
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 Jun 30 13:02:59 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/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report.tsv --temp /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0 --threads 40 --missed-cleavages 1 --min-pep-len 6 --max-pep-len 30 --mass-acc 10 --mass-acc-ms1 5 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 1 --max-pr-charge 5 --min-pr-mz 400 --max-pr-mz 1000 --min-fr-mz 100 --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 40
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 1000
Min fragment m/z set to 100
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 5e-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
[0:04] Processing FASTA
[0:05] Assembling elution groups
[0:10] 4902976 precursors generated
[0:10] Protein names missing for some isoforms
[0:10] Gene names missing for some isoforms
[0:10] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:14] [0:22] [2:23] [2:40] [2:42] [2:44] Saving the library to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report-lib.predicted.speclib
[2:47] Initialising library
[2:55] Loading spectral library /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report-lib.predicted.speclib
[2:57] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[2:58] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 4902976 precursors in 2602499 elution groups (targets and decoys).
[2:58] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[2:58] Annotating library proteins with information from the FASTA database
[2:58] Protein names missing for some isoforms
[2:58] Gene names missing for some isoforms
[2:58] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[3:01] Initialising library

First pass: generating a spectral library from DIA data

[3:09] File #1/6
[3:09] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[4:01] Pre-processing...
[4:02] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 4811219 precursors in range
[4:03] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[4:13] RT window set to 1.23175
[4:13] Peak width: 2.904
[4:13] Scan window radius set to 6
[4:13] Recommended MS1 mass accuracy setting: 2.8 ppm
[4:17] Searching decoys
[4:36] Main search
[5:14] Removing low confidence identifications
[5:30] Removing interfering precursors
[5:40] Training neural networks on 292510 target and 254344 decoy PSMs
[6:24] Training neural networks on 292510 target and 250439 decoy PSMs
[7:05] Precursors at 1% peptidoform FDR: 102774
[7:07] Number of IDs at 0.01 FDR: 105016
[7:07] Calculating protein q-values
[7:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[7:07] Quantification
[7:08] Precursors with scored PTMs at 1% FDR: 2368 out of 2528 considered
[7:08] Precursors with all scored PTM sites unoccupied at 1% FDR: 100406
[7:08] Precursors with PTMs localised (when required) with > 90% confidence: 2276 out of 2368
[7:09] Quantification information saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP1_raw.quant

[7:09] File #2/6
[7:09] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[8:00] Pre-processing...
[8:01] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4811219 precursors in range
[8:02] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[8:12] RT window set to 1.15308
[8:12] Recommended MS1 mass accuracy setting: 2.6 ppm
[8:16] Searching decoys
[8:34] Main search
[9:11] Removing low confidence identifications
[9:27] Removing interfering precursors
[9:37] Training neural networks on 308683 target and 266015 decoy PSMs
[10:23] Training neural networks on 308683 target and 261225 decoy PSMs
[11:06] Precursors at 1% peptidoform FDR: 104292
[11:08] Number of IDs at 0.01 FDR: 106917
[11:08] Calculating protein q-values
[11:08] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[11:08] Quantification
[11:09] Precursors with scored PTMs at 1% FDR: 2463 out of 2667 considered
[11:09] Precursors with all scored PTM sites unoccupied at 1% FDR: 101829
[11:09] Precursors with PTMs localised (when required) with > 90% confidence: 2378 out of 2463
[11:10] Quantification information saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP2_raw.quant

[11:10] File #3/6
[11:10] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[12:03] Pre-processing...
[12:04] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4811219 precursors in range
[12:04] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[12:15] RT window set to 1.19731
[12:15] Recommended MS1 mass accuracy setting: 2.5 ppm
[12:19] Searching decoys
[12:38] Main search
[13:16] Removing low confidence identifications
[13:31] Removing interfering precursors
[13:42] Training neural networks on 305180 target and 263212 decoy PSMs
[14:27] Training neural networks on 305180 target and 259532 decoy PSMs
[15:10] Precursors at 1% peptidoform FDR: 104811
[15:11] Number of IDs at 0.01 FDR: 107525
[15:11] Calculating protein q-values
[15:11] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[15:11] Quantification
[15:12] Precursors with scored PTMs at 1% FDR: 2459 out of 2655 considered
[15:12] Precursors with all scored PTM sites unoccupied at 1% FDR: 102352
[15:12] Precursors with PTMs localised (when required) with > 90% confidence: 2362 out of 2459
[15:13] Quantification information saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP3_raw.quant

[15:13] File #4/6
[15:13] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[16:07] Pre-processing...
[16:08] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4811219 precursors in range
[16:08] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[16:19] RT window set to 1.31196
[16:19] Recommended MS1 mass accuracy setting: 2.6 ppm
[16:23] Searching decoys
[16:44] Main search
[17:24] Removing low confidence identifications
[17:40] Removing interfering precursors
[17:51] Training neural networks on 313958 target and 269140 decoy PSMs
[18:38] Training neural networks on 313958 target and 264724 decoy PSMs
[19:21] Precursors at 1% peptidoform FDR: 105052
[19:23] Number of IDs at 0.01 FDR: 107694
[19:23] Calculating protein q-values
[19:23] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[19:23] Quantification
[19:24] Precursors with scored PTMs at 1% FDR: 3111 out of 3307 considered
[19:24] Precursors with all scored PTM sites unoccupied at 1% FDR: 101941
[19:24] Precursors with PTMs localised (when required) with > 90% confidence: 2994 out of 3111
[19:25] Quantification information saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP1_raw.quant

[19:25] File #5/6
[19:25] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[20:20] Pre-processing...
[20:21] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4811219 precursors in range
[20:21] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[20:32] RT window set to 1.24145
[20:32] Recommended MS1 mass accuracy setting: 2.5 ppm
[20:36] Searching decoys
[20:56] Main search
[21:36] Removing low confidence identifications
[21:51] Removing interfering precursors
[22:02] Training neural networks on 306909 target and 267836 decoy PSMs
[22:48] Training neural networks on 306909 target and 264301 decoy PSMs
[23:32] Precursors at 1% peptidoform FDR: 104800
[23:33] Number of IDs at 0.01 FDR: 107313
[23:33] Calculating protein q-values
[23:33] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[23:33] Quantification
[23:34] Precursors with scored PTMs at 1% FDR: 3144 out of 3354 considered
[23:34] Precursors with all scored PTM sites unoccupied at 1% FDR: 101656
[23:34] Precursors with PTMs localised (when required) with > 90% confidence: 3032 out of 3144
[23:35] Quantification information saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP2_raw.quant

[23:35] File #6/6
[23:35] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[24:29] Pre-processing...
[24:30] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4811219 precursors in range
[24:31] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[24:41] RT window set to 1.18796
[24:41] Recommended MS1 mass accuracy setting: 2.7 ppm
[24:45] Searching decoys
[25:04] Main search
[25:42] Removing low confidence identifications
[25:58] Removing interfering precursors
[26:08] Training neural networks on 313568 target and 267552 decoy PSMs
[26:56] Training neural networks on 313568 target and 264287 decoy PSMs
[27:39] Precursors at 1% peptidoform FDR: 104564
[27:41] Number of IDs at 0.01 FDR: 107172
[27:41] Calculating protein q-values
[27:41] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[27:41] Quantification
[27:42] Precursors with scored PTMs at 1% FDR: 3107 out of 3333 considered
[27:42] Precursors with all scored PTM sites unoccupied at 1% FDR: 101457
[27:42] Precursors with PTMs localised (when required) with > 90% confidence: 2986 out of 3107
[27:43] Quantification information saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP3_raw.quant

[27:43] Cross-run analysis
[27:43] Reading quantification information: 6 files
[27:57] Target precursors at 1% global q-value: 137942
[27:57] Quantifying peptides
[28:14] Assembling protein groups
[28:15] Quantifying proteins
[28:16] Calculating q-values for protein and gene groups
[28:17] Calculating global q-values for protein and gene groups
[28:17] Protein groups with global q-value <= 0.01: 11971
[28:20] Compressed report saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[28:20] Stats report saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report-first-pass.stats.tsv
[28:20] Generating spectral library:
[28:22] 148906 target and 7882 decoy precursors saved
WARNING: 24655 precursors without any fragments annotated were skipped
[28:23] Spectral library saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report-lib.parquet

[28:23] Loading spectral library /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report-lib.parquet
[28:24] Spectral library loaded: 17801 protein isoforms, 17726 protein groups and 156788 precursors in 146543 elution groups (targets and decoys).
[28:24] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[28:25] Annotating library proteins with information from the FASTA database
[28:25] Protein names missing for some isoforms
[28:25] Gene names missing for some isoforms
[28:25] Library contains 17796 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[28:25] Initialising library
[28:26] Saving the library to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report-lib.parquet.skyline.speclib


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

[28:26] File #1/6
[28:26] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[28:46] Pre-processing...
[28:46] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 148906 precursors in range
[28:46] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[28:47] RT window set to 0.442318
[28:47] Recommended MS1 mass accuracy setting: 3.1 ppm
[28:47] Searching decoys
[28:47] Main search
[28:49] Removing low confidence identifications
[28:52] Removing interfering precursors
[28:53] Training neural networks on 119861 target and 62391 decoy PSMs
[29:06] Training neural networks on 119683 target and 66678 decoy PSMs
[29:19] Precursors at 1% peptidoform FDR: 95064
[29:20] Number of IDs at 0.01 FDR: 97416
[29:20] Calculating protein q-values
[29:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[29:20] Quantification
[29:20] Precursors with scored PTMs at 1% FDR: 2244 out of 2330 considered
[29:20] Precursors with all scored PTM sites unoccupied at 1% FDR: 93692
[29:20] Precursors with PTMs localised (when required) with > 90% confidence: 2170 out of 2244

[29:21] File #2/6
[29:21] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[29:42] Pre-processing...
[29:42] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 148906 precursors in range
[29:42] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[29:43] RT window set to 0.433362
[29:43] Recommended MS1 mass accuracy setting: 2.8 ppm
[29:43] Searching decoys
[29:44] Main search
[29:45] Removing low confidence identifications
[29:49] Removing interfering precursors
[29:50] Training neural networks on 118697 target and 62654 decoy PSMs
[30:03] Training neural networks on 118505 target and 66764 decoy PSMs
[30:16] Precursors at 1% peptidoform FDR: 94496
[30:16] Number of IDs at 0.01 FDR: 96332
[30:16] Calculating protein q-values
[30:16] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[30:16] Quantification
[30:17] Precursors with scored PTMs at 1% FDR: 2205 out of 2307 considered
[30:17] Precursors with all scored PTM sites unoccupied at 1% FDR: 92624
[30:17] Precursors with PTMs localised (when required) with > 90% confidence: 2141 out of 2205

[30:17] File #3/6
[30:17] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[30:38] Pre-processing...
[30:39] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 148906 precursors in range
[30:39] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[30:39] RT window set to 0.435957
[30:39] Recommended MS1 mass accuracy setting: 2.9 ppm
[30:40] Searching decoys
[30:40] Main search
[30:42] Removing low confidence identifications
[30:45] Removing interfering precursors
[30:46] Training neural networks on 118318 target and 62131 decoy PSMs
[31:00] Training neural networks on 118101 target and 66529 decoy PSMs
[31:12] Precursors at 1% peptidoform FDR: 94495
[31:13] Number of IDs at 0.01 FDR: 96575
[31:13] Calculating protein q-values
[31:13] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[31:13] Quantification
[31:13] Precursors with scored PTMs at 1% FDR: 2262 out of 2318 considered
[31:13] Precursors with all scored PTM sites unoccupied at 1% FDR: 93036
[31:13] Precursors with PTMs localised (when required) with > 90% confidence: 2190 out of 2262

[31:14] File #4/6
[31:14] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[31:35] Pre-processing...
[31:36] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 148906 precursors in range
[31:36] Calibrating with mass accuracies 22 (MS1), 25 (MS2)
[31:36] RT window set to 0.450397
[31:36] Recommended MS1 mass accuracy setting: 3 ppm
[31:36] Searching decoys
[31:37] Main search
[31:39] Removing low confidence identifications
[31:42] Removing interfering precursors
[31:43] Training neural networks on 118947 target and 62850 decoy PSMs
[31:56] Training neural networks on 118748 target and 67193 decoy PSMs
[32:09] Precursors at 1% peptidoform FDR: 96023
[32:09] Number of IDs at 0.01 FDR: 98229
[32:09] Calculating protein q-values
[32:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[32:09] Quantification
[32:10] Precursors with scored PTMs at 1% FDR: 2547 out of 2664 considered
[32:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 94259
[32:10] Precursors with PTMs localised (when required) with > 90% confidence: 2472 out of 2547

[32:11] File #5/6
[32:11] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[32:32] Pre-processing...
[32:33] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 148906 precursors in range
[32:33] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[32:33] RT window set to 0.450624
[32:33] Recommended MS1 mass accuracy setting: 2.9 ppm
[32:34] Searching decoys
[32:34] Main search
[32:36] Removing low confidence identifications
[32:39] Removing interfering precursors
[32:40] Training neural networks on 120906 target and 63054 decoy PSMs
[32:53] Training neural networks on 120717 target and 67506 decoy PSMs
[33:06] Precursors at 1% peptidoform FDR: 98366
[33:07] Number of IDs at 0.01 FDR: 101157
[33:07] Calculating protein q-values
[33:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[33:07] Quantification
[33:07] Precursors with scored PTMs at 1% FDR: 2569 out of 2735 considered
[33:07] Precursors with all scored PTM sites unoccupied at 1% FDR: 96162
[33:07] Precursors with PTMs localised (when required) with > 90% confidence: 2492 out of 2569

[33:08] File #6/6
[33:08] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[33:30] Pre-processing...
[33:30] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 148906 precursors in range
[33:30] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[33:30] RT window set to 0.440346
[33:31] Recommended MS1 mass accuracy setting: 3 ppm
[33:31] Searching decoys
[33:31] Main search
[33:33] Removing low confidence identifications
[33:36] Removing interfering precursors
[33:38] Training neural networks on 120936 target and 62138 decoy PSMs
[33:51] Training neural networks on 120759 target and 67296 decoy PSMs
[34:04] Precursors at 1% peptidoform FDR: 98209
[34:05] Number of IDs at 0.01 FDR: 99959
[34:05] Calculating protein q-values
[34:05] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[34:05] Quantification
[34:05] Precursors with scored PTMs at 1% FDR: 2580 out of 2699 considered
[34:05] Precursors with all scored PTM sites unoccupied at 1% FDR: 95848
[34:05] Precursors with PTMs localised (when required) with > 90% confidence: 2507 out of 2580

[34:06] Cross-run analysis
[34:06] Reading quantification information: 6 files
[34:08] Target precursors at 1% global q-value: 119514
[34:08] Quantifying peptides
[35:06] Quantification parameters: 0.310808, 0.00146267, 0.00137771, 0.0119099, 0.0121793, 0.0118406, 0.133713, 0.210415, 0.162736, 0.0133688, 0.0367049, 0.0145836, 0.280769, 0.0521532, 0.0718142, 0.011096
[35:06] Quantifying proteins
[35:07] Calculating q-values for protein and gene groups
[35:07] Calculating global q-values for protein and gene groups
[35:07] Protein groups with global q-value <= 0.01: 11349
[35:09] Compressed report saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[35:09] Stats report saved to /home/robbe/PB_output/results/Post_hoc_Astral/HYE_Astral/diann_v2.5.0/report.stats.tsv

