
DIA-NN 2.5.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Apr 12 2026 10:45:33
Current date and time: Tue Aug  4 14:24:35 2026
Logical CPU cores: 128
/usr/diann-2.5.0/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_v2.5.0/report.tsv --temp /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0 --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
[0:08] Processing FASTA
[0:11] Assembling elution groups
[0:20] 5055014 precursors generated
[0:20] Protein names missing for some isoforms
[0:20] Gene names missing for some isoforms
[0:20] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:33] [0:50] [29:28] [31:23] [31:26] [31:30] Saving the library to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report-lib.predicted.speclib
[31:34] Initialising library
[31:50] Loading spectral library /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report-lib.predicted.speclib
[31:53] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[31:54] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5055014 precursors in 2602499 elution groups (targets and decoys).
[31:54] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[31:54] Annotating library proteins with information from the FASTA database
[31:54] Protein names missing for some isoforms
[31:54] Gene names missing for some isoforms
[31:54] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[31:59] Initialising library

First pass: generating a spectral library from DIA data

[32:14] File #1/6
[32:14] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[32:36] Pre-processing...
[32:38] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 5050223 precursors in range
[32:39] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[33:20] RT window set to 1.11215
[33:20] Peak width: 2.828
[33:20] Scan window radius set to 6
[33:20] Recommended MS1 mass accuracy setting: 2.6 ppm
[34:02] Optimised mass accuracy: 7 ppm
[34:15] Searching decoys
[35:24] Main search
[37:35] Removing low confidence identifications
[38:03] Removing interfering precursors
[38:17] Training neural networks on 214204 target and 133420 decoy PSMs
[39:59] Training neural networks on 214204 target and 134392 decoy PSMs
[41:44] Precursors at 1% peptidoform FDR: 104574
[41:46] Number of IDs at 0.01 FDR: 106266
[41:46] Calculating protein q-values
[41:47] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[41:47] Quantification
[41:49] Precursors with scored PTMs at 1% FDR: 2297 out of 2422 considered
[41:49] Precursors with all scored PTM sites unoccupied at 1% FDR: 102277
[41:49] Precursors with PTMs localised (when required) with > 90% confidence: 2209 out of 2297
[41:50] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP1_raw.quant

[41:50] File #2/6
[41:50] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[42:09] Pre-processing...
[42:10] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[42:11] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[42:55] RT window set to 1.16475
[42:55] Recommended MS1 mass accuracy setting: 2.6 ppm
[43:06] Searching decoys
[44:09] Main search
[46:48] Removing low confidence identifications
[47:22] Removing interfering precursors
[47:38] Training neural networks on 220942 target and 135960 decoy PSMs
[49:46] Training neural networks on 220942 target and 138069 decoy PSMs
[51:42] Precursors at 1% peptidoform FDR: 106433
[51:44] Number of IDs at 0.01 FDR: 109336
[51:44] Calculating protein q-values
[51:45] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[51:46] Quantification
[51:48] Precursors with scored PTMs at 1% FDR: 2367 out of 2673 considered
[51:48] Precursors with all scored PTM sites unoccupied at 1% FDR: 104066
[51:48] Precursors with PTMs localised (when required) with > 90% confidence: 2283 out of 2367
[51:51] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP2_raw.quant

[51:51] File #3/6
[51:51] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[52:11] Pre-processing...
[52:12] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[52:13] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[52:59] RT window set to 1.24321
[52:59] Recommended MS1 mass accuracy setting: 2.8 ppm
[53:11] Searching decoys
[54:46] Main search
[57:34] Removing low confidence identifications
[58:05] Removing interfering precursors
[58:28] Training neural networks on 220299 target and 136083 decoy PSMs
[60:32] Training neural networks on 220299 target and 137746 decoy PSMs
[62:28] Precursors at 1% peptidoform FDR: 106658
[62:30] Number of IDs at 0.01 FDR: 110259
[62:30] Calculating protein q-values
[62:30] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[62:30] Quantification
[62:33] Precursors with scored PTMs at 1% FDR: 2283 out of 2632 considered
[62:33] Precursors with all scored PTM sites unoccupied at 1% FDR: 104375
[62:33] Precursors with PTMs localised (when required) with > 90% confidence: 2200 out of 2283
[62:34] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP3_raw.quant

[62:34] File #4/6
[62:34] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[62:55] Pre-processing...
[62:57] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[62:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[63:28] RT window set to 1.46489
[63:28] Recommended MS1 mass accuracy setting: 3.1 ppm
[63:45] Searching decoys
[65:14] Main search
[68:29] Removing low confidence identifications
[69:02] Removing interfering precursors
[69:17] Training neural networks on 221936 target and 139590 decoy PSMs
[71:19] Training neural networks on 221936 target and 140327 decoy PSMs
[73:15] Precursors at 1% peptidoform FDR: 108018
[73:17] Number of IDs at 0.01 FDR: 110664
[73:17] Calculating protein q-values
[73:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[73:18] Quantification
[73:21] Precursors with scored PTMs at 1% FDR: 3002 out of 3202 considered
[73:21] Precursors with all scored PTM sites unoccupied at 1% FDR: 105016
[73:21] Precursors with PTMs localised (when required) with > 90% confidence: 2890 out of 3002
[73:22] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP1_raw.quant

[73:22] File #5/6
[73:22] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[73:44] Pre-processing...
[73:46] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[73:47] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[74:31] RT window set to 1.27025
[74:31] Recommended MS1 mass accuracy setting: 2.9 ppm
[74:44] Searching decoys
[76:21] Main search
[79:00] Removing low confidence identifications
[79:32] Removing interfering precursors
[79:45] Training neural networks on 219812 target and 137471 decoy PSMs
[81:37] Training neural networks on 219812 target and 138575 decoy PSMs
[83:16] Precursors at 1% peptidoform FDR: 107099
[83:19] Number of IDs at 0.01 FDR: 109508
[83:19] Calculating protein q-values
[83:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[83:20] Quantification
[83:22] Precursors with scored PTMs at 1% FDR: 2999 out of 3197 considered
[83:22] Precursors with all scored PTM sites unoccupied at 1% FDR: 104072
[83:22] Precursors with PTMs localised (when required) with > 90% confidence: 2900 out of 2999
[83:23] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP2_raw.quant

[83:23] File #6/6
[83:23] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[83:48] Pre-processing...
[83:49] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[83:50] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[84:22] RT window set to 1.2182
[84:22] Recommended MS1 mass accuracy setting: 2.7 ppm
[84:31] Searching decoys
[85:21] Main search
[87:32] Removing low confidence identifications
[87:59] Removing interfering precursors
[88:14] Training neural networks on 222141 target and 138470 decoy PSMs
[90:07] Training neural networks on 222141 target and 140481 decoy PSMs
[91:54] Precursors at 1% peptidoform FDR: 107476
[91:57] Number of IDs at 0.01 FDR: 110393
[91:57] Calculating protein q-values
[91:58] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[91:58] Quantification
[92:01] Precursors with scored PTMs at 1% FDR: 2954 out of 3224 considered
[92:01] Precursors with all scored PTM sites unoccupied at 1% FDR: 104522
[92:01] Precursors with PTMs localised (when required) with > 90% confidence: 2848 out of 2954
[92:02] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP3_raw.quant

[92:02] Cross-run analysis
[92:02] Reading quantification information: 6 files
[92:22] Target precursors at 1% global q-value: 141403
[92:22] Quantifying peptides
[93:23] Assembling protein groups
[93:25] Quantifying proteins
[93:26] Calculating q-values for protein and gene groups
[93:29] Calculating global q-values for protein and gene groups
[93:29] Protein groups with global q-value <= 0.01: 11982
[93:34] Compressed report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[93:34] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report-first-pass.stats.tsv
[93:35] Generating spectral library:
[93:39] 152340 target and 7782 decoy precursors saved
WARNING: 27786 precursors without any fragments annotated were skipped
[93:39] Spectral library saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report-lib.parquet

[93:42] Loading spectral library /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report-lib.parquet
[93:44] Spectral library loaded: 17714 protein isoforms, 17628 protein groups and 160122 precursors in 149010 elution groups (targets and decoys).
[93:44] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[93:45] Annotating library proteins with information from the FASTA database
[93:45] Gene names missing for some isoforms
[93:45] Library contains 17705 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[93:45] Initialising library
[93:48] Saving the library to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report-lib.parquet.skyline.speclib


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

[93:48] File #1/6
[93:48] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[94:10] Pre-processing...
[94:11] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 152340 precursors in range
[94:11] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[94:12] RT window set to 0.433433
[94:13] Recommended MS1 mass accuracy setting: 3.1 ppm
[94:13] Searching decoys
[94:14] Main search
[94:18] Removing low confidence identifications
[94:25] Removing interfering precursors
[94:28] Training neural networks on 122322 target and 62842 decoy PSMs
[95:15] Training neural networks on 122137 target and 68657 decoy PSMs
[96:01] Precursors at 1% peptidoform FDR: 98948
[96:01] Number of IDs at 0.01 FDR: 101480
[96:01] Calculating protein q-values
[96:01] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[96:01] Quantification
[96:02] Precursors with scored PTMs at 1% FDR: 2147 out of 2253 considered
[96:02] Precursors with all scored PTM sites unoccupied at 1% FDR: 97472
[96:02] Precursors with PTMs localised (when required) with > 90% confidence: 2070 out of 2147

[96:03] File #2/6
[96:03] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[96:23] Pre-processing...
[96:24] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 152340 precursors in range
[96:24] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[96:25] RT window set to 0.426916
[96:25] Recommended MS1 mass accuracy setting: 2.8 ppm
[96:26] Searching decoys
[96:27] Main search
[96:31] Removing low confidence identifications
[96:36] Removing interfering precursors
[96:39] Training neural networks on 122567 target and 62076 decoy PSMs
[97:22] Training neural networks on 122380 target and 68322 decoy PSMs
[98:06] Precursors at 1% peptidoform FDR: 99469
[98:07] Number of IDs at 0.01 FDR: 101678
[98:07] Calculating protein q-values
[98:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[98:07] Quantification
[98:08] Precursors with scored PTMs at 1% FDR: 2194 out of 2304 considered
[98:08] Precursors with all scored PTM sites unoccupied at 1% FDR: 97932
[98:08] Precursors with PTMs localised (when required) with > 90% confidence: 2136 out of 2194

[98:09] File #3/6
[98:09] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[98:47] Pre-processing...
[98:48] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 152340 precursors in range
[98:48] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[98:49] RT window set to 0.429875
[98:49] Recommended MS1 mass accuracy setting: 3 ppm
[98:50] Searching decoys
[98:51] Main search
[98:55] Removing low confidence identifications
[99:01] Removing interfering precursors
[99:04] Training neural networks on 122609 target and 61065 decoy PSMs
[99:46] Training neural networks on 122415 target and 68137 decoy PSMs
[100:32] Precursors at 1% peptidoform FDR: 100087
[100:32] Number of IDs at 0.01 FDR: 102067
[100:32] Calculating protein q-values
[100:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[100:32] Quantification
[100:33] Precursors with scored PTMs at 1% FDR: 2205 out of 2282 considered
[100:33] Precursors with all scored PTM sites unoccupied at 1% FDR: 98408
[100:33] Precursors with PTMs localised (when required) with > 90% confidence: 2136 out of 2205

[100:34] File #4/6
[100:34] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[100:55] Pre-processing...
[100:56] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 152340 precursors in range
[100:56] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[100:57] RT window set to 0.459343
[100:57] Recommended MS1 mass accuracy setting: 3.1 ppm
[100:57] Searching decoys
[100:59] Main search
[101:03] Removing low confidence identifications
[101:09] Removing interfering precursors
[101:12] Training neural networks on 121548 target and 61325 decoy PSMs
[101:57] Training neural networks on 121307 target and 67951 decoy PSMs
[103:00] Precursors at 1% peptidoform FDR: 99285
[103:00] Number of IDs at 0.01 FDR: 101541
[103:00] Calculating protein q-values
[103:00] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[103:00] Quantification
[103:02] Precursors with scored PTMs at 1% FDR: 2467 out of 2587 considered
[103:02] Precursors with all scored PTM sites unoccupied at 1% FDR: 97590
[103:02] Precursors with PTMs localised (when required) with > 90% confidence: 2385 out of 2467

[103:02] File #5/6
[103:02] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[103:23] Pre-processing...
[103:24] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 152340 precursors in range
[103:24] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[103:26] RT window set to 0.451496
[103:26] Recommended MS1 mass accuracy setting: 3.1 ppm
[103:27] Searching decoys
[103:28] Main search
[103:32] Removing low confidence identifications
[103:38] Removing interfering precursors
[103:41] Training neural networks on 123209 target and 62178 decoy PSMs
[104:31] Training neural networks on 122987 target and 69112 decoy PSMs
[105:25] Precursors at 1% peptidoform FDR: 101593
[105:26] Number of IDs at 0.01 FDR: 104406
[105:26] Calculating protein q-values
[105:26] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[105:26] Quantification
[105:27] Precursors with scored PTMs at 1% FDR: 2516 out of 2667 considered
[105:27] Precursors with all scored PTM sites unoccupied at 1% FDR: 99970
[105:27] Precursors with PTMs localised (when required) with > 90% confidence: 2435 out of 2516

[105:28] File #6/6
[105:28] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[105:48] Pre-processing...
[105:49] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 152340 precursors in range
[105:49] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[105:51] RT window set to 0.454539
[105:51] Recommended MS1 mass accuracy setting: 2.8 ppm
[105:51] Searching decoys
[105:53] Main search
[105:57] Removing low confidence identifications
[106:04] Removing interfering precursors
[106:07] Training neural networks on 121177 target and 60893 decoy PSMs
[107:03] Training neural networks on 120978 target and 67951 decoy PSMs
[107:55] Precursors at 1% peptidoform FDR: 99470
[107:55] Number of IDs at 0.01 FDR: 101819
[107:55] Calculating protein q-values
[107:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[107:55] Quantification
[107:57] Precursors with scored PTMs at 1% FDR: 2488 out of 2603 considered
[107:57] Precursors with all scored PTM sites unoccupied at 1% FDR: 97911
[107:57] Precursors with PTMs localised (when required) with > 90% confidence: 2411 out of 2488

[107:57] Cross-run analysis
[107:57] Reading quantification information: 6 files
[108:01] Target precursors at 1% global q-value: 121827
[108:01] Quantifying peptides
[109:37] Quantification parameters: 0.30999, 0.00144921, 0.00140181, 0.0118248, 0.0118632, 0.0119153, 0.127298, 0.211139, 0.165423, 0.0130781, 0.0324499, 0.0141804, 0.29842, 0.0527987, 0.0762826, 0.0113671
[109:54] Quantifying proteins
[109:54] Calculating q-values for protein and gene groups
[109:55] Calculating global q-values for protein and gene groups
[109:55] Protein groups with global q-value <= 0.01: 11438
[109:59] Compressed report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[109:59] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.5.0/report.stats.tsv

