
DIA-NN 2.5.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Apr 12 2026 10:45:33
Current date and time: Thu Apr 30 10:46:26 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/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report.tsv --threads 32 --missed-cleavages 2 --min-pep-len 7 --max-pep-len 30 --mass-acc 20 --mass-acc-ms1 20 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 2 --max-pr-charge 4 --min-pr-mz 400 --max-pr-mz 1200 --min-fr-mz 200 --max-fr-mz 2000 --unimod4 --var-mod UniMod:35,15.994915,M --gen-spec-lib --fasta-search --reanalyse 

Thread number set to 32
Maximum number of missed cleavages set to 2
Min peptide length set to 7
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 2
Max precursor charge set to 4
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
Cysteine carbamidomethylation enabled as a fixed modification
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
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 

6 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:06] Processing FASTA
[0:09] Assembling elution groups
[0:19] 8103720 precursors generated
[0:19] Protein names missing for some isoforms
[0:19] Gene names missing for some isoforms
[0:19] Library contains 31680 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:25] [0:45] [7:50] [8:25] [8:30] [8:35] Saving the library to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report-lib.predicted.speclib
[8:40] Initialising library
[8:58] Loading spectral library /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report-lib.predicted.speclib
[9:01] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[9:02] Spectral library loaded: 31832 protein isoforms, 43199 protein groups and 8103720 precursors in 3825450 elution groups (targets and decoys).
[9:02] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[9:03] Annotating library proteins with information from the FASTA database
[9:03] Protein names missing for some isoforms
[9:03] Gene names missing for some isoforms
[9:03] Library contains 31680 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[9:08] Initialising library

First pass: generating a spectral library from DIA data

[9:23] File #1/6
[9:23] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[10:09] Pre-processing...
[10:12] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 7009928 precursors in range
[10:13] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[10:31] RT window set to 1.21828
[10:31] Peak width: 2.94
[10:31] Scan window radius set to 6
[10:31] Recommended MS1 mass accuracy setting: 2.6 ppm
[10:41] Searching decoys
[11:31] Main search
[13:08] Removing low confidence identifications
[13:28] Removing interfering precursors
[13:44] Training neural networks on 216917 target and 189866 decoy PSMs
[14:30] Training neural networks on 216917 target and 185805 decoy PSMs
[15:04] Precursors at 1% peptidoform FDR: 96005
[15:05] Number of IDs at 0.01 FDR: 97767
[15:05] Calculating protein q-values
[15:06] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[15:06] Quantification
[15:07] Precursors with scored PTMs at 1% FDR: 2229 out of 2353 considered
[15:07] Precursors with all scored PTM sites unoccupied at 1% FDR: 93776
[15:07] Precursors with PTMs localised (when required) with > 90% confidence: 2142 out of 2229
[15:08] Quantification information saved to /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw.quant

[15:08] File #2/6
[15:08] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[16:10] Pre-processing...
[16:13] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 7009928 precursors in range
[16:14] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[16:31] RT window set to 1.18611
[16:31] Recommended MS1 mass accuracy setting: 2.7 ppm
[16:40] Searching decoys
[17:31] Main search
[19:05] Removing low confidence identifications
[19:25] Removing interfering precursors
[19:38] Training neural networks on 208134 target and 179642 decoy PSMs
[20:25] Training neural networks on 208134 target and 175916 decoy PSMs
[21:07] Precursors at 1% peptidoform FDR: 96788
[21:09] Number of IDs at 0.01 FDR: 98909
[21:09] Calculating protein q-values
[21:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[21:09] Quantification
[21:10] Precursors with scored PTMs at 1% FDR: 2301 out of 2459 considered
[21:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 94487
[21:10] Precursors with PTMs localised (when required) with > 90% confidence: 2224 out of 2301
[21:11] Quantification information saved to /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw.quant

[21:12] File #3/6
[21:12] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[21:58] Pre-processing...
[22:00] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 7009928 precursors in range
[22:01] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[22:19] RT window set to 1.25091
[22:19] Recommended MS1 mass accuracy setting: 2.8 ppm
[22:28] Searching decoys
[23:22] Main search
[25:04] Removing low confidence identifications
[25:26] Removing interfering precursors
[25:41] Training neural networks on 219376 target and 192034 decoy PSMs
[26:23] Training neural networks on 219376 target and 187898 decoy PSMs
[27:00] Precursors at 1% peptidoform FDR: 97634
[27:02] Number of IDs at 0.01 FDR: 99802
[27:02] Calculating protein q-values
[27:02] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[27:02] Quantification
[27:03] Precursors with scored PTMs at 1% FDR: 2327 out of 2529 considered
[27:03] Precursors with all scored PTM sites unoccupied at 1% FDR: 95307
[27:03] Precursors with PTMs localised (when required) with > 90% confidence: 2236 out of 2327
[27:04] Quantification information saved to /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw.quant

[27:05] File #4/6
[27:05] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[27:53] Pre-processing...
[27:55] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 7009928 precursors in range
[27:56] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[28:16] RT window set to 1.35416
[28:16] Recommended MS1 mass accuracy setting: 3 ppm
[28:29] Searching decoys
[29:31] Main search
[31:46] Removing low confidence identifications
[32:13] Removing interfering precursors
[32:28] Training neural networks on 221817 target and 196080 decoy PSMs
[33:24] Training neural networks on 221817 target and 191817 decoy PSMs
[34:12] Precursors at 1% peptidoform FDR: 97958
[34:14] Number of IDs at 0.01 FDR: 100139
[34:14] Calculating protein q-values
[34:15] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[34:15] Quantification
[34:17] Precursors with scored PTMs at 1% FDR: 2907 out of 3077 considered
[34:17] Precursors with all scored PTM sites unoccupied at 1% FDR: 95051
[34:17] Precursors with PTMs localised (when required) with > 90% confidence: 2785 out of 2907
[34:18] Quantification information saved to /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw.quant

[34:18] File #5/6
[34:18] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[35:08] Pre-processing...
[35:11] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 7009928 precursors in range
[35:12] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[35:34] RT window set to 1.44596
[35:34] Recommended MS1 mass accuracy setting: 2.8 ppm
[35:48] Searching decoys
[37:13] Main search
[39:45] Removing low confidence identifications
[40:12] Removing interfering precursors
[40:30] Training neural networks on 225033 target and 198380 decoy PSMs
[41:30] Training neural networks on 225033 target and 193965 decoy PSMs
[42:25] Precursors at 1% peptidoform FDR: 98391
[42:27] Number of IDs at 0.01 FDR: 100274
[42:27] Calculating protein q-values
[42:28] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[42:28] Quantification
[42:30] Precursors with scored PTMs at 1% FDR: 2939 out of 3085 considered
[42:30] Precursors with all scored PTM sites unoccupied at 1% FDR: 95512
[42:30] Precursors with PTMs localised (when required) with > 90% confidence: 2816 out of 2939
[42:31] Quantification information saved to /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw.quant

[42:31] File #6/6
[42:31] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[43:26] Pre-processing...
[43:29] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 7009928 precursors in range
[43:30] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[43:52] RT window set to 1.29972
[43:53] Recommended MS1 mass accuracy setting: 2.7 ppm
[44:08] Searching decoys
[45:24] Main search
[47:29] Removing low confidence identifications
[47:53] Removing interfering precursors
[48:06] Training neural networks on 220314 target and 194821 decoy PSMs
[48:52] Training neural networks on 220314 target and 191020 decoy PSMs
[49:35] Precursors at 1% peptidoform FDR: 97548
[49:37] Number of IDs at 0.01 FDR: 99969
[49:37] Calculating protein q-values
[49:37] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[49:37] Quantification
[49:39] Precursors with scored PTMs at 1% FDR: 2835 out of 3144 considered
[49:39] Precursors with all scored PTM sites unoccupied at 1% FDR: 94863
[49:39] Precursors with PTMs localised (when required) with > 90% confidence: 2718 out of 2835
[49:40] Quantification information saved to /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw.quant

[49:40] Cross-run analysis
[49:40] Reading quantification information: 6 files
[50:03] Target precursors at 1% global q-value: 130803
[50:04] Quantifying peptides
[50:38] Assembling protein groups
[50:40] Quantifying proteins
[50:40] Calculating q-values for protein and gene groups
[50:42] Calculating global q-values for protein and gene groups
[50:42] Protein groups with global q-value <= 0.01: 11646
[50:45] Compressed report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[50:45] Stats report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report-first-pass.stats.tsv
[50:45] Generating spectral library:
[50:48] 140821 target and 7716 decoy precursors saved
WARNING: 19889 precursors without any fragments annotated were skipped
[50:49] Spectral library saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report-lib.parquet

[50:50] Loading spectral library /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report-lib.parquet
[50:51] Spectral library loaded: 17314 protein isoforms, 17193 protein groups and 148537 precursors in 139479 elution groups (targets and decoys).
[50:51] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[50:51] Annotating library proteins with information from the FASTA database
[50:51] Protein names missing for some isoforms
[50:51] Gene names missing for some isoforms
[50:51] Library contains 17304 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[50:51] Initialising library
[50:53] Saving the library to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report-lib.parquet.skyline.speclib


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

[50:53] File #1/6
[50:53] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[51:09] Pre-processing...
[51:10] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 140821 precursors in range
[51:10] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[51:11] RT window set to 0.413717
[51:11] Recommended MS1 mass accuracy setting: 3.2 ppm
[51:11] Searching decoys
[51:12] Main search
[51:15] Removing low confidence identifications
[51:19] Removing interfering precursors
[51:20] Training neural networks on 111280 target and 58286 decoy PSMs
[51:38] Training neural networks on 111111 target and 60683 decoy PSMs
[51:55] Precursors at 1% peptidoform FDR: 87907
[51:55] Number of IDs at 0.01 FDR: 90991
[51:55] Calculating protein q-values
[51:56] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[51:56] Quantification
[51:56] Precursors with scored PTMs at 1% FDR: 1979 out of 2092 considered
[51:56] Precursors with all scored PTM sites unoccupied at 1% FDR: 87338
[51:56] Precursors with PTMs localised (when required) with > 90% confidence: 1919 out of 1979

[51:57] File #2/6
[51:57] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[52:15] Pre-processing...
[52:16] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 140821 precursors in range
[52:16] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[52:17] RT window set to 0.437251
[52:17] Recommended MS1 mass accuracy setting: 3.4 ppm
[52:17] Searching decoys
[52:18] Main search
[52:20] Removing low confidence identifications
[52:24] Removing interfering precursors
[52:26] Training neural networks on 112062 target and 59217 decoy PSMs
[52:43] Training neural networks on 111869 target and 61382 decoy PSMs
[53:02] Precursors at 1% peptidoform FDR: 89351
[53:02] Number of IDs at 0.01 FDR: 91681
[53:02] Calculating protein q-values
[53:02] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[53:02] Quantification
[53:03] Precursors with scored PTMs at 1% FDR: 2040 out of 2164 considered
[53:03] Precursors with all scored PTM sites unoccupied at 1% FDR: 88003
[53:03] Precursors with PTMs localised (when required) with > 90% confidence: 1987 out of 2040

[53:04] File #3/6
[53:04] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[53:20] Pre-processing...
[53:21] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 140821 precursors in range
[53:21] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[53:21] RT window set to 0.42973
[53:21] Recommended MS1 mass accuracy setting: 3.2 ppm
[53:21] Searching decoys
[53:22] Main search
[53:24] Removing low confidence identifications
[53:29] Removing interfering precursors
[53:31] Training neural networks on 112203 target and 59407 decoy PSMs
[53:51] Training neural networks on 112041 target and 61451 decoy PSMs
[54:08] Precursors at 1% peptidoform FDR: 89625
[54:08] Number of IDs at 0.01 FDR: 91983
[54:08] Calculating protein q-values
[54:08] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[54:08] Quantification
[54:10] Precursors with scored PTMs at 1% FDR: 2051 out of 2162 considered
[54:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 88355
[54:10] Precursors with PTMs localised (when required) with > 90% confidence: 1989 out of 2051

[54:10] File #4/6
[54:10] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[54:27] Pre-processing...
[54:27] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 140821 precursors in range
[54:27] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[54:28] RT window set to 0.437679
[54:28] Recommended MS1 mass accuracy setting: 3.5 ppm
[54:28] Searching decoys
[54:29] Main search
[54:31] Removing low confidence identifications
[54:34] Removing interfering precursors
[54:35] Training neural networks on 113029 target and 60863 decoy PSMs
[54:51] Training neural networks on 112862 target and 62760 decoy PSMs
[55:12] Precursors at 1% peptidoform FDR: 91254
[55:13] Number of IDs at 0.01 FDR: 93316
[55:13] Calculating protein q-values
[55:13] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[55:13] Quantification
[55:13] Precursors with scored PTMs at 1% FDR: 2321 out of 2459 considered
[55:13] Precursors with all scored PTM sites unoccupied at 1% FDR: 89466
[55:13] Precursors with PTMs localised (when required) with > 90% confidence: 2246 out of 2321

[55:14] File #5/6
[55:14] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[55:33] Pre-processing...
[55:34] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 140821 precursors in range
[55:34] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[55:34] RT window set to 0.442325
[55:34] Recommended MS1 mass accuracy setting: 3 ppm
[55:34] Searching decoys
[55:35] Main search
[55:38] Removing low confidence identifications
[55:42] Removing interfering precursors
[55:43] Training neural networks on 113298 target and 59910 decoy PSMs
[56:02] Training neural networks on 113124 target and 62635 decoy PSMs
[56:20] Precursors at 1% peptidoform FDR: 92372
[56:20] Number of IDs at 0.01 FDR: 94444
[56:20] Calculating protein q-values
[56:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[56:20] Quantification
[56:21] Precursors with scored PTMs at 1% FDR: 2446 out of 2552 considered
[56:21] Precursors with all scored PTM sites unoccupied at 1% FDR: 90469
[56:21] Precursors with PTMs localised (when required) with > 90% confidence: 2372 out of 2446

[56:22] File #6/6
[56:22] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[56:41] Pre-processing...
[56:42] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 140821 precursors in range
[56:42] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[56:42] RT window set to 0.449273
[56:42] Recommended MS1 mass accuracy setting: 3 ppm
[56:42] Searching decoys
[56:43] Main search
[56:46] Removing low confidence identifications
[56:50] Removing interfering precursors
[56:52] Training neural networks on 113070 target and 60018 decoy PSMs
[57:09] Training neural networks on 112913 target and 62840 decoy PSMs
[57:27] Precursors at 1% peptidoform FDR: 91213
[57:28] Number of IDs at 0.01 FDR: 93770
[57:28] Calculating protein q-values
[57:28] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[57:28] Quantification
[57:28] Precursors with scored PTMs at 1% FDR: 2374 out of 2508 considered
[57:28] Precursors with all scored PTM sites unoccupied at 1% FDR: 89653
[57:28] Precursors with PTMs localised (when required) with > 90% confidence: 2298 out of 2374

[57:29] Cross-run analysis
[57:29] Reading quantification information: 6 files
[57:32] Target precursors at 1% global q-value: 112725
[57:32] Quantifying peptides
[58:26] Quantification parameters: 0.317905, 0.00144974, 0.00128629, 0.014253, 0.0643398, 0.0571128, 0.218762, 0.108822, 0.126483, 0.118238, 0.0501938, 0.0580414, 0.161918, 0.0515169, 0.0607044, 0.0118099
[58:38] Quantifying proteins
[58:38] Calculating q-values for protein and gene groups
[58:38] Calculating global q-values for protein and gene groups
[58:38] Protein groups with global q-value <= 0.01: 11177
[58:41] Compressed report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[58:41] Stats report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral/diann_v2.5.0/report.stats.tsv

