
DIA-NN 2.5.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Apr 12 2026 10:45:33
Current date and time: Wed Jul  8 19:53:42 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.5.0/diann-linux --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw --fasta /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta --out /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report.tsv --temp /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0 --threads 24 --missed-cleavages 1 --min-pep-len 6 --max-pep-len 30 --mass-acc 10 --mass-acc-ms1 3 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 1 --max-pr-charge 5 --min-pr-mz 380 --max-pr-mz 980 --min-fr-mz 150 --max-fr-mz 2000 --cut K*,R* --unimod4 --var-mod UniMod:35,15.994915,M --var-mods 1 --gen-spec-lib --fasta-search --reanalyse --no-norm 

Thread number set to 24
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 380
Max precursor m/z set to 980
Min fragment m/z set to 150
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
Normalisation disabled
Mass accuracy will be fixed to 1e-05 (MS2) and 3e-06 (MS1)
WARNING: FASTA digest mode enabled and raw data are provided, turning on deep learning spectra/RT/IM prediction
WARNING: incorrect settings, the in silico-predicted library must be generated in a separate pipeline step and then used to process the raw data, now without activating FASTA digest
WARNING: peptidoform scoring enabled because variable modifications have been declared; to disable, use --no-peptidoforms
The following variable modifications will be localised: UniMod:35 

6 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:18] Processing FASTA
[0:21] Assembling elution groups
[0:39] 5055014 precursors generated
[0:39] Protein names missing for some isoforms
[0:39] Gene names missing for some isoforms
[0:39] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:49] [1:16] [20:26] [23:59] [24:08] [24:23] Saving the library to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report-lib.predicted.speclib
[24:29] Initialising library
[24:58] Loading spectral library /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report-lib.predicted.speclib
[25:04] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[25:05] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5055014 precursors in 2602499 elution groups (targets and decoys).
[25:05] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[25:06] Annotating library proteins with information from the FASTA database
[25:06] Protein names missing for some isoforms
[25:06] Gene names missing for some isoforms
[25:06] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[25:12] Initialising library

First pass: generating a spectral library from DIA data

[25:30] File #1/6
[25:30] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[26:02] Pre-processing...
[26:04] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 5050223 precursors in range
[26:05] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[27:06] RT window set to 1.11215
[27:06] Peak width: 2.828
[27:06] Scan window radius set to 6
[27:07] Recommended MS1 mass accuracy setting: 2.6 ppm
[27:31] Searching decoys
[29:17] Main search
[31:08] Removing low confidence identifications
[31:34] Removing interfering precursors
[31:52] Training neural networks on 321056 target and 275781 decoy PSMs
[33:26] Training neural networks on 321056 target and 275788 decoy PSMs
[35:05] Precursors at 1% peptidoform FDR: 104820
[35:07] Number of IDs at 0.01 FDR: 106870
[35:07] Calculating protein q-values
[35:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[35:08] Quantification
[35:09] Precursors with scored PTMs at 1% FDR: 2368 out of 2485 considered
[35:09] Precursors with all scored PTM sites unoccupied at 1% FDR: 102452
[35:09] Precursors with PTMs localised (when required) with > 90% confidence: 2268 out of 2368
[35:10] Quantification information saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP1_raw.quant

[35:10] File #2/6
[35:10] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[35:32] Pre-processing...
[35:33] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[35:33] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[35:54] RT window set to 1.16475
[35:54] Recommended MS1 mass accuracy setting: 2.6 ppm
[36:00] Searching decoys
[36:37] Main search
[37:51] Removing low confidence identifications
[38:22] Removing interfering precursors
[38:43] Training neural networks on 331310 target and 283988 decoy PSMs
[40:14] Training neural networks on 331310 target and 284414 decoy PSMs
[41:35] Precursors at 1% peptidoform FDR: 107456
[41:36] Number of IDs at 0.01 FDR: 110299
[41:36] Calculating protein q-values
[41:37] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[41:37] Quantification
[41:38] Precursors with scored PTMs at 1% FDR: 2429 out of 2658 considered
[41:38] Precursors with all scored PTM sites unoccupied at 1% FDR: 105027
[41:38] Precursors with PTMs localised (when required) with > 90% confidence: 2341 out of 2429
[41:39] Quantification information saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP2_raw.quant

[41:39] File #3/6
[41:39] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[41:55] Pre-processing...
[41:56] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[41:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[42:12] RT window set to 1.24321
[42:12] Recommended MS1 mass accuracy setting: 2.8 ppm
[42:17] Searching decoys
[42:58] Main search
[44:02] Removing low confidence identifications
[44:32] Removing interfering precursors
[44:50] Training neural networks on 323309 target and 277549 decoy PSMs
[46:08] Training neural networks on 323309 target and 278747 decoy PSMs
[47:20] Precursors at 1% peptidoform FDR: 107684
[47:23] Number of IDs at 0.01 FDR: 110656
[47:23] Calculating protein q-values
[47:25] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[47:25] Quantification
[47:27] Precursors with scored PTMs at 1% FDR: 2424 out of 2684 considered
[47:27] Precursors with all scored PTM sites unoccupied at 1% FDR: 105260
[47:27] Precursors with PTMs localised (when required) with > 90% confidence: 2332 out of 2424
[47:30] Quantification information saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP3_raw.quant

[47:30] File #4/6
[47:30] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[47:46] Pre-processing...
[47:48] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[47:48] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[48:00] RT window set to 1.46489
[48:00] Recommended MS1 mass accuracy setting: 3.1 ppm
[48:05] Searching decoys
[48:42] Main search
[50:01] Removing low confidence identifications
[50:32] Removing interfering precursors
[50:55] Training neural networks on 347180 target and 301887 decoy PSMs
[52:17] Training neural networks on 347180 target and 301397 decoy PSMs
[53:37] Precursors at 1% peptidoform FDR: 108309
[53:38] Number of IDs at 0.01 FDR: 110839
[53:38] Calculating protein q-values
[53:38] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[53:38] Quantification
[53:40] Precursors with scored PTMs at 1% FDR: 3120 out of 3318 considered
[53:40] Precursors with all scored PTM sites unoccupied at 1% FDR: 105189
[53:40] Precursors with PTMs localised (when required) with > 90% confidence: 2997 out of 3120
[53:41] Quantification information saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP1_raw.quant

[53:41] File #5/6
[53:41] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[53:56] Pre-processing...
[53:58] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[53:58] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[54:14] RT window set to 1.27025
[54:15] Recommended MS1 mass accuracy setting: 2.9 ppm
[54:20] Searching decoys
[54:55] Main search
[56:02] Removing low confidence identifications
[56:26] Removing interfering precursors
[56:43] Training neural networks on 327997 target and 285042 decoy PSMs
[57:58] Training neural networks on 327997 target and 284656 decoy PSMs
[59:25] Precursors at 1% peptidoform FDR: 107716
[59:27] Number of IDs at 0.01 FDR: 109779
[59:27] Calculating protein q-values
[59:27] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[59:27] Quantification
[59:29] Precursors with scored PTMs at 1% FDR: 3114 out of 3294 considered
[59:29] Precursors with all scored PTM sites unoccupied at 1% FDR: 104602
[59:29] Precursors with PTMs localised (when required) with > 90% confidence: 3005 out of 3114
[59:30] Quantification information saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP2_raw.quant

[59:30] File #6/6
[59:30] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[59:46] Pre-processing...
[59:47] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[59:47] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[60:04] RT window set to 1.2182
[60:04] Recommended MS1 mass accuracy setting: 2.7 ppm
[60:10] Searching decoys
[60:42] Main search
[61:47] Removing low confidence identifications
[62:10] Removing interfering precursors
[62:25] Training neural networks on 313667 target and 268911 decoy PSMs
[64:46] Training neural networks on 313667 target and 270376 decoy PSMs
[67:17] Precursors at 1% peptidoform FDR: 107243
[67:23] Number of IDs at 0.01 FDR: 110082
[67:23] Calculating protein q-values
[67:26] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[67:27] Quantification
[67:31] Precursors with scored PTMs at 1% FDR: 3008 out of 3254 considered
[67:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 104235
[67:31] Precursors with PTMs localised (when required) with > 90% confidence: 2896 out of 3008
[67:37] Quantification information saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP3_raw.quant

[67:37] Cross-run analysis
[67:37] Reading quantification information: 6 files
[68:10] Target precursors at 1% global q-value: 141676
[68:11] Quantifying peptides
[69:07] Assembling protein groups
[69:12] Quantifying proteins
[69:14] Calculating q-values for protein and gene groups
[69:34] Calculating global q-values for protein and gene groups
[69:35] Protein groups with global q-value <= 0.01: 12014
[69:42] Compressed report saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[69:42] Stats report saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report-first-pass.stats.tsv
[69:44] Generating spectral library:
[69:50] 153725 target and 8083 decoy precursors saved
WARNING: 25668 precursors without any fragments annotated were skipped
[69:50] Spectral library saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report-lib.parquet

[69:55] Loading spectral library /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report-lib.parquet
[69:59] Spectral library loaded: 18001 protein isoforms, 17909 protein groups and 161808 precursors in 150658 elution groups (targets and decoys).
[69:59] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[69:59] Annotating library proteins with information from the FASTA database
[69:59] Protein names missing for some isoforms
[69:59] Gene names missing for some isoforms
[69:59] Library contains 17992 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[70:00] Initialising library
[70:03] Saving the library to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report-lib.parquet.skyline.speclib


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

[70:03] File #1/6
[70:03] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[71:16] Pre-processing...
[71:17] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 153725 precursors in range
[71:17] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[71:20] RT window set to 0.434008
[71:20] Recommended MS1 mass accuracy setting: 3.1 ppm
[71:21] Searching decoys
[71:23] Main search
[71:29] Removing low confidence identifications
[71:40] Removing interfering precursors
[71:44] Training neural networks on 121262 target and 62269 decoy PSMs
[72:33] Training neural networks on 121031 target and 68317 decoy PSMs
[73:19] Precursors at 1% peptidoform FDR: 96757
[73:20] Number of IDs at 0.01 FDR: 98959
[73:20] Calculating protein q-values
[73:21] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[73:21] Quantification
[73:22] Precursors with scored PTMs at 1% FDR: 2188 out of 2271 considered
[73:22] Precursors with all scored PTM sites unoccupied at 1% FDR: 95214
[73:22] Precursors with PTMs localised (when required) with > 90% confidence: 2111 out of 2188

[73:24] File #2/6
[73:24] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[74:29] Pre-processing...
[74:30] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 153725 precursors in range
[74:30] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[74:32] RT window set to 0.437395
[74:32] Recommended MS1 mass accuracy setting: 3 ppm
[74:33] Searching decoys
[74:35] Main search
[74:41] Removing low confidence identifications
[74:49] Removing interfering precursors
[74:54] Training neural networks on 121540 target and 62340 decoy PSMs
[75:43] Training neural networks on 121343 target and 68607 decoy PSMs
[76:28] Precursors at 1% peptidoform FDR: 97536
[76:29] Number of IDs at 0.01 FDR: 99397
[76:29] Calculating protein q-values
[76:29] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[76:29] Quantification
[76:31] Precursors with scored PTMs at 1% FDR: 2223 out of 2317 considered
[76:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 95771
[76:31] Precursors with PTMs localised (when required) with > 90% confidence: 2159 out of 2223

[76:34] File #3/6
[76:34] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[77:52] Pre-processing...
[77:53] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 153725 precursors in range
[77:53] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[77:55] RT window set to 0.435084
[77:55] Recommended MS1 mass accuracy setting: 3.1 ppm
[77:55] Searching decoys
[77:56] Main search
[77:59] Removing low confidence identifications
[78:02] Removing interfering precursors
[78:04] Training neural networks on 121812 target and 63074 decoy PSMs
[78:23] Training neural networks on 121616 target and 69071 decoy PSMs
[78:44] Precursors at 1% peptidoform FDR: 97864
[78:44] Number of IDs at 0.01 FDR: 100237
[78:44] Calculating protein q-values
[78:44] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[78:44] Quantification
[78:45] Precursors with scored PTMs at 1% FDR: 2266 out of 2345 considered
[78:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 96620
[78:45] Precursors with PTMs localised (when required) with > 90% confidence: 2194 out of 2266

[78:45] File #4/6
[78:45] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[79:03] Pre-processing...
[79:04] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 153725 precursors in range
[79:04] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[79:05] RT window set to 0.459972
[79:05] Recommended MS1 mass accuracy setting: 3.3 ppm
[79:05] Searching decoys
[79:06] Main search
[79:08] Removing low confidence identifications
[79:12] Removing interfering precursors
[79:14] Training neural networks on 124064 target and 62472 decoy PSMs
[79:35] Training neural networks on 123866 target and 68994 decoy PSMs
[79:55] Precursors at 1% peptidoform FDR: 100332
[79:56] Number of IDs at 0.01 FDR: 103074
[79:56] Calculating protein q-values
[79:56] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[79:56] Quantification
[79:57] Precursors with scored PTMs at 1% FDR: 2540 out of 2680 considered
[79:57] Precursors with all scored PTM sites unoccupied at 1% FDR: 98838
[79:57] Precursors with PTMs localised (when required) with > 90% confidence: 2455 out of 2540

[79:57] File #5/6
[79:57] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[80:13] Pre-processing...
[80:14] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 153725 precursors in range
[80:14] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[80:15] RT window set to 0.4609
[80:15] Recommended MS1 mass accuracy setting: 3.1 ppm
[80:15] Searching decoys
[80:16] Main search
[80:19] Removing low confidence identifications
[80:22] Removing interfering precursors
[80:24] Training neural networks on 124154 target and 61874 decoy PSMs
[80:44] Training neural networks on 123953 target and 69086 decoy PSMs
[81:04] Precursors at 1% peptidoform FDR: 100409
[81:05] Number of IDs at 0.01 FDR: 102481
[81:05] Calculating protein q-values
[81:05] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[81:05] Quantification
[81:05] Precursors with scored PTMs at 1% FDR: 2530 out of 2646 considered
[81:05] Precursors with all scored PTM sites unoccupied at 1% FDR: 98090
[81:05] Precursors with PTMs localised (when required) with > 90% confidence: 2451 out of 2530

[81:06] File #6/6
[81:06] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[81:25] Pre-processing...
[81:26] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 153725 precursors in range
[81:26] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[81:27] RT window set to 0.448866
[81:27] Recommended MS1 mass accuracy setting: 3 ppm
[81:27] Searching decoys
[81:28] Main search
[81:30] Removing low confidence identifications
[81:35] Removing interfering precursors
[81:37] Training neural networks on 123752 target and 62523 decoy PSMs
[81:57] Training neural networks on 123569 target and 69098 decoy PSMs
[82:18] Precursors at 1% peptidoform FDR: 99676
[82:18] Number of IDs at 0.01 FDR: 102009
[82:18] Calculating protein q-values
[82:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[82:18] Quantification
[82:19] Precursors with scored PTMs at 1% FDR: 2520 out of 2660 considered
[82:19] Precursors with all scored PTM sites unoccupied at 1% FDR: 97953
[82:19] Precursors with PTMs localised (when required) with > 90% confidence: 2446 out of 2520

[82:20] Cross-run analysis
[82:20] Reading quantification information: 6 files
[82:22] Target precursors at 1% global q-value: 122399
[82:22] Quantifying peptides
[83:15] Quantification parameters: 0.309476, 0.00145372, 0.00137126, 0.0120497, 0.0119677, 0.0120172, 0.137946, 0.201727, 0.159718, 0.0131687, 0.0357114, 0.014329, 0.303174, 0.0524547, 0.0735857, 0.0110946
[83:15] Quantifying proteins
[83:16] Calculating q-values for protein and gene groups
[83:16] Calculating global q-values for protein and gene groups
[83:16] Protein groups with global q-value <= 0.01: 11327
[83:19] Compressed report saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[83:19] Stats report saved to /home/robbe/PB_output/results/AstralManuscript/HYE_Astral/diann_v2.5.0/report.stats.tsv

