
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 Aug  4 14:24:35 2026
Logical CPU cores: 128
/usr/diann-2.1.0/diann --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/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report.tsv --temp /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0 --threads 100 --missed-cleavages 1 --min-pep-len 6 --max-pep-len 30 --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* --gen-spec-lib --predictor --unimod4 --var-mod UniMod:35,15.994915,M --var-mods 1 --gen-spec-lib --fasta-search --reanalyse 

Thread number set to 100
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*
A spectral library will be generated
Deep learning will be used to generate a new in silico spectral library from peptides provided
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
DIA-NN will automatically optimise the mass accuracy for the first run of the experiment, use this mode for preliminary analyses only
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
[0:10] Processing FASTA
[0:14] Assembling elution groups
[0:25] 5055014 precursors generated
[0:25] Protein names missing for some isoforms
[0:25] Gene names missing for some isoforms
[0:25] Library contains 31685 proteins, and 0 genes
[0:38] [1:02] [24:51] [26:23] [26:29] [26:34] Saving the library to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report-lib.predicted.speclib
[26:40] Initialising library
[27:04] Loading spectral library /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report-lib.predicted.speclib
[27:07] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[27:09] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5055014 precursors in 2602499 elution groups.
[27:09] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[27:09] Annotating library proteins with information from the FASTA database
[27:09] Protein names missing for some isoforms
[27:09] Gene names missing for some isoforms
[27:09] Library contains 31685 proteins, and 0 genes
[27:15] Initialising library

First pass: generating a spectral library from DIA data

[27:40] File #1/6
[27:40] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[29:52] Pre-processing...
[29:57] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 5050223 precursors in range
[29:58] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[30:42] RT window set to 1.16387
[30:42] Peak width: 2.692
[30:42] Scan window radius set to 5
[30:42] Recommended MS1 mass accuracy setting: 2.3 ppm
[31:30] Optimised mass accuracy: 7 ppm
[31:51] Searching decoys
[32:29] Main search
[34:26] Removing low confidence identifications
[34:51] Removing interfering precursors
[35:05] Training neural networks on 209989 target and 128496 decoy PSMs
[37:21] Training neural networks on 209989 target and 130661 decoy PSMs
[39:23] Number of IDs at 0.01 FDR: 103187
[39:24] Precursors at 1% peptidoform FDR: 100814
[39:25] Calculating protein q-values
[39:26] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[39:26] Quantification
[39:28] Precursors with scored PTMs at 1% FDR: 2195 out of 2378 considered
[39:28] Precursors with all scored PTM sites unoccupied at 1% FDR: 98619
[39:28] Precursors with PTMs localised (when required) with > 90% confidence: 2127 out of 2195
[39:29] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP1_raw.quant

[39:29] File #2/6
[39:29] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[41:13] Pre-processing...
[41:17] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[41:18] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[42:01] RT window set to 1.20789
[42:01] Recommended MS1 mass accuracy setting: 2.3 ppm
[42:23] Searching decoys
[42:51] Main search
[43:44] Removing low confidence identifications
[44:03] Removing interfering precursors
[44:16] Training neural networks on 212108 target and 129676 decoy PSMs
[46:12] Training neural networks on 212108 target and 131126 decoy PSMs
[47:36] Number of IDs at 0.01 FDR: 104464
[47:37] Precursors at 1% peptidoform FDR: 101679
[47:39] Calculating protein q-values
[47:40] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[47:40] Quantification
[47:41] Precursors with scored PTMs at 1% FDR: 2314 out of 2498 considered
[47:41] Precursors with all scored PTM sites unoccupied at 1% FDR: 99365
[47:41] Precursors with PTMs localised (when required) with > 90% confidence: 2245 out of 2314
[47:43] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP2_raw.quant

[47:43] File #3/6
[47:43] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[49:53] Pre-processing...
[49:57] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[49:59] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[50:34] RT window set to 1.11993
[50:34] Recommended MS1 mass accuracy setting: 2.6 ppm
[50:59] Searching decoys
[51:41] Main search
[53:08] Removing low confidence identifications
[53:28] Removing interfering precursors
[53:42] Training neural networks on 211811 target and 129451 decoy PSMs
[55:23] Training neural networks on 211811 target and 130975 decoy PSMs
[57:10] Number of IDs at 0.01 FDR: 105249
[57:11] Precursors at 1% peptidoform FDR: 102167
[57:12] Calculating protein q-values
[57:13] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[57:13] Quantification
[57:15] Precursors with scored PTMs at 1% FDR: 2304 out of 2497 considered
[57:15] Precursors with all scored PTM sites unoccupied at 1% FDR: 99863
[57:15] Precursors with PTMs localised (when required) with > 90% confidence: 2238 out of 2304
[57:16] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP3_raw.quant

[57:16] File #4/6
[57:16] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[59:20] Pre-processing...
[59:26] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[59:27] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[60:01] RT window set to 1.21925
[60:01] Recommended MS1 mass accuracy setting: 2.5 ppm
[60:27] Searching decoys
[61:11] Main search
[62:36] Removing low confidence identifications
[62:58] Removing interfering precursors
[63:12] Training neural networks on 214550 target and 133394 decoy PSMs
[65:01] Training neural networks on 214550 target and 134396 decoy PSMs
[66:25] Number of IDs at 0.01 FDR: 104772
[66:26] Precursors at 1% peptidoform FDR: 101925
[66:28] Calculating protein q-values
[66:29] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[66:29] Quantification
[66:31] Precursors with scored PTMs at 1% FDR: 2791 out of 3090 considered
[66:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 99134
[66:31] Precursors with PTMs localised (when required) with > 90% confidence: 2713 out of 2791
[66:32] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP1_raw.quant

[66:32] File #5/6
[66:32] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[68:42] Pre-processing...
[68:48] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[68:49] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[69:24] RT window set to 1.26939
[69:24] Recommended MS1 mass accuracy setting: 2.8 ppm
[69:50] Searching decoys
[70:15] Main search
[71:08] Removing low confidence identifications
[71:27] Removing interfering precursors
[71:41] Training neural networks on 213136 target and 132065 decoy PSMs
[73:04] Training neural networks on 213136 target and 132974 decoy PSMs
[74:40] Number of IDs at 0.01 FDR: 105180
[74:41] Precursors at 1% peptidoform FDR: 102727
[74:43] Calculating protein q-values
[74:44] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[74:44] Quantification
[74:45] Precursors with scored PTMs at 1% FDR: 2899 out of 3121 considered
[74:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 99828
[74:45] Precursors with PTMs localised (when required) with > 90% confidence: 2817 out of 2899
[74:46] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP2_raw.quant

[74:47] File #6/6
[74:47] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[77:01] Pre-processing...
[77:07] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[77:08] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[77:50] RT window set to 1.05492
[77:50] Recommended MS1 mass accuracy setting: 2.5 ppm
[78:14] Searching decoys
[78:43] Main search
[79:53] Removing low confidence identifications
[80:15] Removing interfering precursors
[80:28] Training neural networks on 211375 target and 128738 decoy PSMs
[82:09] Training neural networks on 211375 target and 130258 decoy PSMs
[83:32] Number of IDs at 0.01 FDR: 104388
[83:33] Precursors at 1% peptidoform FDR: 101788
[83:34] Calculating protein q-values
[83:34] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[83:34] Quantification
[83:36] Precursors with scored PTMs at 1% FDR: 2848 out of 3098 considered
[83:36] Precursors with all scored PTM sites unoccupied at 1% FDR: 98940
[83:36] Precursors with PTMs localised (when required) with > 90% confidence: 2748 out of 2848
[83:37] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP3_raw.quant

[83:37] Cross-run analysis
[83:37] Reading quantification information: 6 files
[83:57] Quantifying peptides
[88:50] Assembling protein groups
[88:54] Quantifying proteins
[88:55] Calculating q-values for protein and gene groups
[88:58] Calculating global q-values for protein and gene groups
[88:58] Protein groups with global q-value <= 0.01: 11426
[89:03] Compressed report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[89:03] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report-first-pass.stats.tsv
[89:04] Generating spectral library:
[89:07] 132146 target and 1229 decoy precursors saved
WARNING: 3193 precursors without any fragments annotated were skipped
[89:07] Spectral library saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report-lib.parquet

[89:11] Loading spectral library /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report-lib.parquet
[89:12] Spectral library loaded: 13107 protein isoforms, 12941 protein groups and 133375 precursors in 124146 elution groups.
[89:12] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[89:13] Annotating library proteins with information from the FASTA database
[89:13] Gene names missing for some isoforms
[89:13] Library contains 13097 proteins, and 0 genes
[89:13] Initialising library
[89:14] Saving the library to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report-lib.parquet.skyline.speclib


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

[89:14] File #1/6
[89:14] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[91:53] Pre-processing...
[91:57] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 132146 precursors in range
[91:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[91:58] RT window set to 0.42568
[91:58] Recommended MS1 mass accuracy setting: 2.8 ppm
[91:59] Searching decoys
[92:00] Main search
[92:03] Removing low confidence identifications
[92:08] Removing interfering precursors
[92:10] Training neural networks on 113498 target and 56137 decoy PSMs
[92:54] Training neural networks on 113454 target and 62112 decoy PSMs
[93:34] Number of IDs at 0.01 FDR: 108510
[93:35] Precursors at 1% peptidoform FDR: 106906
[93:35] Calculating protein q-values
[93:35] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[93:35] Quantification
[93:36] Precursors with scored PTMs at 1% FDR: 2551 out of 2629 considered
[93:36] Precursors with all scored PTM sites unoccupied at 1% FDR: 104355
[93:36] Precursors with PTMs localised (when required) with > 90% confidence: 2477 out of 2551

[93:37] File #2/6
[93:37] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[95:41] Pre-processing...
[95:45] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 132146 precursors in range
[95:45] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[95:46] RT window set to 0.427102
[95:46] Recommended MS1 mass accuracy setting: 2.9 ppm
[95:46] Searching decoys
[95:47] Main search
[95:50] Removing low confidence identifications
[95:55] Removing interfering precursors
[95:58] Training neural networks on 113890 target and 56187 decoy PSMs
[96:41] Training neural networks on 113853 target and 62222 decoy PSMs
[97:35] Number of IDs at 0.01 FDR: 109418
[97:36] Precursors at 1% peptidoform FDR: 108285
[97:36] Calculating protein q-values
[97:36] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[97:36] Quantification
[97:37] Precursors with scored PTMs at 1% FDR: 2639 out of 2676 considered
[97:37] Precursors with all scored PTM sites unoccupied at 1% FDR: 105646
[97:37] Precursors with PTMs localised (when required) with > 90% confidence: 2562 out of 2639

[97:38] File #3/6
[97:38] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[99:53] Pre-processing...
[99:57] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 132146 precursors in range
[99:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[99:58] RT window set to 0.435013
[99:58] Recommended MS1 mass accuracy setting: 3.1 ppm
[99:59] Searching decoys
[99:59] Main search
[100:02] Removing low confidence identifications
[100:07] Removing interfering precursors
[100:09] Training neural networks on 113817 target and 56196 decoy PSMs
[101:01] Training neural networks on 113771 target and 62397 decoy PSMs
[101:43] Number of IDs at 0.01 FDR: 109172
[101:44] Precursors at 1% peptidoform FDR: 108146
[101:44] Calculating protein q-values
[101:44] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[101:44] Quantification
[101:45] Precursors with scored PTMs at 1% FDR: 2624 out of 2681 considered
[101:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 105522
[101:45] Precursors with PTMs localised (when required) with > 90% confidence: 2552 out of 2624

[101:46] File #4/6
[101:46] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[103:56] Pre-processing...
[104:00] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 132146 precursors in range
[104:00] Calibrating with mass accuracies 22 (MS1), 25 (MS2)
[104:01] RT window set to 0.45874
[104:01] Recommended MS1 mass accuracy setting: 2.7 ppm
[104:02] Searching decoys
[104:03] Main search
[104:05] Removing low confidence identifications
[104:09] Removing interfering precursors
[104:12] Training neural networks on 114161 target and 57032 decoy PSMs
[104:58] Training neural networks on 114121 target and 63083 decoy PSMs
[105:44] Number of IDs at 0.01 FDR: 109462
[105:45] Precursors at 1% peptidoform FDR: 108489
[105:45] Calculating protein q-values
[105:45] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[105:45] Quantification
[105:46] Precursors with scored PTMs at 1% FDR: 2876 out of 2904 considered
[105:46] Precursors with all scored PTM sites unoccupied at 1% FDR: 105613
[105:46] Precursors with PTMs localised (when required) with > 90% confidence: 2785 out of 2876

[105:47] File #5/6
[105:47] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[107:52] Pre-processing...
[107:57] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 132146 precursors in range
[107:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[107:57] RT window set to 0.443028
[107:57] Recommended MS1 mass accuracy setting: 2.8 ppm
[107:58] Searching decoys
[107:59] Main search
[108:02] Removing low confidence identifications
[108:08] Removing interfering precursors
[108:10] Training neural networks on 114213 target and 57155 decoy PSMs
[108:57] Training neural networks on 114169 target and 62951 decoy PSMs
[109:55] Number of IDs at 0.01 FDR: 110327
[109:55] Precursors at 1% peptidoform FDR: 109174
[109:55] Calculating protein q-values
[109:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[109:55] Quantification
[109:57] Precursors with scored PTMs at 1% FDR: 2945 out of 2982 considered
[109:57] Precursors with all scored PTM sites unoccupied at 1% FDR: 106229
[109:57] Precursors with PTMs localised (when required) with > 90% confidence: 2868 out of 2945

[109:57] File #6/6
[109:57] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[112:13] Pre-processing...
[112:17] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 132146 precursors in range
[112:17] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[112:17] RT window set to 0.45234
[112:18] Recommended MS1 mass accuracy setting: 3 ppm
[112:18] Searching decoys
[112:19] Main search
[112:21] Removing low confidence identifications
[112:26] Removing interfering precursors
[112:28] Training neural networks on 113991 target and 57108 decoy PSMs
[113:12] Training neural networks on 113947 target and 63056 decoy PSMs
[113:56] Number of IDs at 0.01 FDR: 109661
[113:56] Precursors at 1% peptidoform FDR: 108659
[113:56] Calculating protein q-values
[113:56] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[113:56] Quantification
[113:58] Precursors with scored PTMs at 1% FDR: 2926 out of 2976 considered
[113:58] Precursors with all scored PTM sites unoccupied at 1% FDR: 105733
[113:58] Precursors with PTMs localised (when required) with > 90% confidence: 2844 out of 2926

[113:58] Cross-run analysis
[113:58] Reading quantification information: 6 files
[114:01] Quantifying peptides
[116:52] Quantification parameters: 0.31545, 0.00139903, 0.0014106, 0.0120611, 0.0118693, 0.0119387, 0.143821, 0.239655, 0.170036, 0.0133224, 0.0333261, 0.01422, 0.320606, 0.0524623, 0.0733772, 0.0113199
[118:14] Quantifying proteins
[118:15] Calculating q-values for protein and gene groups
[118:15] Calculating global q-values for protein and gene groups
[118:15] Protein groups with global q-value <= 0.01: 10902
[118:20] Compressed report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[118:20] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.1.0/report.stats.tsv

