contains 31685 proteins, and 0 genes
[0:15] [0:25] [10:50] [11:52] [11:55] [11:58] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report-lib.predicted.speclib
[12:01] Initialising library
[12:18] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report-lib.predicted.speclib
[12:20] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[12:21] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5697771 precursors in 2602499 elution groups.
[12:21] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[12:22] Annotating library proteins with information from the FASTA database
[12:22] Protein names missing for some isoforms
[12:22] Gene names missing for some isoforms
[12:22] Library contains 31685 proteins, and 0 genes
[12:27] Initialising library

First pass: generating a spectral library from DIA data

[12:47] File #1/12
[12:47] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d
WARNING: for the vast majority of timsTOF datasets it is better to manually fix both the MS1 and MS2 mass accuracies to 15 ppm
[12:56] Pre-processing...
[13:06] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[13:07] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[20:12] RT window set to 2.25042
[20:12] IM window set to 0.0404944
[20:12] Peak width: 3.184
[20:12] Scan window radius set to 7
[20:13] Recommended MS1 mass accuracy setting: 8 ppm
[26:14] Searching decoys
[30:17] Main search
[37:55] Removing low confidence identifications
[38:03] Removing interfering precursors
[38:09] Training neural networks on 20862 target and 10680 decoy PSMs
[38:24] Training neural networks on 20862 target and 9992 decoy PSMs
[38:34] Number of IDs at 0.01 FDR: 11681
[38:34] Precursors at 1% peptidoform FDR: 10796
[38:35] Calculating protein q-values
[38:36] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[38:36] Quantification
[38:36] Precursors with scored PTMs at 1% FDR: 226 out of 266 considered
[38:36] Precursors with all scored PTM sites unoccupied at 1% FDR: 10570
[38:36] Precursors with PTMs localised (when required) with > 90% confidence: 221 out of 226
[38:37] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R1_d.quant

[38:37] File #2/12
[38:37] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[38:44] Pre-processing...
[38:55] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[38:55] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[45:31] RT window set to 2.54347
[45:31] IM window set to 0.0443062
[45:32] Recommended MS1 mass accuracy setting: 10 ppm
[51:46] Searching decoys
[56:26] Main search
[65:00] Removing low confidence identifications
[65:08] Removing interfering precursors
[65:13] Training neural networks on 24949 target and 13201 decoy PSMs
[65:29] Training neural networks on 24949 target and 12284 decoy PSMs
[65:40] Number of IDs at 0.01 FDR: 13265
[65:41] Precursors at 1% peptidoform FDR: 12417
[65:42] Calculating protein q-values
[65:42] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[65:42] Quantification
[65:43] Precursors with scored PTMs at 1% FDR: 251 out of 289 considered
[65:43] Precursors with all scored PTM sites unoccupied at 1% FDR: 12166
[65:43] Precursors with PTMs localised (when required) with > 90% confidence: 246 out of 251
[65:44] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R2_d.quant

[65:44] File #3/12
[65:44] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[65:52] Pre-processing...
[66:03] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[66:04] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[72:58] RT window set to 2.58615
[72:58] IM window set to 0.0426888
[72:58] Recommended MS1 mass accuracy setting: 9 ppm
[79:16] Searching decoys
[83:46] Main search
[92:29] Removing low confidence identifications
[92:37] Removing interfering precursors
[92:42] Training neural networks on 23311 target and 11930 decoy PSMs
[92:56] Training neural networks on 23311 target and 11165 decoy PSMs
[93:09] Number of IDs at 0.01 FDR: 12668
[93:11] Precursors at 1% peptidoform FDR: 11973
[93:14] Calculating protein q-values
[93:16] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[93:16] Quantification
[93:18] Precursors with scored PTMs at 1% FDR: 261 out of 304 considered
[93:18] Precursors with all scored PTM sites unoccupied at 1% FDR: 11712
[93:18] Precursors with PTMs localised (when required) with > 90% confidence: 256 out of 261
[93:19] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R3_d.quant

[93:20] File #4/12
[93:20] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[93:29] Pre-processing...
[93:42] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[93:43] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[100:32] RT window set to 2.77589
[100:32] IM window set to 0.0431535
[100:32] Recommended MS1 mass accuracy setting: 9 ppm
[106:50] Searching decoys
[111:45] Main search
[121:13] Removing low confidence identifications
[121:21] Removing interfering precursors
[121:26] Training neural networks on 25895 target and 13942 decoy PSMs
[121:42] Training neural networks on 25895 target and 12864 decoy PSMs
[121:54] Number of IDs at 0.01 FDR: 13631
[121:55] Precursors at 1% peptidoform FDR: 12810
[121:56] Calculating protein q-values
[121:56] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[121:56] Quantification
[121:57] Precursors with scored PTMs at 1% FDR: 278 out of 322 considered
[121:57] Precursors with all scored PTM sites unoccupied at 1% FDR: 12532
[121:57] Precursors with PTMs localised (when required) with > 90% confidence: 270 out of 278
[121:58] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R4_d.quant

[121:58] File #5/12
[121:58] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[122:07] Pre-processing...
[122:19] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[122:20] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[129:14] RT window set to 2.24911
[129:14] IM window set to 0.0434934
[129:14] Recommended MS1 mass accuracy setting: 9 ppm
[134:59] Searching decoys
[139:16] Main search
[147:37] Removing low confidence identifications
[147:45] Removing interfering precursors
[147:50] Training neural networks on 23352 target and 12333 decoy PSMs
[148:06] Training neural networks on 23352 target and 11479 decoy PSMs
[148:17] Number of IDs at 0.01 FDR: 12917
[148:17] Precursors at 1% peptidoform FDR: 12179
[148:18] Calculating protein q-values
[148:19] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[148:19] Quantification
[148:20] Precursors with scored PTMs at 1% FDR: 267 out of 298 considered
[148:20] Precursors with all scored PTM sites unoccupied at 1% FDR: 11912
[148:20] Precursors with PTMs localised (when required) with > 90% confidence: 262 out of 267
[148:20] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R5_d.quant

[148:20] File #6/12
[148:20] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[148:30] Pre-processing...
[148:43] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[148:44] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[155:14] RT window set to 2.35489
[155:14] IM window set to 0.0417644
[155:14] Recommended MS1 mass accuracy setting: 10 ppm
[160:59] Searching decoys
[165:24] Main search
[173:37] Removing low confidence identifications
[173:45] Removing interfering precursors
[173:50] Training neural networks on 24196 target and 12836 decoy PSMs
[174:06] Training neural networks on 24196 target and 11963 decoy PSMs
[174:16] Number of IDs at 0.01 FDR: 13053
[174:17] Precursors at 1% peptidoform FDR: 12324
[174:18] Calculating protein q-values
[174:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[174:18] Quantification
[174:19] Precursors with scored PTMs at 1% FDR: 283 out of 313 considered
[174:19] Precursors with all scored PTM sites unoccupied at 1% FDR: 12041
[174:19] Precursors with PTMs localised (when required) with > 90% confidence: 278 out of 283
[174:19] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_A9_G_DIA_nLC_tTOF_R6_d.quant

[174:19] File #7/12
[174:19] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[174:27] Pre-processing...
[174:37] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[174:38] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[181:09] RT window set to 2.34198
[181:09] IM window set to 0.0411392
[181:09] Recommended MS1 mass accuracy setting: 9 ppm
[186:45] Searching decoys
[190:44] Main search
[197:44] Removing low confidence identifications
[197:52] Removing interfering precursors
[197:57] Training neural networks on 21558 target and 10695 decoy PSMs
[198:11] Training neural networks on 21558 target and 10184 decoy PSMs
[198:19] Number of IDs at 0.01 FDR: 12686
[198:20] Precursors at 1% peptidoform FDR: 12104
[198:20] Calculating protein q-values
[198:21] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[198:21] Quantification
[198:21] Precursors with scored PTMs at 1% FDR: 262 out of 294 considered
[198:21] Precursors with all scored PTM sites unoccupied at 1% FDR: 11842
[198:21] Precursors with PTMs localised (when required) with > 90% confidence: 258 out of 262
[198:21] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R1_d.quant

[198:21] File #8/12
[198:21] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[198:28] Pre-processing...
[198:37] 1886 MS1 and 49019 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[198:38] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[204:21] RT window set to 2.4635
[204:21] IM window set to 0.0426996
[204:22] Recommended MS1 mass accuracy setting: 8 ppm
[209:36] Searching decoys
[213:27] Main search
[220:29] Removing low confidence identifications
[220:36] Removing interfering precursors
[220:41] Training neural networks on 23707 target and 11920 decoy PSMs
[220:56] Training neural networks on 23707 target and 11125 decoy PSMs
[221:05] Number of IDs at 0.01 FDR: 13424
[221:05] Precursors at 1% peptidoform FDR: 12606
[221:06] Calculating protein q-values
[221:06] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[221:06] Quantification
[221:07] Precursors with scored PTMs at 1% FDR: 285 out of 330 considered
[221:07] Precursors with all scored PTM sites unoccupied at 1% FDR: 12321
[221:07] Precursors with PTMs localised (when required) with > 90% confidence: 281 out of 285
[221:07] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R2_d.quant

[221:07] File #9/12
[221:07] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[221:15] Pre-processing...
[221:25] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[221:26] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[227:32] RT window set to 2.26068
[227:32] IM window set to 0.0423643
[227:32] Recommended MS1 mass accuracy setting: 9 ppm
[232:42] Searching decoys
[236:15] Main search
[242:57] Removing low confidence identifications
[243:04] Removing interfering precursors
[243:09] Training neural networks on 23289 target and 11546 decoy PSMs
[243:21] Training neural networks on 23289 target and 10819 decoy PSMs
[243:29] Number of IDs at 0.01 FDR: 13603
[243:29] Precursors at 1% peptidoform FDR: 13027
[243:30] Calculating protein q-values
[243:30] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[243:30] Quantification
[243:31] Precursors with scored PTMs at 1% FDR: 303 out of 334 considered
[243:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 12724
[243:31] Precursors with PTMs localised (when required) with > 90% confidence: 296 out of 303
[243:31] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R3_d.quant

[243:31] File #10/12
[243:31] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[243:38] Pre-processing...
[243:50] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[243:50] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[249:39] RT window set to 2.73679
[249:39] IM window set to 0.0424506
[249:40] Recommended MS1 mass accuracy setting: 9 ppm
[255:04] Searching decoys
[259:23] Main search
[267:34] Removing low confidence identifications
[267:41] Removing interfering precursors
[267:46] Training neural networks on 25329 target and 13107 decoy PSMs
[267:59] Training neural networks on 25329 target and 12259 decoy PSMs
[268:08] Number of IDs at 0.01 FDR: 13937
[268:08] Precursors at 1% peptidoform FDR: 13306
[268:09] Calculating protein q-values
[268:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[268:09] Quantification
[268:10] Precursors with scored PTMs at 1% FDR: 318 out of 350 considered
[268:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 12988
[268:10] Precursors with PTMs localised (when required) with > 90% confidence: 312 out of 318
[268:10] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R4_d.quant

[268:10] File #11/12
[268:10] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[268:17] Pre-processing...
[268:29] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[268:30] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[274:16] RT window set to 2.26836
[274:16] IM window set to 0.041143
[274:16] Recommended MS1 mass accuracy setting: 9 ppm
[279:05] Searching decoys
[282:35] Main search
[289:14] Removing low confidence identifications
[289:21] Removing interfering precursors
[289:26] Training neural networks on 23879 target and 11669 decoy PSMs
[289:38] Training neural networks on 23879 target and 11022 decoy PSMs
[289:46] Number of IDs at 0.01 FDR: 13573
[289:46] Precursors at 1% peptidoform FDR: 12940
[289:47] Calculating protein q-values
[289:47] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[289:47] Quantification
[289:47] Precursors with scored PTMs at 1% FDR: 315 out of 356 considered
[289:47] Precursors with all scored PTM sites unoccupied at 1% FDR: 12625
[289:47] Precursors with PTMs localised (when required) with > 90% confidence: 305 out of 315
[289:48] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R5_d.quant

[289:48] File #12/12
[289:48] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[289:55] Pre-processing...
[290:07] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 5543758 precursors in range
[290:07] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[295:34] RT window set to 2.46462
[295:34] IM window set to 0.0424797
[295:35] Recommended MS1 mass accuracy setting: 9 ppm
[300:30] Searching decoys
[304:21] Main search
[311:53] Removing low confidence identifications
[312:01] Removing interfering precursors
[312:07] Training neural networks on 25848 target and 13359 decoy PSMs
[312:22] Training neural networks on 25848 target and 12563 decoy PSMs
[312:30] Number of IDs at 0.01 FDR: 14135
[312:31] Precursors at 1% peptidoform FDR: 13417
[312:32] Calculating protein q-values
[312:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[312:32] Quantification
[312:33] Precursors with scored PTMs at 1% FDR: 326 out of 363 considered
[312:33] Precursors with all scored PTM sites unoccupied at 1% FDR: 13091
[312:33] Precursors with PTMs localised (when required) with > 90% confidence: 321 out of 326
[312:33] Quantification information saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/_public_local_ProteoBench_PYE_diaPASEF_B9_G_DIA_nLC_tTOF_R6_d.quant

[312:33] Cross-run analysis
[312:33] Reading quantification information: 12 files
[312:43] Quantifying peptides
[313:07] Assembling protein groups
[313:08] Quantifying proteins
[313:08] Calculating q-values for protein and gene groups
[313:10] Calculating global q-values for protein and gene groups
[313:10] Protein groups with global q-value <= 0.01: 2834
[313:11] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[313:11] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report-first-pass.stats.tsv
[313:11] Generating spectral library:
[313:11] 20235 target and 202 decoy precursors saved
WARNING: 228 precursors without any fragments annotated were skipped
[313:11] Spectral library saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report-lib.parquet

[313:14] Loading spectral library /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report-lib.parquet
[313:14] Spectral library loaded: 3556 protein isoforms, 3387 protein groups and 20437 precursors in 19151 elution groups.
[313:14] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[313:14] Annotating library proteins with information from the FASTA database
[313:14] Gene names missing for some isoforms
[313:14] Library contains 3528 proteins, and 0 genes
[313:14] Initialising library
[313:14] Saving the library to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report-lib.parquet.skyline.speclib


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

[313:14] File #1/12
[313:14] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R1.d
[313:21] Pre-processing...
[313:30] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[313:30] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[313:31] RT window set to 0.721463
[313:31] IM window set to 0.0105011
[313:31] Recommended MS1 mass accuracy setting: 10 ppm
[313:32] Searching decoys
[313:32] Main search
[313:33] Removing low confidence identifications
[313:34] Removing interfering precursors
[313:34] Training neural networks on 17790 target and 10964 decoy PSMs
[313:40] Training neural networks on 17785 target and 10164 decoy PSMs
[313:45] Number of IDs at 0.01 FDR: 15168
[313:45] Precursors at 1% peptidoform FDR: 13922
[313:45] Calculating protein q-values
[313:45] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[313:45] Quantification
[313:46] Precursors with scored PTMs at 1% FDR: 289 out of 317 considered
[313:46] Precursors with all scored PTM sites unoccupied at 1% FDR: 13633
[313:46] Precursors with PTMs localised (when required) with > 90% confidence: 285 out of 289

[313:46] File #2/12
[313:46] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R2.d
[313:53] Pre-processing...
[314:02] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[314:02] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[314:03] RT window set to 0.720877
[314:03] IM window set to 0.010764
[314:03] Recommended MS1 mass accuracy setting: 11 ppm
[314:04] Searching decoys
[314:04] Main search
[314:05] Removing low confidence identifications
[314:06] Removing interfering precursors
[314:06] Training neural networks on 18066 target and 11293 decoy PSMs
[314:12] Training neural networks on 18062 target and 10480 decoy PSMs
[314:18] Number of IDs at 0.01 FDR: 15923
[314:18] Precursors at 1% peptidoform FDR: 14992
[314:18] Calculating protein q-values
[314:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[314:18] Quantification
[314:18] Precursors with scored PTMs at 1% FDR: 292 out of 328 considered
[314:18] Precursors with all scored PTM sites unoccupied at 1% FDR: 14700
[314:18] Precursors with PTMs localised (when required) with > 90% confidence: 289 out of 292

[314:19] File #3/12
[314:19] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R3.d
[314:25] Pre-processing...
[314:36] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[314:36] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[314:37] RT window set to 0.712123
[314:37] IM window set to 0.01
[314:37] Recommended MS1 mass accuracy setting: 10 ppm
[314:38] Searching decoys
[314:38] Main search
[314:39] Removing low confidence identifications
[314:40] Removing interfering precursors
[314:40] Training neural networks on 18097 target and 11384 decoy PSMs
[314:46] Training neural networks on 18091 target and 10520 decoy PSMs
[314:52] Number of IDs at 0.01 FDR: 16011
[314:52] Precursors at 1% peptidoform FDR: 14907
[314:52] Calculating protein q-values
[314:52] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[314:52] Quantification
[314:52] Precursors with scored PTMs at 1% FDR: 315 out of 339 considered
[314:52] Precursors with all scored PTM sites unoccupied at 1% FDR: 14592
[314:52] Precursors with PTMs localised (when required) with > 90% confidence: 310 out of 315

[314:52] File #4/12
[314:52] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R4.d
[314:59] Pre-processing...
[315:11] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[315:11] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[315:12] RT window set to 0.693565
[315:12] IM window set to 0.0102414
[315:12] Recommended MS1 mass accuracy setting: 10 ppm
[315:12] Searching decoys
[315:13] Main search
[315:14] Removing low confidence identifications
[315:15] Removing interfering precursors
[315:15] Training neural networks on 18141 target and 11277 decoy PSMs
[315:21] Training neural networks on 18138 target and 10498 decoy PSMs
[315:27] Number of IDs at 0.01 FDR: 16216
[315:27] Precursors at 1% peptidoform FDR: 15157
[315:27] Calculating protein q-values
[315:27] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[315:27] Quantification
[315:27] Precursors with scored PTMs at 1% FDR: 326 out of 347 considered
[315:27] Precursors with all scored PTM sites unoccupied at 1% FDR: 14831
[315:27] Precursors with PTMs localised (when required) with > 90% confidence: 319 out of 326

[315:27] File #5/12
[315:27] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R5.d
[315:34] Pre-processing...
[315:46] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[315:46] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[315:47] RT window set to 0.711784
[315:47] IM window set to 0.010249
[315:47] Recommended MS1 mass accuracy setting: 10 ppm
[315:47] Searching decoys
[315:48] Main search
[315:49] Removing low confidence identifications
[315:50] Removing interfering precursors
[315:50] Training neural networks on 18155 target and 11445 decoy PSMs
[315:56] Training neural networks on 18148 target and 10611 decoy PSMs
[316:02] Number of IDs at 0.01 FDR: 16250
[316:02] Precursors at 1% peptidoform FDR: 15165
[316:02] Calculating protein q-values
[316:02] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[316:02] Quantification
[316:02] Precursors with scored PTMs at 1% FDR: 319 out of 335 considered
[316:02] Precursors with all scored PTM sites unoccupied at 1% FDR: 14846
[316:02] Precursors with PTMs localised (when required) with > 90% confidence: 310 out of 319

[316:02] File #6/12
[316:02] Loading run /public/local/ProteoBench/PYE_diaPASEF/A9_G_DIA_nLC_tTOF_R6.d
[316:09] Pre-processing...
[316:20] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[316:20] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[316:21] RT window set to 0.717483
[316:21] IM window set to 0.0103492
[316:21] Recommended MS1 mass accuracy setting: 10 ppm
[316:22] Searching decoys
[316:23] Main search
[316:23] Removing low confidence identifications
[316:25] Removing interfering precursors
[316:25] Training neural networks on 18103 target and 11369 decoy PSMs
[316:31] Training neural networks on 18099 target and 10511 decoy PSMs
[316:36] Number of IDs at 0.01 FDR: 15932
[316:36] Precursors at 1% peptidoform FDR: 14787
[316:36] Calculating protein q-values
[316:36] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[316:36] Quantification
[316:37] Precursors with scored PTMs at 1% FDR: 323 out of 345 considered
[316:37] Precursors with all scored PTM sites unoccupied at 1% FDR: 14464
[316:37] Precursors with PTMs localised (when required) with > 90% confidence: 313 out of 323

[316:37] File #7/12
[316:37] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R1.d
[316:43] Pre-processing...
[316:52] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[316:52] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[316:54] RT window set to 0.734655
[316:54] IM window set to 0.0104444
[316:54] Recommended MS1 mass accuracy setting: 10 ppm
[316:54] Searching decoys
[316:55] Main search
[316:55] Removing low confidence identifications
[316:57] Removing interfering precursors
[316:57] Training neural networks on 18060 target and 11148 decoy PSMs
[317:03] Training neural networks on 18055 target and 10416 decoy PSMs
[317:08] Number of IDs at 0.01 FDR: 16471
[317:08] Precursors at 1% peptidoform FDR: 15203
[317:08] Calculating protein q-values
[317:08] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[317:08] Quantification
[317:09] Precursors with scored PTMs at 1% FDR: 332 out of 354 considered
[317:09] Precursors with all scored PTM sites unoccupied at 1% FDR: 14871
[317:09] Precursors with PTMs localised (when required) with > 90% confidence: 323 out of 332

[317:09] File #8/12
[317:09] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R2.d
[317:15] Pre-processing...
[317:23] 1886 MS1 and 49019 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[317:23] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[317:25] RT window set to 0.72637
[317:25] IM window set to 0.01148
[317:25] Recommended MS1 mass accuracy setting: 10 ppm
[317:25] Searching decoys
[317:26] Main search
[317:26] Removing low confidence identifications
[317:28] Removing interfering precursors
[317:28] Training neural networks on 18195 target and 11576 decoy PSMs
[317:34] Training neural networks on 18194 target and 10585 decoy PSMs
[317:39] Number of IDs at 0.01 FDR: 16480
[317:39] Precursors at 1% peptidoform FDR: 15350
[317:39] Calculating protein q-values
[317:39] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[317:39] Quantification
[317:40] Precursors with scored PTMs at 1% FDR: 338 out of 363 considered
[317:40] Precursors with all scored PTM sites unoccupied at 1% FDR: 15012
[317:40] Precursors with PTMs localised (when required) with > 90% confidence: 331 out of 338

[317:40] File #9/12
[317:40] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R3.d
[317:47] Pre-processing...
[317:57] 1886 MS1 and 49013 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[317:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[317:58] RT window set to 0.695138
[317:58] IM window set to 0.01
[317:58] Recommended MS1 mass accuracy setting: 10 ppm
[317:59] Searching decoys
[317:59] Main search
[318:00] Removing low confidence identifications
[318:01] Removing interfering precursors
[318:01] Training neural networks on 18254 target and 11628 decoy PSMs
[318:07] Training neural networks on 18251 target and 10554 decoy PSMs
[318:13] Number of IDs at 0.01 FDR: 16783
[318:13] Precursors at 1% peptidoform FDR: 15919
[318:13] Calculating protein q-values
[318:13] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[318:13] Quantification
[318:13] Precursors with scored PTMs at 1% FDR: 345 out of 370 considered
[318:13] Precursors with all scored PTM sites unoccupied at 1% FDR: 15574
[318:13] Precursors with PTMs localised (when required) with > 90% confidence: 337 out of 345

[318:14] File #10/12
[318:14] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R4.d
[318:21] Pre-processing...
[318:32] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[318:32] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[318:33] RT window set to 0.704328
[318:33] IM window set to 0.0101923
[318:33] Recommended MS1 mass accuracy setting: 10 ppm
[318:34] Searching decoys
[318:34] Main search
[318:35] Removing low confidence identifications
[318:36] Removing interfering precursors
[318:36] Training neural networks on 18299 target and 11371 decoy PSMs
[318:42] Training neural networks on 18293 target and 10494 decoy PSMs
[318:48] Number of IDs at 0.01 FDR: 16844
[318:48] Precursors at 1% peptidoform FDR: 16028
[318:48] Calculating protein q-values
[318:48] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[318:48] Quantification
[318:48] Precursors with scored PTMs at 1% FDR: 350 out of 367 considered
[318:48] Precursors with all scored PTM sites unoccupied at 1% FDR: 15678
[318:48] Precursors with PTMs localised (when required) with > 90% confidence: 342 out of 350

[318:48] File #11/12
[318:48] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R5.d
[318:55] Pre-processing...
[319:06] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[319:06] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[319:08] RT window set to 0.691743
[319:08] IM window set to 0.01
[319:08] Recommended MS1 mass accuracy setting: 10 ppm
[319:08] Searching decoys
[319:09] Main search
[319:10] Removing low confidence identifications
[319:11] Removing interfering precursors
[319:11] Training neural networks on 18279 target and 11395 decoy PSMs
[319:17] Training neural networks on 18271 target and 10528 decoy PSMs
[319:23] Number of IDs at 0.01 FDR: 16875
[319:23] Precursors at 1% peptidoform FDR: 15934
[319:23] Calculating protein q-values
[319:23] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[319:23] Quantification
[319:23] Precursors with scored PTMs at 1% FDR: 356 out of 366 considered
[319:23] Precursors with all scored PTM sites unoccupied at 1% FDR: 15578
[319:23] Precursors with PTMs localised (when required) with > 90% confidence: 346 out of 356

[319:23] File #12/12
[319:23] Loading run /public/local/ProteoBench/PYE_diaPASEF/B9_G_DIA_nLC_tTOF_R6.d
[319:30] Pre-processing...
[319:42] 1886 MS1 and 49016 MS2 scans in 1886 (inferred) and 1886 (encoded) cycles, 20235 precursors in range
[319:42] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[319:43] RT window set to 0.689751
[319:43] IM window set to 0.01
[319:43] Recommended MS1 mass accuracy setting: 11 ppm
[319:44] Searching decoys
[319:44] Main search
[319:45] Removing low confidence identifications
[319:46] Removing interfering precursors
[319:46] Training neural networks on 18163 target and 11324 decoy PSMs
[319:52] Training neural networks on 18156 target and 10409 decoy PSMs
[319:58] Number of IDs at 0.01 FDR: 16508
[319:58] Precursors at 1% peptidoform FDR: 15520
[319:58] Calculating protein q-values
[319:58] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[319:58] Quantification
[319:58] Precursors with scored PTMs at 1% FDR: 355 out of 368 considered
[319:58] Precursors with all scored PTM sites unoccupied at 1% FDR: 15165
[319:58] Precursors with PTMs localised (when required) with > 90% confidence: 347 out of 355

[319:58] Cross-run analysis
[319:58] Reading quantification information: 12 files
[319:58] Quantifying peptides
[320:32] Quantification parameters: 0.315292, 0.00241013, 0.0107576, 0.0299312, 0.124467, 0.0922971, 0.345837, 0.162982, 0.242967, 0.0144541, 0.141282, 0.0444861, 0.347146, 0.225564, 0.206556, 0.013231
[320:46] Quantifying proteins
[320:46] Calculating q-values for protein and gene groups
[320:46] Calculating global q-values for protein and gene groups
[320:46] Protein groups with global q-value <= 0.01: 2584
[320:47] Compressed report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[320:47] Stats report saved to /home/robbe/PB_output/results/Plasma_Normalization/PYE_diaPASEF/diann_v2.1.0/report.stats.tsv

